To help you understand the trends surrounding AI and other new technologies and what we expect to happen in the future, our highly experienced Kiplinger Letter team will keep you abreast of the latest developments and forecasts. (Get a free issue of The Kiplinger Letter or subscribe.) You'll get all the latest news first by subscribing, but we will publish many (but not all) of the forecasts a few days afterward online. Here’s the latest…

It’s a repeat of the 1990s heyday for information technology sellers. “AI is driving the strongest IT spending growth since 1996,” according to Stephen Minton, an analyst at tech market research firm IDC.

Global IT spending will jump 10% in 2026 compared with 2025, according to Gartner, a tech market research firm, pushing the IT market above $6 trillion. This comes after a very strong 2025.

Spending on AI data centers leads the way, with nearly 20% growth in the $500 billion data center market, an especially big windfall for Nvidia, the leading seller of AI chips. These “fantastically expensive” AI-optimized servers continue to sell as fast as they can be made, said John Lovelock, an analyst at Gartner, in a recent online presentation.

North America dominates global spending on AI servers for data centers, accounting for half of the total, according to Gartner. Giant AI builders such as Alphabet, Amazon, Meta and Microsoft are set to make up two-thirds of the spending as they race to improve their AI.

Top AI systems are seeing exploding sales, as businesses and governments shell out more money to access advanced AI tools from Google, OpenAI, Anthropic, Mistral AI, Databricks, Alibaba and others. Gartner expects a staggering 67% yearly spending growth rate on generative AI models through 2029.

Spending will be strong on cloud computing, software and IT services, too. Software sales are boosted by vendors hiking prices to account for new AI features, found in software used for analytics, sales, supply chain management and more. Software vendors feel intense pressure to introduce AI features. “It will be an extinction-level event for software not to have generative AI feature functionality in their product,” said Lovelock.

Smartphone and PC sales are in for solid growth as consumers and businesses seek out new AI-enabled models that can run AI software directly on the device. There are tailwinds beyond AI, such as an ongoing shift to cloud computing from local servers, especially by smaller companies. The expiration of support for Windows 10 by Microsoft also continues to spur companies to update PC fleets.

This level of spending is not sustainable forever, Minton noted in a recent online presentation of IDC’s forecast. But he also doesn’t see any signs of a bubble about to burst. However, there is a bit of circularity to current IT spending growth, as AI spending lifts the overall economy, which helps companies and boosts business sentiment. That drives business IT spending, including investments in AI.

Businesses express some anxiety about spending more on IT, but it’s not dinging budgets yet, with business tech spending poised to rise 10%. Many companies are starting to think of AI as a necessity to compete. Meanwhile, a lot of spending can’t be cut because it’s for must-have IT, such as cloud computing. Among the IT categories most immune to budget cuts: AI tools, software and security.

Next year is likely to be a big year for businesses racing to benefit from AI, so here’s some business advice: Have an AI policy that offers guidance to workers about what’s allowed and what’s not, and sets the rules for security and privacy. Break individual jobs into small tasks and see if AI can automate or augment a few of them.

Test and closely evaluate pilot projects. Encourage employees to test and use AI tools that the company approves. Consider sharing short video tutorials on best practices. Experiment with free AI chatbots and harness the AI tools in software already in use at your business. Many companies are initially focusing on business productivity. AI can save time by summarizing meetings, emails and reports. Or it can brainstorm or analyze data, allowing workers to make more efficient use of their time and effort.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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It's no longer an esoteric technology that interests only nerds. Now, people use the technology to write, create images, edit videos, analyze data and write code.

As AI continues to impact every industry, the personal finance industry hasn't been left behind. The AI-powered personal finance management market was valued at $1.48 billion in 2024, according to Research and Markets.

Kiplinger's Adviser Intel, formerly known as Building Wealth, is a curated network of trusted financial professionals who share expert insights on wealth building and preservation. Contributors, including fiduciary financial planners, wealth managers, CEOs and attorneys, provide actionable advice about retirement planning, estate planning, tax strategies and more. Experts are invited to contribute and do not pay to be included, so you can trust their advice is honest and valuable.

It's projected to be a $1.63 billion market by the end of 2025, at a compounded annual growth rate (CAGR) of 10.1%, and a $2.37 billion market in 2029, at a CAGR of 9.8%.

From budgeting, saving and investing to robo-advising, financial coaching, credit scoring and debt management, AI continues to shape personal finance management, providing value across the globe.

Let's look at some of the applications of AI in personal finance, the challenges with adopting AI and tips for wise usage of AI.

AI and budgeting

AI-powered tools can help with:

Data aggregation and categorization. AI-powered tools such as Monarch, YNAB, PocketGuard and Mint AI, among others, can pull data from your bank accounts, credit cards and payment history to identify spending patterns and categorize transactions.

Based on this information, you can create a budget to gain better control of your finances. These apps can also use relevant information to suggest areas in which you can modify spending habits to pursue more important goals.

Automated budget creation. AI-powered tools such as Galaxy.ai and Tiller can create a personalized budget based on your income, expenses and financial goals. They'll suggest how you can better allocate your income across expenses to help achieve your goals.

Predictive forecasting. Some budgeting tools (Drivetrain and SuperAGI, among others) can use AI to forecast how your budget will change if your income changes, unexpected expenses arise or you take out a loan.

Anomaly detection. Some AI tools (such as Expenzey and Cleo) can use your past spending habits to flag unusual transactions or overspending in real time. They help prevent fraud and ensure you stay on budget.

Expenses tracking. Budgeting tools allow you to see how close you are to reaching your budget limits. Examples include Mint AI and Cleo.

Bill negotiation. Apps such as PocketGuard can identify bills that might be too high. They'll automatically negotiate with the relevant service providers to lower your expenses.

Automated bill payment. SuperAGI and Mint AI, among others, automate bill payments to a range of providers.

AI and saving

For some, the main point of budgeting is to foster saving.

AI-powered budgeting tools have features that can help. These include:

• Identifying areas to cut expenses. SuperAGI, YNAB, Tiller and PocketGuard
• Paying yourself first by automating savings. PocketGuard, Albert and Oportun
• Identifying and canceling unwanted subscriptions. Rocket Money and Subscription Stopper

AI, investing and financial planning

Some AI tools can suggest how to invest based on your financial goals, time horizon and risk tolerance.

For example, Empower provides investment recommendations based on investment goals and risk tolerance. It also offers retirement planning tools.

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Some AI-powered tools provide comprehensive financial planning that goes beyond investment management.

For example, Albert combines AI with human advisers to provide comprehensive money management.

Even robo-advisers such as Acorns and Wealthfront use AI to optimize client portfolios and automate portfolio rebalancing.

AI and financial education

Albert has a feature called Genius in which an AI tool can act as a virtual financial coach.

Large-language models (LLMs) such as ChatGPT, Perplexity and Claude, among others, can also act as a financial coach and provide a comprehensive financial education.

Most of the apps we've discussed are also built in a chatbot style, so you can ask questions and get personalized answers if they have access to your financial information.

AI, credit scoring and debt management

Some financial institutions now use AI for credit scoring. These combine traditional credit data with alternative sources such as utility bills, transaction history, income, work history and other behavioral data to evaluate creditworthiness. Examples include FICO Score XD and Zest AI.

Consumers can use platforms such as Experian Boost and Credit Karma to improve their credit scores. They use AI to analyze multiple data points to provide personalized suggestions.

Navigating the risks of AI in personal finance

Despite the benefits that AI provides, certain risks remain with its usage in general and in personal finance management in particular.

Some of the most important include:

Limits to the possibility of personalization. AI-powered apps don't have the emotional intelligence and human judgment required to offer truly personalized advice.

While it can help with the automation of repetitive tasks and the provision of information, the emotive element makes human financial advisers necessary.

Privacy concerns. To provide more valuable advice, AI-powered apps will require more personal information, including sensitive personal data. Given concerns about cybersecurity, this is a risk.

AI models can be hacked to make the information they provide reflect a particular ideology or the personal views of the attacker.

Factual mistakes. Generative AI can be factually inaccurate in many cases. They sometimes cite sources that don't exist.

What can you do about these risks?

While AI-powered apps can help, they shouldn't be a replacement for human financial advisers.

Instead, advisers should find a way to integrate AI into their activities so they can provide maximum value to their clients.

Other ways to mitigate risks:

Data-protection policies. Before using any AI-powered app, read its data-protection policies. Choose those you're confident have the policies in place to protect you.

Don't ignore reputable blogs. Look for blogs that provide information from financial experts to confirm what AI tells you.

By familiarizing yourself with reputable blogs, you become insulated from false information, because LLMs might not always be objective.

Provide AI with accurate information. The quality of what you get from AI-powered apps is proportional to the quality of the information you provide.

If you're sure a platform can protect your data, provide relevant information to provide better value.

Final thoughts

The opportunities for the use of AI in personal finance are enormous. However, given the risks, it is up to you to use AI-powered apps responsibly.

If you have a human adviser, consult them before making significant financial choices based on AI recommendation.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

This "golden handcuffs" comp structure incentivizes sticking around through rolling vesting periods, and the concentrated stock positions can make portfolios feel precarious.

Meanwhile, AI implementation and economic uncertainty are calling the security of many roles into question.

The confluence of these two challenges leads to executives feeling stuck while doing well and building real wealth while feeling unstable. How can executives plan thoughtfully for freedom in a world that's changing so fast?

Kiplinger's Adviser Intel, formerly known as Building Wealth, is a curated network of trusted financial professionals who share expert insights on wealth building and preservation. Contributors, including fiduciary financial planners, wealth managers, CEOs and attorneys, provide actionable advice about retirement planning, estate planning, tax strategies and more. Experts are invited to contribute and do not pay to be included, so you can trust their advice is honest and valuable.

A financial planning style known as Coast FI (short for Coast Financial Independence) may hold a compelling solution to the planning needs of modern professionals.

What is Coast FI?

Coast FI is a subset of the FIRE (Financial Independence, Retire Early) movement. I'm not a personal fan of the FIRE movement, as it most often leads to casual versions of financial planning, attaching personal identity to one component of a plan (a future retirement date) and a challenging shift to spending down assets after years of deferring joy to get there.

However, if done well, a FIRE plan can serve as a financial plan attached to a personal retirement goal.

Coast FI takes this idea and, instead of simply saving to retire as early as possible, encourages a focus on a different question: How much would you need to have invested, such that if you didn't touch your nest egg, it would grow to support your future retirement spending needs?

Then you're free to work only as much as needed to support your current lifestyle — in other words, you're free to let your investments coast.

This takes the simple calculus of an early retirement plan and adds an important lever — one for optionality. It also more closely mirrors the actual trajectory of most people's retirement.

Rather than a one-and-done retirement date, executives more often have corporate exits and reentries, unplanned exits, sabbaticals, consulting jobs and so on. Coast FI isn't built on "retirement" — it's built on flexibility.

For a high-earning modern executive, it reframes the question from "How much more do I need?" to "How much freedom have I already earned?"

How Coast FI addresses golden handcuffs

The goal of "golden handcuffs" like RSUs and stock options is to retain employees with rolling vesting schedules, making it challenging (or at least expensive) to target an exit point.

Personal goals might get delayed while promotions add to equity but not directly to freedom. If you're always a quarter away from your next vest, when do you leave?

If you add to this "the new golden handcuffs" of the increasing cost of living and an executive's strong tie to professional identity, you can see how barriers toward exit targets are ever-present.

To address golden handcuffs in a retirement plan, most people will intuitively look at a few key variables:

• The current size of their investment portfolio
• The target size of their future retirement portfolio
• How much additional investing needs to happen to get there

Where Coast FI helps executives move toward freedom is by including annual cash flow needs into the equation. At a certain point, a Coast FI plan will show that no more investing is needed to reach the defined goals, assuming no withdrawals happen until then.

This number will change each year based on portfolio growth and the years remaining until retirement.

With this number defined, an executive might find that they are able to make their corporate exit without waiting around for future vesting dates or use a few consulting contracts to cover living expenses and begin to loosen their golden handcuffs.

How Coast FI addresses job instability

While executives are locked into golden handcuffs, we are seeing regular reports of layoffs and how AI innovation is coming for white-collar jobs. This isn't the best position from which to do real, high-quality, financial planning.

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This is where the Coast FI philosophy can again be helpful, offering crucial information and flexibility as your career develops:

• Have a great job? Continue saving
• Receive a bonus or additional equity? You're closer to your Coast FI number
• Want to leave to consult? Set your revenue targets aligned with your plan
  Get laid off? You know exactly how much you need to make to cover your living expenses at every point along the way

In an uncertain world, modern executives don't need to focus only on an arbitrary early retirement in the future, but also on adaptability throughout their careers. As the AI wave progresses, the Coast FI philosophy offers a sound default way of financial planning so that executives can use their company equity and hard work to build both wealth and freedom.

A Coast FI example

Let's look at "Chris and Jessica" and build a Coast FI plan for them.

The "coast" number. Chris and Jessica are 40-year-old tech executives. They have calculated that at age 60, they'll need $5,000,000 in today's dollars to fund their desired retirement.

To find their Coast number, they'll take the 20 years they have left before retirement, a rate of return for their investments and an inflation rate that will let them calculate how big their nest egg would need to be today to stop saving now.

That math, written out, would look like this:

$5,000,000 * (1+.04) ^ -20 = $2,281,935

So we arrive at Chris and Jessica needing about $2.28 million saved today, growing at 7% per year minus a 3% rate of inflation for the next 20 years to fully fund their retirement goals at age 60.

Equity over time. Chris and Jessica will continue to receive income and equity awards throughout their working years. Their Coast FI plan will help them target savings vs spending rates and build their plans to sell and diversify company stock to meet their goals.

Cash flow targets. Both while working and in the event of a job change, Chris and Jessica's Coast FI plan will tell them how much money they can spend and how much they need to save in any given year to hit their Coast FI number. Once they've hit their number, they can adjust their income need down to reflect no longer needing to save.

The biggest asset of the Coast FI philosophy is the ability to review and refine all the applicable numbers at any point to stay on track with changing careers, markets and goals. This ability makes it a powerful default planning framework.

Financial plans need to be strong enough to build on and flexible enough to withstand changes without breaking.

For the modern executive, especially those looking to build freedom from golden handcuffs in a quickly changing environment, Coast FI plans may offer a convenient mental shortcut to set goals, target action steps and adapt to changes over time.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

As economists and investors try to weigh artificial intelligence’s role in the economy, and with stock market bubble fears on the rise, uncertainty over the fast-moving tech is running high. Taking a longer view than the day-to-day headlines, here are five forecasts to help make sense of what’s coming.

1. There will be a flurry of new AI services from leading AI firms in the next year or two to tap new revenue to cover rising costs. OpenAI, for example, recently launched an AI video social media app called Sora and a new web browser. AI companies will push harder into digital advertising and online shopping, both promising markets for their web search and AI chatbots.

2. Though free options are here to stay, AI price hikes are coming. Top tiers of service, which provide the highest-quality AI responses and much more usage, will see higher prices. Consumers and businesses will have to pay more for AI tools from Microsoft, OpenAI, Alphabet, Anthropic and others. Generative AI is being integrated into most software, from photo editing to sales tools, and prices are sure to rise.

3. AI companies will push harder to tap potentially lucrative new markets, such as education, government, medicine, energy, defense and finance. Education seems ripe for making a lot more revenue in the near term, as both colleges and K-12 schools adopt AI tech. However, note that there’s a lot of pressure to show that the tech pays off, such as by finding clear evidence that AI makes accurate medical diagnoses.

4. Market volatility is likely with bubble fears rising. Remember DeepSeek? Earlier this year, the Chinese AI company sparked a major sell-off of AI tech stocks, plus other stocks in the AI sphere. Some investors thought a new breakthrough meant AI companies wouldn’t need as many chips. That wasn’t true, but expect more DeepSeek moments, stemming from concerns related to tech advances or spending slowdowns that could crimp sales of chips and other hardware needed to support AI services.

5. Shortages of chips, energy, labor and more will slow down AI projects. The continuing shortages mean it’s very likely that some plans for data centers are delayed, as major players rush to find all the needed supplies, ranging from computer memory and storage to HVAC systems and electrical equipment. Meanwhile, there’s growing local opposition to building data centers, which is poised to get more intense. For those who fear that AI spending and development is unsustainable, these headwinds may provide some reassurance that the breakneck spending on data centers will slow down to a more sustainable pace.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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One of the most serious problems AI poses for job seekers is the potential elimination of entire classes of jobs, as well as a reduction in demand for many white-collar positions. The issue is so contentious that Congress introduced a bipartisan bill that would require companies to report jobs lost due to AI to the Department of Labor.

The other way AI can mess with your job search? AI is notorious for both reflecting and perpetuating human biases, such as racism, sexism or agism. If you're an older woman seeking a job, it's essential to be aware of the latest research findings and take steps to mitigate them.

AI absorbs stereotypes about working women

According to research published in Nature, advanced AI systems, known as large language models (LLMs), appear to have formulated some troubling ideas about what a working woman looks like and the types of jobs she can do.

Specifically, an analysis of large language models (LLMS) and millions of videos and images across the web revealed that when women are portrayed in different occupations and social roles, they're almost always depicted as being younger than men in the same positions.

While this is true across all jobs and scenarios, the researchers also found the biggest age gap in pictures depicting high-status, high-paying work. Moreover, this isn't an isolated problem of gender bias, as researchers were specifically looking for a "culture-wide trend."

The fact that LLMs had these misperceptions was especially troubling because the models didn't formulate the idea of which roles women fill by looking at pictures — the LLMs looked at words and still developed biases against older working women.

“Why would it be showing up in billions of words where there’s no visual presentation of people?” Douglas Guilbeault, the study's author and an assistant professor of organizational behavior at Stanford Graduate School of Business, said. “That is really suggesting it’s woven into the fabric of how we categorize and interpret people in the social world.”

In other words, our stereotypes of what men and women are good at, and which women belong in the workforce, are so baked in — despite decades of challenging those perceptions — that AI models now view women as less capable, and capable women as being young.

AI (and online images) are perpetuating these stereotypes

So, why does it matter that online images of success show men or young working women, or that LLMs think all women leaders are young and that women are less experienced than their male counterparts?

AI bias affects the real world

For one thing, many people spend all day online, forming their perceptions of the world based on the images they see. In fact, another recent study revealed that just 45 minutes of exposure to online pictures of people in various occupations altered people's perceptions of which gender is associated with specific jobs.

Furthermore, a growing number of companies are utilizing AI to review resumes, screen candidates, and even conduct interviews, which could make it harder for women to secure a seat at the table — and to retain the seats they've worked so hard to claim.

When AI writes resumes

In fact, when researchers asked ChatGPT to generate 34,500 unique resumes for 54 different jobs using traditionally male and female names, the resumes also depicted women as being less experienced and younger. Then, when ChatGPT was asked to evaluate resume quality, older men were given the highest ratings even in situations when fake male and female candidates had been given the exact same credentials from the start.

Women have long been the subject of age discrimination. Older women, who tend to live longer than men and often have less saved for retirement, may find themselves in a position where they need to work longer than their male counterparts.

If AI is screening them out, and they're facing hiring managers who have spent years online having their perceptions of professionals shaped by biased images, what chance do they have of fair treatment in the workforce?

How can you beat the AI algorithm?

AI isn't going anywhere, and the reality is that its role in screening job candidates will only grow. That's a problem for employers and society to address, but in the meantime, how can you beat an AI algorithm to get the job you want?

One of the simplest ways to combat AI bias is to limit the recruitment tool's ability to stereotype you. As Leslie Stevens-Huffman writes in Dice, "Consider removing your full address and specific dates from the education and work‑history sections of your résumé, online profiles, and digital portfolio. AI scans all of them, and together they shape the algorithm's picture of you."

You should also study how to navigate AI screens and develop a resume that will help you succeed. "There are tools to help you 'see' your resume the way an AI screener might, says NYU journalism professor Hilke Schellmann. "Sites like Jobscan and others allow you to input a job description and compare your resume to that description to see if your resume matches the role. But beware of looking too good on paper."

Older female job seekers often have to go the extra mile to get past AI-screening tools. For example, you can get a foot in the door by developing a robust network, joining industry associations or pursuing additional certifications.

Hopefully, over time, those developing AI models can find smarter ways to avoid bias. But, until that day comes, this may be just another hurdle that has to be overcome.

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It’s not easy to make sense of the artificial intelligence arms race. Astronomical sums are being spent on building AI data centers, with circular financing deals stoking bubble fears. It’s not yet clear how AI big spenders will make a return on their massive investment.

At the same time, demand for AI continues to outstrip supply. AI revenue is starting to pour in, as adoption by consumers and businesses rises swiftly. Meanwhile, Big Tech companies have mountains of cash and profitable business lines.

What gives? Generative AI is a true breakthrough, but risks related to overspending are on the rise. Meanwhile, a very large portion of recent U.S. economic growth and stock market gains comes from this AI spending.

The major worry is that today’s vast spending on AI data centers is nowhere near economically sustainable. To meet the expected demand for data centers, it will require $500 billion in annual global capex spending on new data centers, according to an analysis by Bain & Company, the management consulting giant.

AI companies will have to find $2 trillion in new yearly revenue by 2030 to arrive at an economically sustainable model. There could be an $800 billion shortfall if firms don’t find new and better ways to boost sales. Don’t mistake Bain as pessimistic, though, says David Crawford, a partner at Bain and chairman of its global Technology, Media & Telecommunications practice.

“We actually believe those things will happen,” Crawford says of finding new revenue. “We're extremely bullish on this trend.” He calls generative AI more significant than anything he’s seen working at Bain for 25 years. “We’re in for an extraordinary period of innovation.”

Of course, there are plenty of others who see the growing chasm between AI spending and revenue as the telltale sign of a bubble forming. That includes many people who agree that AI is a breakthrough technology with huge potential but worry that the hype is outpacing reality.

To drill down on the looming economic challenges, look no further than OpenAI, where sales are surging, but costs are rising faster. OpenAI reportedly will see sales of roughly $10 billion in 2025, a huge feat, since ChatGPT launched in 2022. It aims to make $100 billion by 2029, but it has plans to spend hundreds of billions over the next few years.

The start-up has a complex web of deals that includes a five-year contract to buy $300 billion in computing power from Oracle, and a deal for Nvidia to invest $100 billion in OpenAI. Nvidia’s financing the purchase of its own chips, along with other circular financing deals, has stoked bubble fears. OpenAI also has tie-ups with AMD and Broadcom for chips. Amid the massive future outlays, OpenAI has a private valuation of $500 billion, more than Samsung, Johnson & Johnson or Costco. And Alphabet, Amazon, Meta, Microsoft and others keep spending heavily in an arms race that requires ever more computing power to build leading AI tech.

Consider a few of the major risks we see:

• A lack of rational analysis over spending, notably from some Big Tech leaders who truly believe breakthrough superintelligence is around the corner. They think underinvesting is a bigger risk than overspending.
• Funding the AI build-out is getting less transparent. Meta and others are starting to finance deals via special-purpose vehicles and other transactions that are more opaque than normal capital expenditures. That trend is sure to grow.
• AI chips need to be replaced every three to five years and account for 50% of the spending to build data centers. Even with Goldman Sachs, BlackRock, Apollo and others lining up to finance deals, that replacement cycle requires much more AI revenue.

The capital that’s fueling AI’s ascent is money that can’t be put to other uses. And AI is swallowing up not just dollars, but human labor, including construction workers, electricians, HVAC specialists and IT pros needed to build data centers. Those trends drive up the cost of labor and supplies.

On the other hand, there are signs that this AI boom has staying power. Demand continues to outstrip supply for AI chips and AI computing power. OpenAI has 800 million users, showing how rapidly generative AI has been adopted. Revenue is growing swiftly, with generative AI set to reap $153 billion in revenue this year, according to a prediction by Morgan Stanley. That’s still far below capex spending, but up from zero in 2021.

Still, it’s hard to ignore the unfettered AI exuberance, including rising levels of FOMO (fear of missing out). Tech leaders, such as Jeff Bezos, even concede that some type of bubble is likely, but say it will pay off eventually. It’s hard to predict when AI excitement could cool or a pullback in spending could happen. For now, it looks like the pace of spending is set to continue for two years or more. That could unlock more opportunities with better AI tech, but also pose even more risks.

As overspending on AI occurs, one thing to keep a close eye on is AI revenue. Whole new major markets for AI are needed, beyond work software that merely boosts worker productivity.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Like many people, this reporter has not given much thought to the cash cushion or funding vehicles to pay for long-term care (LTC) later in life. My wife has an LTC insurance policy she got through work 15 years ago that will offset her costs. However, despite diligently building a retirement nest egg, I never really investigated whether I would need long-term care, how much it would cost, and, more importantly, how I would pay for it. Like most folks, I have read stories citing cost guesstimates based on the “average” person. But I’ve done little planning specific to long-term care.

Until late October, that is. That’s when I decided to test run an AI-powered platform called Waterlily that uses artificial intelligence (AI) to predict long-term care needs — decades before they happen — as well as estimate the cost of care and help people find the most optimal LTC insurance policy. These long-term care predictions, according to Waterlily, are powered by an AI platform that compares an individual’s information, like mine, with similar data from 50,000 families and draws from a dataset with over 500 million data points to personalize the LTC predictions.

Waterlily: the AI powered tool predicts long-term care needs

It was an eye-opening exercise that went by in a New York minute — not hours, days, or weeks. In a matter of seconds, after filling out a three-minute intake form that collected information on my personal health, prescriptions, family health history and other relevant data, the Waterlily platform spit out a report to me via email that quickly got the attention of my future self.

So, will I need long-term care one day? Unfortunately, yes, according to Waterlily, which uses prediction models trained on the LTC journeys of other families.

I am currently in my early 60s. Waterlily found that there is a 70% chance that I’ll require long-term care (that’s higher than the 56% odds for the average 65-year-old, Waterlily says, but in line with the 70% of Americans who will eventually need LTC). Waterlily’s AI-driven analytics tool also weighs in on when my care will start. When is that? When I’m 86 years old.

My long-term care needs will last 4.2 years, Waterlily estimates, with a mix of care that starts at home with help from family members (which is less costly), then moves to an assisted living facility, and finally to a nursing home that provides full-time care.

Waterlily predicts my long-term care costs

While hearing that I’ll need care in the later stages of my life was not totally unexpected, it was nonetheless sobering. It was a reality check.

The Waterlily analysis didn’t stop there. The next part of the analysis dives into a topic that keeps Americans up at night: the cost of LTC. And AI doesn’t pull any punches: LTC is not cheap. The $64,000 question is: how much? And, of course, how do you pay for it?

Most people age 50 and older say they are not confident they can pay for a nursing home (62%), assisted living (58%), or home care (51%), according to the University of Michigan’s Institute for Healthcare Policy & Innovation.

No doubt, a long-term event can be financially ruinous. In fact, Lily Vittayarukskul, CEO and founder of Waterlily, says a driving force behind her starting the company was her family’s financial hardship during her teenage years that resulted from providing long-term care to her aunt, diagnosed with terminal colon cancer. “Navigating those two years nearly bankrupted us,” said Vittayarukskul.

Funding long-term care is a costly endeavor. So, getting your arms around the cost sooner rather than later can give you time to plan for and fund any care needs with greater confidence.

My potential costs are staggering. The AI algorithm projected my cost at $1.48 million in inflation-adjusted dollars, with 60% of the cost attributed to an estimated 18-month stay at a full-care facility starting at age 89.

Waterlily maps out a funding plan for long-term care

The final piece of the puzzle is Waterlily’s analysis of how to fund this large potential expenditure later in life.

One myth is that Medicare will cover long-term care costs. In fact, 58% of Americans think Medicare will provide LTC coverage, according to the 2025 Nationwide Retirement Institute Long-Term Care Survey. But Medicare’s LTC coverage is limited and short-term, and does not provide the extended, day-to-day support aging Americans will eventually need, the survey noted.

Waterlily helps you build a plan to pay for LTC. Funding options include self-funding, or using savings to cover LTC bills, buying LTC insurance, as well as using other income sources, such as an annuity.

I opted for a hybrid approach in my hypothetical analysis, using a combination of personal investments and an LTC insurance policy to cover as close to 100% of the total estimated LTC cost as possible.

Waterlily’s platform runs the funding numbers for you. You plug in your funding preferences, and it does the computations. I started with self-funding, earmarking $200,000 of retirement fund assets at a 5% annual return rate with 20-plus years of growth runway. But Waterlily ran the numbers and seconds later informed me that self-funding would only pay for 52% of my projected LTC expenses.

Why getting a high return on investment for LTC insurance can improve retirement outcomes

The next step was using Waterlily’s AI platform to help me close the funding gap by finding an LTC insurance policy that could capture the most coverage in total dollars for my initial lump sum investment, which Vittayarukskul dubs “ROI,” or return on investment.

This is the part of the process where the power of AI shines.

The test. I opted to see whether a $100,000 LTC policy would close my funding shortage. (Of course, this is not an insignificant-sized investment and may not be an option for all Americans.) Waterlily’s new offering, “Quote-and-Apply,” then used AI to crunch and analyze hundreds of thousands of insurance policy configurations and half a billion data points to find the most “mathematically optimal” policies to fit my personal situation. “It calculates the precise return on every premium dollar on the policy you’re considering purchasing,” said Vittayarukskul.

The policies presented are ranked by ROI, highlighting those that will generate the biggest dollar amount of total coverage for my $100,000 policy. Waterlily’s analysis also lets you know if your application is likely to be accepted or rejected for coverage by insurance underwriters based on your medical information.

The results. In less than a second, Waterlily found a $100,000 policy with a 494% ROI and total coverage of $574,000. In my hypothetical example, the combination of self-funding and buying an LTC policy covered 91% of my projected LTC cost. So, in just a few minutes, I was able to determine the age at which my care would begin, how long it would last and its cost. The system also provided a funding plan to cover the costs.

Since my analysis was journalistic in nature, I did not use Waterlily’s Quote-and-Apply system — which skips or pre-fills 70% of application fields based on what’s already known about the applicant — to apply for coverage.

“Families can conduct a mathematically complete analysis of hundreds of thousands of policy permutations, a process that is physically impossible for a human, all in a span of a second,” said Vittayarukskul. “(They can) instantly arrive at (LTC insurance) options with the highest return on investment personalized to an individual or couple.”

LTC plans for couples. Vittayarukskul notes that joint LTC policies that include both spouses can often be less costly than individual ones.

The Waterlily AI platform will also analyze existing LTC policies you might have. For example, Waterlily factored in my wife’s LTC policy with a self-funding investment of $200,000. The system calculated that she would be able to cover 68% of her inflation-adjusted total LTC costs of $1.72 million.

Privacy. As with any AI platform, you should be careful when handing over personal health and financial data. Waterlily's privacy policy states that you may request the deletion of your data by contacting the team via email at hello@joinwaterlily.com.

The University of Michigan's long-term care study found that only 11% of adult respondents said they had bought long-term care insurance.

Vittayarukskul says Waterlily is currently offering this analysis free to consumers on their website, although there is a charge for use by financial advisers.

Read More

• How to Pay for Long-Term Care
• Mom Needs a Nursing Home. Should I Spend Down Her Assets So She Qualifies for Medicaid?
• Holding Wealth: Why Retirees Shouldn't Focus on Leaving an Inheritance
• Average Net Worth by Age

If you’re not sold on using AI to magically put yourself into videos to share with friends, OpenAI has a simple pitch: It’s a "blast."

"We first started playing with this 'upload yourself' feature several months ago on the Sora team, and we all had a blast with it," says OpenAI’s announcement.

That fun, addictive quality was highlighted in the example videos OpenAI shared: A man doing a backflip on a paddleboard, a person riding a horse on top of another horse and a figure skater performing a triple axle with a cat on her head, to name a few. When you use the new social app Sora, and you agree to upload your image and voice, that figure skater could be you.

Sora uses OpenAI’s powerful, and recently updated, AI video creation tool to turn simple text inputs, such as "a guy does a backflip," into highly produced videos with sound. The videos are both fantastical and shockingly realistic, with famous and nonfamous people.

Users can choose to add themselves and share their creations. The videos have watermarks and some guardrails, such as filtering content deemed harmful. But OpenAI is entering a minefield of trying to police certain content and figuring out where to draw the line, especially with teen users. Meanwhile, Sora-created videos are quickly showing up on other platforms.

Sora’s surging popularity will spur copycat apps from Meta, Google, xAI and others. And apps such as Facebook and Instagram will push more AI videos. Given OpenAI’s long-term pursuit of revenue, don’t be surprised if the company focuses on building Sora into a head-to-head competitor with Meta for users and advertising dollars.

Will people want to look at an endless newsfeed of AI videos? The answer is likely yes, at least for many. Just as TikTok caused U.S. social media giants to pivot away from images and text to short-form video, Sora is likely to spur an emphasis on AI-generated videos across the social media landscape.

The coming explosion of AI videos will rattle Washington. Expect Congress to quickly take up AI videos in hearings and new bills, focusing on fears of terrorist propaganda, violent media, privacy risks, harm to kids, misinformation and more. OpenAI’s strategy is to move fast, so it will be hard for lawmakers to keep up.

One glaring early issue is rampant copyright infringement, and it has Hollywood and other artists fuming. Early Sora videos have famous characters and celebrities, which prompted OpenAI to announce changes, but its fast-moving tactics are sure to invite lawsuits. Though OpenAI wants to negotiate with artists and media giants, it likely doesn’t fear lawsuits, especially ones that could settle some of the novel questions around AI videos and copyright.

Don’t expect any federal laws soon, but quick state action is a sure thing. Twenty states already have laws aimed at curbing deceptive uses of AI related to elections, according to the R Street Institute, a public policy think tank. However, regulating the wide-scale emergence of AI videos risks infringing on freedom of expression, so lawsuits over coming state policies are likely, too.

Beyond consumer fun, look for Sora to be a tool often used by advertisers, including small businesses. It gives marketers of all sizes a new way to create highly produced digital video ads and online content that will catch the attention of customers. There’s sure to be lots of viral AI video trends that brands look to capitalize on.

Meanwhile, the future may call for more closely vetting videos on the web as altered or made-up videos feature politicians, business leaders and other prominent people.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Survival instincts have companies scrambling to shift their web strategies — perhaps ending the days of the open internet as we know it.

After decades of pursuing web-optimization strategies that encouraged high-volume content generation, many businesses are now feeling that their content-marketing strategies might be backfiring.

Kiplinger's Adviser Intel, formerly known as Building Wealth, is a curated network of trusted financial professionals who share expert insights on wealth building and preservation. Contributors, including fiduciary financial planners, wealth managers, CEOs and attorneys, provide actionable advice about retirement planning, estate planning, tax strategies and more. Experts are invited to contribute and do not pay to be included, so you can trust their advice is honest and valuable.

Cut out of the deal

The high-value, high-authority content that used to promise better page rankings on Google, Bing or Brave has now been used to train the respective artificial intelligence models (Gemini, ChatGPT, Anthropic, etc.).

Businesses are feeling cut out of the deal — and their web traffic is evidence that those feelings aren't misguided.

Following the release of Google's Search Generative Experience two years ago, websites saw their web traffic dip by as much as 56%, according to Search Engine Land, while others reported figures as high as 60%.

Meanwhile, the number of news-related searches on ChatGPT grew by 212% in the last 18 months, according to a Similarweb report.

Without the incentive of web clicks and ad revenue to drive content creation, the foundation of the web as a free and open entity is called into question.

The websites, organizations, news outlets and businesses that have been creating the content and information that users seek have less reason to open the gates of their content to the AI models that seem to exploit them.

Taking a new look at web strategies

Companies that have seen a collapse of web traffic are re-evaluating their web strategy. How do they survive in a world in which AI use is both increasing and seemingly driving away their traffic?

Two things can be true at once:

• To opt out of the AI economy entirely would be disastrous for businesses
• Companies that freely feed the AI beast might be contributing to their own demise

It's a Catch-22. If companies firewall themselves off from AI, they miss out on the opportunity for AI to be aware of them and serve up their content and services.

If they do nothing, these large language models (LLMs) can continue to cannibalize their expertise without the companies seeing any upside.

The tension of this dynamic is likely to alter the structure and fundamental economics of the internet as we know it.

Given what we know about the internet, about capitalism and about how some of the major companies are handling this fallout, there are three content futures for which companies can start to prepare.

1. The microtransaction/compensation model

According to a CNBC report, while media companies such as The New York Times, Axios and Vanity Fair have been able to establish financial partnerships with AI companies that allow them to train and utilize their reporting for users, such partnerships aren't being offered to every content creator on the internet.

It's why a company such as Cloudflare recently announced it would block AI crawlers until the company was fairly compensated — a move that could turn AI into a microtransaction-dominated space, allowing companies to be paid every time their content is fed to a user.

2. The walled-garden internet

Alternatively, companies could choose to shut everything down, killing the oxygen that feeds LLMs to force paid interaction.

It's not a new concept: Industry groups have long used gated materials as a sales tool for their memberships.

By offering a sample of their content for free, companies might still be able to train AI, while capturing a more cost-effective audience in the process.

3. A winner-takes-all AI landscape

Finally, there's a simple winner-takes-all future, in which the AI platforms eliminate all ambiguity from their responses and offer only specific partner sites to their users.

It's a pay-for-play model that favors larger companies, and it's not dissimilar to the dynamic that's taken over Google search results in recent years.

The key for businesses to understand is that the AI future is still very much unfolding around us.

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As disconcerting as a collapse in web traffic might be, click-through rates and web visitors are no longer the indicators of success they once were. In most cases, a smaller number of users make up a larger portion of successful transactions for businesses.

What businesses can do

The old user numbers are gone. They're never coming back — and there's very little that business owners can do about that.

Instead, businesses should focus on controlling the things they can control and avoid falling into the trap of believing that any one AI web solution will be the definite right one or the only one.

The best AI business plan for the future is one that is nimble and unafraid of trying, failing, adapting and trying again.

Here's what business owners can do:

• Test specific queries and prompts across each LLM monthly and see how your business ranks. Tools such as Semrush, Ahrefs and others can help with this.
• Adjust your content between each benchmark to see what is helping and hurting. Remember not to base too much on any one instance, since AI does not provide the same answer every time.
• If/when you rank well, don't assume you always will. As we've learned with SEO, it is constantly evolving. Your No. 1 rank today doesn't promise a No. 1 rank tomorrow.
• Share and repurpose your content. Put it in front of people where they are, parse it out and share it across various channels — partners, social media, directories, etc. If you're part of an association or a chamber of commerce, those can be solid channels to publish to as well.

To reach customers without relying on search results, you can double down on the channels you own — your website, your email list, text messaging, streaming, events and direct interaction with your customers.

You have the opportunity to build direct relationships at a greater level of scale than ever before. Don't give that up to AI or other intermediary channels.

Beware of trend waves and hype bubbles

AI, like everything else today, is susceptible to trend waves and hype bubbles. As an example, consider the role of the "prompt engineer" — the supposed AI-proof job that we were told everyone would be hiring for two years ago. Now, those roles are essentially gone, if they ever existed.

It's the same thing today: 82% of companies are expected to adopt agentic AI in the next few years, according to a report by the Capgemini Research Instiutute, but that doesn't mean that every website should be reoriented to agentic standards.

Understanding what a fully optimized AI-future might look like should give businesses testing frameworks to bounce ideas off of. They could test what works and what doesn't — without missing out on what's happening right now.

Nothing is certain — preparing for multiple directions and having contingency plans will help businesses succeed regardless of what's ahead.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

As the smartphone industry battles tariffs and cost-conscious consumers, Apple’s new slate of iPhones figures to be a big hit.

Updated mobile software, computer chips and exterior design add up to the biggest iPhone upgrade in years. The new hardware will even catch the attention of those clinging to old models. “Apple’s 2025 product strategy is simple: Increase upgrade rates and shorten replacement cycles,” writes tech market research firm IDC in a note.

The superslim, $1,000 iPhone Air will win over many fans. The redesign is a precursor to Apple’s future foldable phone, set to launch as early as next year. Other models are the standard iPhone 17 (starting at $800) and the Pro and Pro Max (starting at $1,100 and $1,200). There are reports that early demand is very strong.

Apple has stumbled trying to launch useful artificial intelligence features, lagging competitors, such as Alphabet, Microsoft and Meta, when it comes to AI tools. The refreshed phone lineup sets Apple up for success down the road, with upgraded mobile chips that are specially designed for AI tasks right on the device.

“In designing its own chips, Apple is able to customize its specific devices for performance, power efficiency, and available features,” writes William Kerwin, an analyst at Morningstar, in a research note. “Its A-series chips for the iPhone integrate neural engines for AI capabilities like facial recognition and are optimized for power efficiency to deliver best-in-class battery life.”

Advanced hardware and a massive customer base make the iPhone a go-to device for developers creating AI apps. And as Apple catches up with AI, its deliberative approach could pay off by staying focused on privacy and security, plus everyday AI features that work well for most people.

One AI feature that Apple recently highlighted is real-time language translation with its AirPods earbuds. Apple Intelligence can also describe an image on the iPhone screen or in the camera lens, whether it’s a plant, a piece of clothing, a painting or anything in between.

Look for a big AI upgrade next year, when Apple plans a major revamp of its Siri voice assistant. The company may even partner with Google to use its Gemini AI model.

In the long term, the iPhone is expected to see solid growth in a mature smartphone market. Analysts at Morningstar expect 5% yearly growth for iPhone revenue through 2029. Admittedly, though, that is below the 10-year historical growth rate of 7%.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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But a dive into generative AI's authority frameworks — the technical mechanisms and conceptual approaches that large language models (LLMs) use to determine the credibility of information and sources — suggests all that posting effort is more of a placebo for visibility-hungry marketers.

There's considerable evidence — including direct output from ChatGPT itself — that LinkedIn posts don't carry enough authority weight to land a company or an expert in an LLM's answers.

Kiplinger's Adviser Intel, formerly known as Building Wealth, is a curated network of trusted financial professionals who share expert insights on wealth building and preservation. Contributors, including fiduciary financial planners, wealth managers, CEOs and attorneys, provide actionable advice about retirement planning, estate planning, tax strategies and more. Experts are invited to contribute and do not pay to be included, so you can trust their advice is honest and valuable.

Growing use of LinkedIn

The continuing steep growth of both users and revenue at LinkedIn provides evidence of business professionals pouring more time and energy into the social media platform. The Microsoft-owned site says that 1.8 million feed updates are viewed every minute on the platform.

That has caused a proliferation of low-cost services and AI-powered tools that will create LinkedIn content on a company's or executive's behalf.

Companies such as Manila-based MicroSourcing, for instance, will outsource LinkedIn posts for you using "dedicated Filipino teams," while other platforms, such as Hootsuite and Grammarly, will give you a free AI-powered tool to generate LinkedIn posts.

But while generating low-cost posts might provide comfort for anxious chief marketing officers, the authority frameworks of generative search engines don't reward or elevate posters based on volume.

These frameworks serve as a kind of information filter, seeking to pull out low-credibility sources and provide a kind of machine-vetting for the answers it provides.

AI models such as OpenAI's ChatGPT series and Google's Gemini evaluate content through five primary lenses:

Source reputation. The digital provenance of an article matters, so the authority attributed to a piece published in The New York Times, recent questions about political bias notwithstanding, will rank very highly, as will pieces published in academic or legal journals.

Most trade news outlets retain a high degree of authority, despite that industry's financial decline.

But LinkedIn, as a platform, sits low in this hierarchy because of its social media structure and high volume of self-promotional and AI-generated material — which authority frameworks, ironically, don't like one bit.

Semantic authority. Search engines assess the tone, precision and evidentiary quality of a piece. They like formal patterns of language that connote authority. LinkedIn posts lean toward conversational, promotional or vernacular language.

Citation networks. Authority frameworks rank content that's frequently cited by other authoritative sources very highly.

Think of Marc Andreessen's Software Eats the World essay, published in The Wall Street Journal in 2011, which has been cited and linked to repeatedly for more than a decade.

LinkedIn posts almost never generate this kind of downstream citation.

Content coherence. Engines evaluate whether the piece hangs together factually and analytically. It looks for focus and depth. Shallow or contradictory posts score poorly. Most LinkedIn posts aren't developed with that level of care, focus or thoroughness.

Temporal relevance. Timeliness matters, but only alongside the other factors. LinkedIn can deliver timely commentary, but it's not enough to offset the other weaknesses.

Even though some pre-2023 LinkedIn data was used by OpenAI to train ChatGPT, standard LinkedIn posts don't register highly enough on those five AI authority angles to move the visibility needle.

AI-generated posts unlikely to show up in AI search

If a LinkedIn post is AI-generated, as more than half of longer-form posts on the platform were shown to be in a recent study, the chances of it helping a firm show up in AI results are negligible.

This is why an aggressive stream of LinkedIn posts, however well-meaning, rarely improves individual or company visibility where it really matters: Inside the AI engines that are increasingly shaping commercial discovery.

It's a vexing problem, given that traditional search results differ so dramatically from the answers that AI presents.

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A quick search for any specific business-related term can quickly illustrate just how big the problem is.

For example, a standard Google search for "best non-Big Four accounting firm for quality of earnings work" returned about 300 results spread across 20 pages. That includes accounting firm websites, sponsored ads splashed across every results page and numerous "guide to best accounting firms" articles.

The same prompt given to ChatGPT returned the names of five firms, with a detailed description of why each made that shortlist. The five that did had a digital authority trail.

The 85,000 accounting firms that didn't make ChatGPT's list? They're invisible to the person making the inquiry.

What does this mean for experts?

A new kind of "publish or vanish" dynamic has arrived, paralleling the old "publish or perish" maxim in academia.

The best advice is to pour more focus and effort into work that can actually earn an authoritative, high-provenance publication rather than effecting a "spray and pray" strategy on LinkedIn.

LinkedIn has important uses as a business directory and a tool for recruiting and networking.

But expecting it to be the engine of an AI visibility strategy is like training for the Olympics by walking around the block: It isn't harmful, but it isn't getting you any closer to gold either.

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What are consumers doing with the most advanced artificial intelligence? Talking to chatbots, creating virtual characters and sprucing up photos, to name a few uses, according to a recent ranking of popular apps and websites by the venture capital firm Andreesen Horowitz.

Tweaking a photo or building a virtual friend may seem frivolous, considering the potential for AI to spur scientific and medical breakthroughs, but tracking monthly users and visitors of generative AI apps and websites is key to understanding AI’s rise.

One major takeaway from the report is that people want general assistants. Popular AI chatbots from OpenAI, Google, xAI and Anthropic are among today’s most popular AI tools.

Top 5 Generative AI Web Products

1. ChatGPT
2. Gemini
3. Deepseek
4. Grok
5. Character.ai

Top 5 Generative AI Mobile Apps

1. ChatGPT
2. Gemini
3. AI Gallery
4. Doubao
5. Microsoft Edge

Source: The Top 100 Gen AI Consumer Apps, Andreessen Horowitz

The biggest AI spenders need to make money from consumers to justify a mountain of capital investment. After the launch of OpenAI’s AI chatbot ChatGPT, there was talk of Google falling behind. But Google has swiftly gained ground, with popular AI tools Gemini, Google AI Studio, Google Labs and NotebookLM.

The rankings also show plenty of room for upstarts. Character.ai is among the popular apps for building a virtual companion, highlighting how many people want to create a character for roleplaying. Users can touch up selfies (another popular use) with Hypic and Peachy. Top apps to create and edit art, photos and videos include AI Gallery, Wink, YouCut, PixVerse and BeautyCam.

Then there’s writing assistance, coding assistance, language translation, web search and slideshow creation from tools such as QuillBot, Lovable, Papago, Perplexity and Gamma.

Note that China is gaining ground, with popular tools Quark, Doubao, Kimi and DeepSeek ranking highly. Quark is a general AI assistant owned by Chinese tech giant Alibaba.

Investors will closely watch these trends to see what apps can break through with consumers. And more importantly, which tools can bring in revenue.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Today, the most disruptive start-ups are owned by private equity. Typically, they're small but high-potential firms operating deeply in the red as they chase new applications for big ideas like artificial intelligence, quantum computing or the blockchain.

But a number of established, publicly traded stocks still qualify as top tech disruptors and offer the promise of significant potential as they ride megatrends to new heights.

There is greater risk when it comes to investing in innovation. There is no guarantee a company's specific technology will scale or that it'll be a dominant player even if it does.

At the same time, the following five top tech disruptors have proven themselves through strong share performance and market capitalizations of more than $1 billion.

• Industry: Capital markets
• Market value: $84.3 billion
• 12-month total return: 103.0%

Digital assets are known for their disruptive potential, but Coinbase Global (COIN) is, in many ways, the more responsible older sibling of the rough-and-tumble crypto firms in the sector. One of the largest cryptocurrency exchanges in the world has taken great pains to play by U.S. regulatory rules.

As one of the few regulated exchanges – and as a publicly traded company listed on the Nasdaq and subject to strict financial accounting standards – Coinbase offers transparency that many of its peers can’t match.

This crypto leader is using its bona fides to connect with mainstream financial institutions, including offering Visa (V) branded cards that pay rewards in crypto.

This synergy of disruptive new technology and a cooperative approach with incumbent banking and payment firms has made COIN stock increasingly attractive to investors. The stock has doubled in the last 12 months.

• Industry: Hotels, restaurants and leisure
• Market value: $21.3 billion
• 12-month total return: 12.1%

Gambling is one of the oldest pastimes in the world, so it’s no small feat that DraftKings (DKNG) has managed to reinvent the experience with new forms of gaming. Since a 2018 Supreme Court ruling overturned federal prohibitions on sportsbooks, DKNG has emerged as one of the dominant players in the space.

With the NFL season just kicking off, DraftKings is everywhere, offering both traditional sportsbook betting and innovations like daily fantasy contests.

The company is also expanding into online casino gaming, including video poker, Powerball and even digital “scratcher” lotteries.

DraftKings is at the center of what is shaping up to be one of the biggest multi-year growth trends of the 21st century. Analysts estimate the global sports betting market will grow by more than $220 billion from 2025 to 2029 – a compound annual growth rate (CAGR) of nearly 13%.

As it continues expanding into other gambling verticals, DraftKings is among a handful of top tech disruptors to watch, giving an old-school industry a high-tech twist for the digital age.

• Industry: Biotechnology
• Market value: $1.4 billion
• 12-month total return: 176.0%

Grail (GRAL) is a cutting-edge medical firm developing diagnostics tools aimed at identifying at-risk cancer patients early and through minimally invasive methods. This innovation could be a game-changer on multiple levels: improving outcomes, reducing the total cost of care, and, ultimately, fighting back against deadly cancers around the world.

Following a regulatory battle in Europe, parent company Illumina (ILMN) spun off Grail as a stand-alone biotech firm. That move came at a great time, as its Galleri cancer-screening blood test has gained significant momentum over the past year.

During the second quarter, the product posted greater than 20% year-over-year revenue growth and is expected to grow by as much as 30% for the full year.

The cancer screening niche offers a rare win-win, saving providers substantial costs while saving lives and improving patient outcomes.

Like all development-stage health care stocks and top tech disruptors, Grail carries risk. But its early successes should give investors confidence.

• Industry: Software
• Market value: $403.9 billion
• 12-month total return: 368.9%

You’d have to be living under a rock not to have heard of Palantir Technologies (PLTR). The stock has soared about 370% in the last 12 months, making it one of the top performers in the entire S&P 500 index.

There are good reasons for the buzz around this multibagger stock. Palantir's data analytics and AI platform is forecast to support 30% revenue growth this year and another 30% in fiscal 2026, driven by powerful long-term megatrends.

Unlike smaller AI startups, Palantir benefits from long-standing partnerships with the intelligence community and the Department of Defense, giving it both credibility and stability.

Palantir is already profitable, building real-world AI solutions for paying clients. Those profits are expected to grow significantly, with Wall Street expecting 50% earnings growth this year and 30% next year.

A strong bottom line positions PLTR as more than just another stock riding the AI hype – it's one of the genuine top tech disruptors worth watching.

• Industry: Specialty retail
• Market value: $1.3 billion
• 12-month total return: 1,014.8%

ThredUp (TDUP) is a top tech disruptor in the retail sector, applying a digital approach to thrift shopping. It leverages smart pricing systems and efficient listings to benefit both resellers and buyers.

Unlike platforms such as eBay (EBAY) that rely on sellers to manage everything, ThredUp takes a streamlined approach. Sellers simply send in their items, and ThredUp handles pricing and listing through proprietary algorithms and experience.

On the consumer side, TDUP is capitalizing on sustained demand for high-end fashion paired with a growing preference for more budget-conscious and sustainable shopping.

As the go-to platform for more than 50,000 brands – from Gap to Gucci – shoppers can trust they’re getting verified, quality items, with peace of mind on both ends of the transaction.

The company is not yet profitable, but it's a compelling top tech disruptor because of its 1.5 million active buyers. And TDUP stock has surged more than 1,000% over the trailing 12 months thanks to impressive revenue and margin growth.

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If you're unfamiliar with the jargon, "multibagger stocks" deliver profits at a multiple of your initial investment. Doubling your money is difficult enough. So when a stock delivers "3X" or "5X" profits – that's three times or five times your original investment – it's definitely something to be happy about.

Each of the multibagger stocks on this list is up at least 350% over the trailing 12 months through September 12 vs 19.2% for the S&P 500 during the same period. These aren't microcap start-ups, either: Each of these multibagger stocks boasts a market cap of at least $10 billion, demonstrating their significant scale and investor interest.

There's obviously risk in all of these firms, given their unique business models as well as macroeconomic concerns. But with returns that blow away the competition, these multibagger stocks show that higher risk can indeed deliver higher rewards when investors pick the right names.

• Market value: $196.9 billion
• 12-month total return: 417.0%

AppLovin (APP) is a software-based marketing platform designed to connect advertisers with customers across a host of digital platforms, from streaming video to mobile games.

Its budding business on smart TVs – serving up targeted ads during commercial breaks now inserted into a host of shows people are increasingly enduring to cut down their monthly streaming bills.

Founded in 2012, AppLovin already has significant scale despite the dominance of Google parent Alphabet (GOOGL) in the ad biz. Management forecast $5.5 billion in revenue for the current fiscal year – with 27% growth to more than $7 billion to follow in fiscal 2026.

Advertising can be extremely cyclical, and AppLovin is fighting some big players. But investors like what they’ve seen over the last year in terms of sales and profitability from this upstart operator.

• Market value: $12.2 billion
• 12-month total return: 1,210.0%

Oklo (OKLO) is a 21st-century energy company, with a prime place at the intersection of artificial intelligence and nuclear power.

As AI continues to reshape the economy and various applications grow increasingly complex, electric power needs are growing in kind.

To help support this new demand, nuclear energy has returned to prominence after many decades out of the limelight. It's all about nuclear's relatively green operations compared to traditional fossil fuels.

Oklo is leading the way in this transition thanks to its advanced fission power plants that provide clean, reliable, affordable energy.

OKLO entered public markets in 2024 via a SPAC merger. With big gains over the last 12 months, Wall Street clearly sees something in this disruptive energy stock.

• Market value: $406.7 billion
• 12-month total return: 381.7%

You'd have to be totally new to Wall Street to not know the tremendous growth story of Palantir Technologies (PLTR).

PLTR is the top-performing stock in the entire S&P 500 over the last 12 months thanks to its position at the center of national security and AI megatrends.

Palantir, which provides AI-powered data processing software, made a name for itself through long-term partnerships with the intelligence community and the Department of Defense.

Unlike some other AI start-ups, Palantir is large and comfortably profitable; management just raised its full-year cash flow guidance to as much as $2.0 billion for 2025.

When it comes to the most popular investments of 2025, this multibagger stands apart with daily volume that regularly tops 70 million shares traded.

• Market value: $102.2 billion
• 12-month total return: 421.2%

Robinhood Markets (HOOD) is a fintech company with a well-deserved reputation for disrupting the old way of investing.

Founded in 2013 with a mobile-friendly and low-cost approach to investing, HOOD is the 2.0 version of early discount brokerages such as eTrade that democratized Wall Street for smaller investors.

With crypto offerings, easy access to options strategies and a strong reputation with younger traders, Robinhood continues to grow and challenge traditional leaders in finance too.

Consider its second-quarter year-over-year revenue growth of 45% to nearly $1 billion: This is no niche player but a fast-growing company redefining what’s possible for a new generation of investors.

• Market value: $1.6 trillion
• 12-month total return: 615.0%

Rocket Lab (RKLB) – an aerospace leader developing rocket launch and control systems for commercial spaceflight and defense applications – is also one of the highest fliers of 2025.

The company is not yet profitable, but management expects to operate at nearly break-even next year thanks to a growing backlog and better-than-expected revenue growth in recent quarters.

As with many innovative start-ups out there, volatility is a given, and there's elevated risk here. But there's tremendous buzz around SpaceX and Blue Origin, pet projects of billionaires Elon Musk and Jeff Bezos, respectively. Yet both remain privately held.

RKLB is perhaps the best way to play the next generation of space travel in a publicly traded stock. Indeed, investors have shown tremendous interest in the stock across the last 12 months.

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It usually takes a while for small businesses to adopt new technology. Compared to larger firms, smalls have tighter budgets and fewer employees to roll out new tech to.

But AI is bucking the traditional wait-and-see approach.

Already, 58% of smalls use generative artificial intelligence, according to the 2025 Empowering Small Business Report, a recent survey by the U.S. Chamber of Commerce. That’s up from 40% in 2024, as more businesses harness AI chatbots, AI coding tools and image creation tools.

Most small businesses, defined in the survey as companies with fewer than 250 employees, believe their competitors are using AI or plan to do so soon. There are signs that AI adoption is helping businesses improve sales, keep customers, save money and otherwise enhance their operations.

AI use is sure to jump next year, too, as more AI tools become fully integrated into popular business software for marketing, payroll, accounting, inventory, sales, human resources and communications. Examples include QuickBooks, LinkedIn, Workday and Grammarly. Companies also tap the AI features built into search engines, such as Google and Perplexity, as well as AI tools from Facebook that make advertising on social media easier.

But that’s just the tip of the iceberg. Businesses even report using AI to navigate tariffs, find lower-cost suppliers, process returns, fulfill last-minute delivery, prevent fraud and develop customer insights, according to the survey.

AI trial and error

So what’s stopping some companies from taking the plunge? Top concerns include quality, cost and legal issues of AI tools. That hesitation comes with risk, as other businesses plow ahead and potentially gain an advantage.

Unlike large firms, most small businesses aren’t building custom AI tools from scratch, and instead are using it in traditional software and free options, such as OpenAI’s ChatGPT or Microsoft Office’s Copilot. And it’s not just office workers. Blue collar workers are increasingly using AI features in software designed for plumbers, electricians, painters and other tradespeople.

AI’s fast adoption is spurring small businesses to increasingly look for AI skills when hiring, and help current employees with AI training. “Nearly all (98%) small business AI users are working to upskill their employees,” according to the survey.

Still, it won’t be easy to find the best, most productive uses of AI. Strapped for time and money? Start by harnessing AI in software you have already purchased or try free tools. Don’t be surprised if some efforts fall short.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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The new game-changer is artificial intelligence (AI).

AI is the biggest business breakthrough in the last century. It's not theoretical. It's here, it's real, and it's evolving fast. So, let's lean into it to give us back something precious: time.

After years of advising startups, I can recognize a tipping point when it arrives. Right now, we're at one for time management, and AI is the key.

Kiplinger's Adviser Intel, formerly known as Building Wealth, is a curated network of trusted financial professionals who share expert insights on wealth building and preservation. Contributors, including fiduciary financial planners, wealth managers, CEOs and attorneys, provide actionable advice about retirement planning, estate planning, tax strategies and more. Experts are invited to contribute and do not pay to be included, so you can trust their advice is honest and valuable.

Whether you're a founder buried in pitch decks, a product manager juggling road maps or a solo operator aiming to outperform, AI can lighten your load, sharpen your focus and let you channel your energy where it truly counts.

If AI could put time in a bottle …

Miles Davis once said, "Time isn't the main thing. It's the only thing." Time is your most limited resource. You can't create more of it or recruit it, but you can manage it better. And that's where AI comes in.

The trick isn't just using AI. It's understanding how it can amplify your efforts. Automate the mundane. Speed up research. Draft faster. Dive deeper into analysis.

Don't chase every shiny tool. Identify your bottlenecks and delegate them to AI. Real productivity is about achieving more by doing less of the unimportant stuff. This isn't about taking the easy road; it's about working smarter on a scale we've never seen before.

How AI made my life (and business) better

I'll be honest: Not long ago, I felt overwhelmed. As an entrepreneur, I lost control of my time the moment I launched my company. You think you'll be your own boss? Wrong. You trade one boss for many: clients, customers, vendors — you name it.

I became a slave to my calendar. Every Sunday night, I planned my week. Every morning, I tackled the day's emergencies. In between? Meeting. Call. Meeting. Call. Repeat.

That endless cycle left no room for the work that truly matters: reflection, vision, strategy, leadership. If I'm not doing those, who is? If I'm the CEO but also the dishwasher and the stamp-licker, where's the leadership? Where's the intentionality? Where's the time to build strategic partnerships or lead my team with clarity and purpose?

That's when "buying back my time" became vital, and where implementing AI made a difference.

It's a productivity powerhouse

Pop culture often reduces AI to a chatbot writing your kid's book report. However, let's elevate the conversation: AI is a powerful tool for productivity. It's how I escaped email ping-pong to schedule a 30-minute call. Ten emails to find a time? Not anymore.

AI manages my calendar with more efficiency and intelligence than most humans. That's not replacing someone's job — it's reallocating energy to higher-value work. My admin's time is better spent elsewhere, and so is mine.

Which tasks are made for AI, and which aren't

Here's the real secret: AI doesn't just take things off your plate; it lets you focus on the things only you can do. That's the litmus test I use now. If a task requires my voice, my experience, my leadership, then it's mine. If not? Automate it. Delegate it. Let it go.

We get bogged down in the weeds. We're chasing invoices, answering customer emails, fixing website issues and attending meetings that could have been handled via email.

Meanwhile, the big-picture work — the vision, the strategy, the partnerships that move the needle — waits. And waits. And sometimes never gets done.

If you don't reprioritize and refocus, you end up spending too much time in the business, and not nearly enough time on it. I see it all the time with the founders I advise how to make the shift, but I had to learn this the hard way.

The data doesn't lie. Most business owners spend only about 32% of their time working on the business, but when asked where they want to spend their time, they often say they want to spend more time working on the business.

Nearly three-quarters say strategic thinking, growth planning and leadership are what really matter. And they're right. That's where the magic happens. That's where culture is built. That's where value is created.

Don't leave money on the table

As entrepreneurs, we often miss opportunities when we fail to follow up. I've left money on the table because I never followed up after receiving an out-of-office reply.

AI can nudge me to reconnect, remind me when a contact changes jobs, and help me maintain relationships with personalized touchpoints. That's the kind of quiet, invisible value that compounds over time.

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But let's not fool ourselves: Not everything can or should be automated. The gut-check moments still matter. Human context and connections still matter.

Whether it's reviewing a sensitive post before it hits social media or rewriting a note that needs genuine empathy, we can't outsource the essence of who we are. That's our edge.

Time isn't something you spend; it's something you invest. That shift in mindset changes everything.

Invite AI to your next meeting

If you're trying to figure out where AI fits into all this, here's what I tell my team and clients: Start small and start smart. Use it where it makes a difference.

For us, it's not about shortening meetings; it's about making them more effective. People still talk too much. We're human.

But AI is invaluable after the meeting. It captures action items, summarizes key takeaways and flags deadlines I might have casually mentioned but otherwise forgotten.

That's where it buys me back time, not in the moment, but in the follow-through. And when I follow through, that builds trust.

The cost of not investing in your time? It's soul-sucking. You end up on the hamster wheel, busy but unproductive, constantly reactive and never quite getting to the work that moves your business forward. You disappoint yourself, your team and your clients. And eventually, it wears you down.

I measure my success differently now. I know I'm doing it right if I'm well-rested, I follow through, I'm not avoiding my calendar and I can sit down to dinner with my family instead of yelling, "Be right there!" from the other room. That's not just balance. That's integrity.

Want to shave 10 or 15 hours off your workweek?

So, if you're feeling overwhelmed, here's your starting point: Adopt one small AI tool — for meetings, for content drafting, for email management. Use it to free up time for your highest-value work — strategy, relationships and creative thinking.

Don't waste time figuring out if a meeting should be at 2 or 3. Focus on what that meeting is for. That's where the real ROI lives.

Here's the truth: Embracing AI isn't just about learning some shiny new tool. It's about rethinking how we value our time. As entrepreneurs, our calendar is our capital.

When we start delegating routine emails, scheduling, basic research and even first drafts, we unlock hours we didn't think we had.

I'm not talking theory here; I'm seeing it play out every week, five, 10, sometimes 15 hours handed back to people simply by being smart about where AI fits in.

But this only works if we're intentional. It's not about automating everything. It's about choosing what stays human and what doesn't need to be. That gives us back the space to lead, think, build and nurture the relationships that drive growth.

Three AI tools to consider

I asked ChatGPT what the best AI tools are for founders who want their time back. No fluff, no guru advice, just real tools that help with the chaos. Categorized by what they do, I picked three:

• Motion. Automatically plans your day by prioritizing tasks, meetings and deadlines.
• Notion AI. Combines tasks, docs and projects in one smart workspace.
• Zapier. Automates workflows between apps like Gmail, Slack and Airtable.

But you find your own.

The future isn't about grinding harder. It's about being sharper, more focused, more present. And AI? It's not the whole answer, but it's an incredible lever when used wisely.

Start small. Start smart. And start now.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

AI security tools can bolster defenses against phishing, deepfakes and other cyberattacks. But there’s a problem that’s getting worse: AI is making companies and individuals more vulnerable to new digital attacks.

“AI models are now being used to perform sophisticated cyberattacks, not just advise on how to carry them out,” says a recent threat report by leading AI company Anthropic. AI chatbots, such as Anthropic’s Claude, can help cybercriminals profile victims, analyze stolen data, steal credit card information and more. One case study showed an attacker targeting at least 17 organizations in health care, emergency services, government and religious institutions for ransomware attacks.

The AI tool helped automate the attacks, from reconnaissance to extortion demands. Anthropic banned the accounts when they were discovered and is now trying to preemptively detect such criminal activity. But that’s not much solace. “We expect attacks like this to become more common,” the report notes.

Meanwhile, the way a lot of businesses are using AI is increasing the risk. The rapid adoption of AI by businesses raises issues, since AI tools are often put in place with weak security settings, leaving the systems vulnerable to a breach. There’s also “shadow AI,” the tools used by workers that aren’t sanctioned by the company, which creates a hidden security risk. Many firms don’t have adequate policies to stop the practice.

The cost of a data breach has surged to more than $10 million in the U.S., on average, according to IBM’s recent Cost of a Data Breach Report 2025. The cat-and-mouse game is escalating. “While businesses scramble to adopt AI for competitive advantage, cybercriminals are just as rapidly incorporating these technologies into their attack arsenals,” writes Limor Kessem, cyber crisis global lead at IBM.

“Security incidents involving shadow AI accounted for 20% of breaches,” according to the report. Shoddy AI company policies, such as ignoring unsanctioned AI tools being used on company networks, significantly raise the cost of a data breach. Note that regulatory fines in the U.S. for data breaches are higher than in other countries, driving up the cost.

On the bright side, investing in AI for security led organizations to detect breaches much faster and save money, according to IBM. New policies can help mitigate the risk, such as oversight of shadow AI, having a solid data breach response plan and regular security training for workers.

A big focus should be on preventing phishing attacks, one of the top causes of data breaches. The attacks happen when fraudulent emails or other messages are used to trick someone into clicking on a malicious link or downloading a malicious file.

Businesses should also regularly take an inventory of all the software in use and ditch underused tools, which are susceptible to attacks. Other factors that help include encrypting data and using advanced threat monitoring tools.

But even detection tools are under threat. Cybercriminals’ use of AI tools “can adapt to defensive measures, like malware detection systems, in real time,” notes Anthropic.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Investors can’t get enough of AI start-ups. A record $70 billion was doled out to generative AI companies by venture capital firms and other investors in the first half of 2025, according to a recent report by S&P Global Market Intelligence. The total was driven by two megadeals: OpenAI’s $40 billion funding round and Meta’s $14.8 billion minority stake in Scale AI.

The eye-popping total highlights the heated competition among leading AI firms and the big expectations investors have for future paydays.

The U.S. is by far the global leader, with nearly $40 billion invested over 728 deals in the second quarter, making up 84% of the global dollars, according to market research firm CB Insights. The median deal size is $4.6 million, a four-year high.

Much of the money is used for buying Nvidia-based computing power. Large players such as OpenAI, xAI and Europe’s Mistral AI are increasingly looking to build or expand their own data centers so they don’t have to rely on cloud computing from Amazon, Microsoft or other cloud vendors.

Look for more small players to get scooped up by leading tech giants and other large companies. Banks, consulting firms and other businesses want AI tech, too, and a quick way to get it is to buy a promising start-up.

AI is clearly flying high, so what could go wrong? “Competition in the space is expensive, and although revenue is increasing rapidly, losses are also mounting, requiring more investor funding,” notes S&P Global Market Intelligence’s report. Plus, investor skepticism is starting to emerge. “At the start of the third quarter in July, xAI secured $10 billion through debt and equity, but the company had to pay a steep interest rate on the debt.”

Expect plenty of start-ups to fail to gain traction and some to eventually go under. The hot market is also crowding out investment in anything that’s not AI-related, potentially spurring a glut of AI start-ups while disregarding other promising tech.

Still, some of the start-ups are already gaining serious traction. Others are sure to soar in the years ahead. The top tech deals in the second quarter were by Scale, xAI, Anduril, Thinking Machines Lab and Anysphere, according to CB Insights.

Anthropic, a leading AI company, is in talks to raise another $10 billion in funding, according to recent reports. Other firms scoring funding this year: Seekr Technologies, Snorkel AI, TensorWave, Decagon, Chainguard, Glean, Harvey, Cyera, Abridge, Ramp and Cyberhaven. The U.S. has an astounding 206 private AI firms valued at more than $1 billion, says CB Insights.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Amid the hype over AI, a practical question: When will the technology boost the economy the way its developers and promoters are promising? Is artificial intelligence going to unleash a surge in worker productivity, as epochal new tech has done in the past? Or is investor enthusiasm for it overdone?

In one sense, AI is already adding to GDP. Spending on AI hardware is astronomical, both for the costly, specialized chips that power AI and the related infrastructure to deliver the electricity that those chips devour. This spending raised GDP by 0.3% in the second quarter of this year. Even that doesn’t fully capture the size of this investment surge, since some capital outlays that tech firms are making don’t show up in the official GDP accounting method. Just look at the top five firms by AI investment: Amazon, Alphabet, Meta, Microsoft and Oracle. The increase in their AI-related capital expenditures over the past two years equals about 10% of GDP gains in the U.S. over that time period. Add the power plants, transmission lines and other infrastructure they need to run their data centers, and the outlay is even bigger.

There are also signs that businesses are gearing up for AI to make an impact on their operations. Company mentions of AI use for research tripled since Nov. 2022, when ChatGPT launched and turbocharged generative AI. 25% of job listings posted for IT professionals since the start of last year have asked for AI-related skills. The number of mobile AI app downloads hit 60 million this March. Internet searches related to AI have grown tenfold since OpenAI unveiled ChatGPT to the public. When it comes to whether AI will make workers more productive, the picture gets murkier. There are some early signs that it’s happening. Inflation-adjusted revenue per worker among S&P 500 companies has been rising since late 2022, following a 15-year period when it stayed flat.

It’s not clear why, but the overlap with advanced AI applications going mainstream is hard to ignore. But with so much money pouring into AI, there are reasons for skepticism. Much of the investment being made today could end up wasted. Many companies that are in vogue now figure to fail. It’s possible that AI computing power being rushed online could ultimately prove to be unneeded, akin to how fiber-optic cable networks got overbuilt in the 1990s. That capacity eventually got used as data consumption rose, but not before builders who spent too much on it went bankrupt. If the current AI data center boom fizzles, the pullback in spending could spark a mild recession, as the tech bust in 2001 did. Most major technological leaps take time to filter through the economy. AI does seem genuinely transformative. But the transformation may take many years.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Despite being digital natives, members of Gen Z who are entering the workforce aren't putting their complete faith in financial influencers or generative AI tools for financial advice. Instead, they are primarily placing their trust in financial advisers.

According to new research from CFA Institute, conducted to glean insights about recent graduates' outlook on their careers and wealth building, 91% of U.S. graduates report they trust human advisers the most.

The Kiplinger Building Wealth program handpicks financial advisers and business owners from around the world to share retirement, estate planning and tax strategies to preserve and grow your wealth. These experts, who never pay for inclusion on the site, include professional wealth managers, fiduciary financial planners, CPAs and lawyers. Most of them have certifications including CFP®, ChFC®, IAR, AIF®, CDFA® and more, and their stellar records can be checked through the SEC or FINRA.

That's nearly double the trust placed in online influencers (53%) and significantly more than those who say they trust AI tools like ChatGPT (49%).

To me, that says everything about where our industry needs to focus to support the needs of the next generation. We need people and technology.

The human element

Over the course of my career in wealth management, I have always believed that trust remains the foundation of good advice and productive adviser/client relationships. That belief has never been more validated. People and relationships build trust. Technology can augment it, but does not supplant it.

This trust-centric mindset is also reflected in Gen Z's motivations for building wealth, which are grounded in stability and long-term well-being rather than short-term trends or quick wins.

When asked their motivation, Gen Z graduates responded that they prioritize security over everything: 63% said their top driver is financial security, and 60% said it's the ability to meet day-to-day needs without worry.

I'm not surprised by these findings. They are practical, realistic concerns, not meme-stock fantasies, bitcoin bubbles or overnight riches, as the headlines may lead you to believe. Today's graduates largely aren't chasing hype.

They're looking for solid financial partnerships to grow their wealth for the long term.

This ethos is reflected in how they want to engage with wealth managers. Nearly half (45%) say they are most likely to work with someone they trust and who puts their interests first. They value relationships, collaboration and personalization.

That's both a challenge and an opportunity for our industry. Trust must be earned, not marketed. We must meet this generation where they are, with transparency, ethics, expertise and a deep understanding of their goals.

The best wealth managers establish relationships with their clients early and understand the underlying values and principles behind their desire to build wealth. They go beyond the dollars and cents, digging into the "why" behind the financial plan.

We must remain true to these fundamentals of fiduciary, client-centered advice, even as the world of finance continues to evolve at an increasingly rapid pace.

While a knee-jerk reaction may be to adopt each new tech innovation, or market every new tool, our superpower is keeping our human perspective and deep-expertise front and center.

Planning, not prediction

Another clear takeaway from our survey: Planning matters. Two-thirds (67%) of graduates said a solid financial plan is key to achieving their goals 10 years from now. Another 59% emphasized the importance of understanding financial markets and strategies.

This reinforces what many advisers already know. The best investment strategy is one that is rooted in the long term and tailored to the individual — not reactive, not totally algorithmic and certainly not influenced by the social media flavor of the month.

Looking for expert tips to grow and preserve your wealth? Sign up for Building Wealth, our free, twice-weekly newsletter.

We recently spoke with Yen Truong, a recent graduate of the Master of Science in Finance program at California State University, Sacramento, and current financial planning specialist at CAPTRUST, to glean additional insight into the advising landscape.

Yen underscored the importance of perspective as it relates to a career in finance. "A good adviser provides more than just financial strategies," she told us. "They build trust with their clients, educate them, and offer perspective during emotional and volatile times."

As our industry evolves and geopolitical strife continues to dominate headlines, reinforcing this value proposition becomes even more important. Financial advice is not just a transaction. It's a relationship. And it is built on integrity, empathy and professional excellence.

AI supports, not replaces

Of course, technology remains an essential and exciting part of the equation. Artificial intelligence has the potential to enhance, but not replace, the human adviser. Used responsibly, it can free up time, improve accuracy and unlock better client insights.

AI integration can also help to provide the type of personalized solutions that the next generation is looking for from their wealth manager, creating a unique experience that meets their specific needs. One-size-fits-all certainly does not apply as it relates to the wealth management relationship of the future.

Yen described AI as "a powerful tool for improving productivity in research analysis and investment operations," but emphasized that it has not, and cannot, replace the core of what advisers do.

This is the future I see: smart, empathetic investment professionals who are fluent in both financial markets and emerging technology. I believe the most successful people in finance will combine human intelligence with artificial intelligence — enhancing judgment, not outsourcing it.

As organizations, we can support our staff to upskill and leverage AI to ultimately benefit their clients. Our data shows that graduates recognize the importance of having AI skills and seek out employers who are willing to support them in their journey to leverage it.

To remain relevant, trusted partners, doubling down on what Gen Z is asking for gets us there: Human connection, personalized advice and a clear roadmap to financial security.

This generation is not looking to cut corners. They're looking to do it right. Our job as financial professionals is to meet them there. I believe this mindset doesn't just serve Gen Z investors, it elevates the standard for how we serve all clients.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

Whether you're nearing retirement and juggling rental properties in multiple states or just starting a family and trying to figure out the best way to invest for your family's future, if you have complex financial needs, you could consider a wealth-management tool to help you make the most of your money.

Range aims to be your go-to, "all-in-one" platform to figure it out. It’s designed for users who want to view their finances holistically and create a plan that considers long-term goals, estate planning and tax implications without working with multiple separate providers.

The platform combines features often found in budgeting apps, tax preparation software and traditional advisory services into a single system.

We take a look under the hood to see how the tool works and if it differs from conventional wealth-management software.

What is Range?

Range Finance has built an online wealth-management platform that's designed to be your one-stop shop for all your financial planning needs.

That includes such services as investment management, tax planning, retirement planning and insurance optimization, as well as cash flow services such as budgeting and financial goal tracking.

You can create a comprehensive plan that aligns everything from your day-to-day spending through to your long-term retirement goals to your tax strategy all in one platform.

That's done with the help of a team of experts, each specializing in a specific area of expertise. You get the benefit of having a financial adviser, accountant, tax pro and other experts on hand without having to independently hire each one yourself. You also don't need to move any assets around or worry about account minimums.

Instead of moving your money over to Range Finance, you can link your existing accounts to the platform, allowing that team of experts to review your financial situation in depth and provide you with a step-by-step plan to reach your goals.

If you want them to get more hands-on, such as full-service investment management, you've got that option, but it's not a requirement to get started.

There are three tiers of service available: Premium; Platinum; and Titanium. Here's a breakdown of each one:

• Premium costs $1,475 semi-annually. It includes unlimited access to fiduciary advisers, a suite of self-service tools, custom investment and retirement planning, as well as budgeting and goal tracking. You'll also be able to include your partner's finances at no extra cost.
• Platinum costs $2,975 semi-annually and includes everything in Premium plus more. The extras that come with this tier include tax filing in up to three states, tax planning and projections, equity-compensation planning, alternative investment planning and other services that are ideal for more complex financial situations.
• Titanium costs $4,975 semi-annually, giving you everything in the Platinum and Premium tiers plus the ability to manage more complicated finances. That includes tax filing in more than three states or international taxes, bookkeeping reviews and more.

The benefits of Range

If you're thinking Range Finance doesn't sound that different from another wealth-management platform, here are key benefits that you'll see when you try it out:

• Get comprehensive planning for multiple assets and complicated financial situations. The Range Finance platform is staffed by experts specializing in all aspects of wealth management. Whether you've got a growing real estate portfolio or you're trying to figure out the best way to maximize your equity compensation package (or both), you can manage all of it on the Range platform.
• Continuous and coordinated optimization of your financial plan. Instead of an annual CPA review, Range provides year-round monitoring to spot opportunities as they arise. Because it's all happening in one place, it's easier to update your tax strategy in real time based on any investment moves or other changes in your financial situation. Investment recommendations will automatically factor in tax consequences, for example.
• Blend human expertise with AI efficiency. Range combines human expertise with AI technology, using financial professionals to review your finances and AI tools to streamline parts of the process. This approach allows clients to participate in planning while benefiting from both the speed of automation and the experience of professionals in areas such as financial planning, tax strategy, and equity compensation.
• A flat fee structure. The subscription for any tier of service is a flat fee, so you know exactly what you're paying, and you won't have to pay more as your wealth grows. The same goes for Range's investment management services.
• No account minimums and no need to transfer your assets to Range. Link your accounts to the platform, but leave your assets where they are.

What to consider before trying Range

While there are plenty of benefits to take advantage of at every tier of service, there are some important points to consider before signing up for the Range Wealth Management Platform:

• You must link your financial accounts to the platform. You don't have to link every account you own, but the more you do, the more comprehensive your financial plan and other recommendations will be. With that said, you can unlink accounts at any time, and there's no need to actually transfer any assets to Range.
• If your tax situation is complicated, you might need to upgrade to a higher tier of service to get the support you need.

Is Range the right fit for you?

Range combines AI-powered tools with a team of human experts to offer investment, tax, retirement and budgeting services in one platform. Its flat-fee pricing and no-asset-transfer approach might appeal to those who want a centralized view of their finances without committing to a traditional wealth-management arrangement.

It could be a good fit for people who have multiple assets or complex financial needs, such as multistate taxes, equity compensation, or real estate holdings and want coordinated planning in one place. However, those with simple finances or who prefer to work exclusively with an in-person adviser might not find the added services worth the cost.

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But for job seekers and investors, the real story — and the real opportunities — lie in the secondary effects reshaping industries, talent markets and investment flows.

Here are five under-the-radar shifts that will define where growth and careers move next:

1. Regional accountants will reap rewards

Regional CPA and advisory firms will likely become the biggest beneficiaries.

The Kiplinger Building Wealth program handpicks financial advisers and business owners from around the world to share retirement, estate planning and tax strategies to preserve and grow your wealth. These experts, who never pay for inclusion on the site, include professional wealth managers, fiduciary financial planners, CPAs and lawyers. Most of them have certifications including CFP®, ChFC®, IAR, AIF®, CDFA® and more, and their stellar records can be checked through the SEC or FINRA.

Revised SALT deduction caps, new family business credits and stricter compliance reporting are overwhelming small-business owners and high-net-worth families, and they're turning to trusted, local accountants for guidance.

Investor takeaway: Smaller, business-focused accounting firms are positioned for rapid growth and could become attractive acquisition targets for larger firms and private equity.

Job seeker takeaway: CPAs with expertise in small-business and family tax planning are in short supply, with more than 300,000 accountants and auditors leaving their jobs over a two-year period starting in 2020, according to the Wall Street Journal. Demand is driving up salaries, signing bonuses and career mobility.

2. Homeland Security spending: The unexpected AI jobs engine

Massive Homeland Security funding, much of it for surveillance, drone tech, next-generation initiatives and predictive analytics, is fueling a surge in AI and defense technology. History suggests that much of this government-funded innovation will eventually carry over into the private sector.

Investor takeaway: Early-stage AI and defense tech firms with strong analytics and automation capabilities may be particularly well-suited to capitalize on this funding cycle.

Job seeker takeaway: AI engineers, data scientists and cybersecurity specialists are entering a hiring boom. Even midcareer software developers should consider defense-tech opportunities as demand accelerates.

3. Clean-tech layoffs will reshape the STEM talent market

Cuts to clean-energy subsidies are prompting layoffs in solar, EV and battery manufacturing.

But displaced engineers and scientists won't stay idle for long. Aerospace, defense, financial services and health care are already absorbing this talent, at more competitive salaries than Silicon Valley typically commands.

Investor takeaway: Midmarket defense and tech firms with robust hiring pipelines can boost innovation while improving margins. The talent shift also reflects a growing worker preference for stability over sky-high compensation.

Job seeker takeaway: Clean-tech engineers should pivot quickly. Industries like aerospace, financial services and health care are actively recruiting STEM talent for applications ranging from risk modeling to telehealth innovation.

4. Small businesses face a compliance crunch, and outsourcing will win

New work requirements for benefits eligibility and fresh tax deductions on tips and overtime are creating a compliance headache for small and midsized businesses.

Payroll software upgrades and outsourced HR services are becoming a necessity, not a luxury.

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Investor takeaway: HR tech providers and managed service firms with scalable compliance solutions are well-positioned for growth.

Job seeker takeaway: Payroll specialists and HR compliance professionals are in high demand as managed services providers expand aggressively.

5. Managed services and outsourcing, not tax cuts, will be the private equity gold rush

While tax cuts grab headlines, managed services and the need for business process outsourcing will emerge as a more significant growth play.

Budget-conscious public agencies and private companies will shift from a traditional staffing model to outsourced IT, accounting and back-office services.

Investor takeaway: Managed services and business process outsourcing offerings with recurring revenue models and a focus on IT and accounting are likely to attract investor interest as consolidation accelerates.

Job seeker takeaway: IT support, accounting and finance operations roles are expanding rapidly in managed services. The ability to manage global teams will become more of a requirement than a preference.

Professionals working across the managed services industry are seeing accelerated promotion tracks as they race to scale with demand.

The bottom line

The One Big Beautiful Bill is creating new winners, not just in obvious tax-cut beneficiaries but in regional accountants, AI startups and managed services firms.

For investors, that means looking beyond the headlines.

For job seekers, it means moving fast to enter high-growth sectors before the competition follows.

The tax law's most profound impact may be on organizational speed. Federal funding shifts will reward companies that can redeploy talent, adjust strategy and adopt new technologies quickly. Many won't keep up.

Rigid organizations, slowed by siloed decision-making and outdated hiring models, will miss contract opportunities and lose market share.

Agile firms will thrive by reallocating resources within weeks, adjusting strategy based on live data and closing skill gaps faster than competitors.

The next era will favor the quick, not the comfortable. Organizations that adapt fastest, and professionals who align with them, will define the next decade of growth.

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• Money for Your Kids? Three Ways Trump's 'Big Beautiful Bill' Impacts Your Child's Finances
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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

AI has huge potential for businesses. But companies aren’t tracking an emerging risk, and it’s one that can be mitigated.

The tech could harm company culture by lowering employee satisfaction, eroding needed skills, or even seeding resentment. In addition to tracking AI’s return on investment, cost savings and productivity gains, firms need to track how AI affects worker behavior.

“This is a very popular topic that we’re taking a lot of calls and queries about,” said Neil Osmond, an analyst at Gartner, a tech market research firm, in a recent presentation. AI is creating a new human-machine relationship that is unlike the adoption of past work technologies, such as PCs or the internet.

As AI chatbots become more humanlike, the tools will trigger human responses, from happiness to anger, as a real colleague would. The emotional response goes beyond fears of job loss to worries about losing parts of a job a worker loves. Rather than ROI, managers should keep tabs on how AI tools are helping employees feel more productive and engaged, said Osmond.

Work closely with affected employees and have them develop AI’s role and how the job will change. Don’t just provide Google’s Gemini, Microsoft Copilot or other AI tools to workers and hope for the best. Ask how AI is changing work and what workers like and don’t like about the shift.

As Osmond put it, “If AI is doing a portion of your job, and AI is better at it than you were, then what’s your new job?” said Osmond. Keep in mind that AI is not just about automating or augmenting. The new tools may do work that a company has never done. Reward workers for finding new moneymaking uses.

Using AI and losing skills

It’s important to keep tabs on human skills as AI handles more day-to-day tasks. For example, 75% of frontline cybersecurity teams will experience an erosion in skills by 2030 because of a dependency on AI, predicts Gartner. There are already worries that cybersecurity professionals will face an irreversible skills shortage due to generative AI taking over more tasks, noted Jeremy D'Hoinne, an analyst at Gartner, at a conference this summer.

Companies and managers must identify and cultivate must-have skills that can’t be lost with AI use, as skill erosion rears its head over the next few years. AI will sift through emails, summarize meetings or documents, create slideshows, draft legal briefs, write software, do economic analysis and perform other tasks. New and experienced workers may get rusty and institutional know-how may be lost. British law firm Clifford Chance, which is pushing AI adoption for its lawyers, is also tracking what skills atrophy, how it occurs and how to plan for it. More companies will do the same.

Consider how AI changes performance evaluations and career trajectories. For example, AI tools can make a new employee as productive as an experienced one, such as a new call center worker performing well with real-time AI responses. Or a new salesperson with an AI assistant that can answer and send emails and calls. Are all employees getting equal access to AI tools? When some get access and some don’t, that can create jealousy.

Humans make AI systems better

Focus on providing new AI skills to workers in short educational videos, brief email messages, infographics or social media-style content. For example, highlight a six-minute video that shows how to use AI to improve writing, a two-minute clip on doing research or a brief report on creating a slideshow. Share specific suggestions of a “prompt,” the specific language an employee should use to get the most out of an AI chatbot.

Avoid a vague push to use AI more. Instead, provide a steady stream of examples, especially ones that workers come across. Note that workers’ AI abilities vary widely. Time savings is one likely outcome. The time could be used for new tasks or learning. To keep employees satisfied, let them play a big part in the decision of how to use freed-up time.

Human knowledge remains critical and is key to continually making the AI systems better. For example, in cybersecurity, there needs to be human judgment to weed out security alerts that are false positives and improve the automated AI tools. Job postings may need updates to emphasize non-AI skills, especially for entry-level gigs. New college graduates will clearly have more experience with AI, but overreliance on it is a looming risk.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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The Kiplinger Letter has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Plenty of people aren't just experimenting with artificial intelligence — they're starting to rely on it. In a 2024 Experian survey, nearly half (47%) said they've turned to an AI chatbot for financial advice.

What they might not realize is that AI often gets it wrong: 35% of the time in a recent study. Researchers at Investing in the Web asked ChatGPT 100 personal finance questions, and more than a third were either partially incorrect or flat-out wrong.

The Kiplinger Building Wealth program handpicks financial advisers and business owners from around the world to share retirement, estate planning and tax strategies to preserve and grow your wealth. These experts, who never pay for inclusion on the site, include professional wealth managers, fiduciary financial planners, CPAs and lawyers. Most of them have certifications including CFP®, ChFC®, IAR, AIF®, CDFA® and more, and their stellar records can be checked through the SEC or FINRA.

AI tools are powerful and impressive and fun to use. But when it comes to more complex and nuanced tasks, they start to fall short.

I've personally spent hours testing ChatGPT with my own household budget. I caught and corrected several mistakes, only to find those same errors showing up again later in the process.

There's no question that artificial intelligence is here to stay. Even in its early days, it's reshaping nearly every industry, including finance.

As someone who's spent decades helping people find truly trustworthy, qualified financial advisers, I want to help demystify how AI is being used in finance, where it's helpful, and why human judgment still matters most.

Where AI is showing up in finance

Right now, AI is great at one thing: processing vast amounts of data, fast. It can recognize patterns, summarize conversations and even flag potential risks based on your investment profile or spending behavior.

Many financial advisers are already using AI to handle the time-consuming administrative tasks, such as compiling reports, analyzing data, summarizing client meeting notes or automating parts of the onboarding process.

But AI can help advisers even more by monitoring changing tax rules or modeling portfolio outcomes in different market scenarios.

All this means better preparation and more time for human conversations. It frees advisers to do what they do best: listen, interpret and guide people through life's financial decisions with empathy and good judgment.

How will AI affect real financial advice?

I use AI all the time to gather information. But I've learned to double-check every result.

For example, when I asked it for a current report on home sales in my neighborhood (information that's part of the public record), it missed a handful of transactions that happened more than a year ago. That meant the value of my property was not in the correct range.

When it generates recommendations, it often loses the logic that led to those conclusions. It doesn't circle back to catch its own mistakes. That's on the user.

The best financial advisers I know treat AI the same way. They don't wholly rely on it. They cross-check. They use it as a time-saver, not as a replacement for real financial planning.

If an adviser is leaning entirely on AI to drive decisions or build plans, that's a red flag. Financial planning isn't just about plugging numbers into software.

It's about understanding values, preferences, fears and trade-offs — all the things you don't find in a spreadsheet.

Couldn't AI make advice cheaper?

In some ways, it already has. By improving efficiency and automating repetitive tasks, AI helps financial advisers serve more clients faster. That can lead to more flexible or competitive pricing, which is a good thing.

But let's not forget what people are actually paying for.

It's not just spreadsheets and software. You're paying for the ability to call someone when you're scared about the markets, or when you're trying to decide whether to pay off your mortgage or fund your kid's wedding.

Personalized advice built around such things as your goals, taxes and estate plan is still where the true value lies.

What about robo-advisers?

Despite the name, most robo-advisers don't actually use AI. They follow simple rules and algorithms, such as automatic rebalancing or low-cost ETF allocation.

Some are layering in basic AI tools for tax-loss harvesting or personalization, but these are still at a surface level. They're not building a full picture of your financial life.

Robo-advisers can be a solid option for people with simple needs. But don't confuse automation with advice.

Will AI take the place of financial advisers?

Here's the thing: AI can't tell when you're quietly panicking about retirement. It can't pick up on the tension between you and your partner about money. It doesn't know that your mother-in-law might need memory care you can't afford.

A financial adviser will.

Let me tell you about a client who wanted to buy a thoroughbred horse. It wasn't a great financial decision on paper, but it mattered deeply to her.

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She had a hand injury and knew she wouldn't be able to ride forever. Her adviser didn't just say "no." She helped this client work toward that goal over time, adjusting the plan so the horse purchase didn't jeopardize her retirement.

AI would have flagged buying the horse as a bad idea and moved on. A highly qualified human adviser understood the emotional weight of the decision and made room for it.

Today, that client is showing her horse, winning ribbons and living out a dream that money alone can't measure. (You can read more about this remarkable client-adviser relationship in my article How Her Financial Adviser Changed Her Life.)

That's not a machine-made plan. That's a human-made life.

Can you trust AI-generated advice?

This is a good question that I encourage everyone to ask. If you're working with an adviser or platform, ask how they're using AI. Are recommendations reviewed by a human? Is the data source reliable? Is there transparency?

In my own vetting process at Wealthramp, where I connect people with independent, fee-only fiduciary advisers, I've started asking these same questions. I want to know how — and how much — advisers are leaning on AI, because clients deserve to know what's going on behind the scenes.

Good advisers will explain exactly how they use AI to support their expertise.

It's a powerful tool, but AI is not your adviser

AI is changing financial advice, but it's not replacing it. It's making the best advisers even better by helping them work faster, stay organized and focus more deeply on their clients.

No matter how smart the technology gets, advice that truly fits your life will always require human insight. It takes time, trust and personal judgment to make the kind of financial decisions that stick.

By all means, use AI to learn. Use it to explore your options. But when it's time to make the big decisions, the kind that shape your future, make sure there's still a human in the room with you.

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

But I know many people tend to agree to privacy policies without so much as skimming them to understand how a website or app is using their data.

I had a theory: If the choice is between not reading the terms you're agreeing to at all or taking a few minutes to get an AI-generated recap of the key points, this might be a scenario in which AI can actually help protect your privacy a little better than you would otherwise.

To test my theory, I asked four AI chatbots to summarize various privacy policies, including their own. The results were surprisingly useful, though there are a few tricks needed to get all the key information you need.

After some trial and error, here are the steps I used to quickly make sense of tediously long privacy policies.

1. Ask AI to summarize the privacy policy page

For this test, I used ChatGPT, Gemini, Copilot and Perplexity. In all cases, I was able to simply paste the URL of the privacy policy and say "summarize this" to get the AI to generate a recap.

The initial summary is fairly vague, but it provides enough to give you a quick overview of the policy.

For example, Gemini's summary of Google's privacy policy was a very short, bullet-point recap of Google's lengthy policy. There's definitely a lot missing, but it was enough to give me a sense of the kind of data Google is collecting about me, what it's using it for, and what kind of third parties with whom it might be sharing my data.

Overall, the summaries were a good starting point to spot any possible red flags that I might be concerned about, so I know which sections of the policy I might want to read in full.

2. Ask follow-up questions based on your concerns

All the summaries I got were pretty short, which, to be fair, is the point of a summary.

But to really understand what you're agreeing to in a privacy policy, it helps to ask the AI a few follow-up questions on certain key points.

Here are questions I recommend asking:

1. What data does the company collect about users? Look for types of data that don't seem necessary for the service. A delivery app needs your address, for example, but it probably doesn't need access to your contact list.
2. What data does the company collect from my device? This might include things such as what device you're using, your IP address or your physical location. Again, look for things that don't seem necessary for the service.
3. How does the company use the data it collects about users? If you see mentions of personalized, targeted or interest-based advertising, the company is likely sharing your data with other companies. Even if you're comfortable with how this company uses your data, those other companies might not be as safe or responsible as you'd like.
4. Does the company sell or share user data with other parties? This is usually a red flag, but not always. If the policy lists the specific companies or agencies your data is shared with, that's a good sign because you can check the privacy policies of those specific partners. If it lists vague categories like "advertisers" or "third parties," you don't have that same ability to verify the policies of every place that will have access to your data. Unfortunately, most privacy policies I checked are vague.
5. What security measures are used to protect user data? If a company is gathering so much information, it's important to know whether it's taking the necessary steps to keep it safe from hackers and other criminals. If the privacy policy is vague on security, that's a red flag.
6. How long does the company store user data? Even with strict security measures, data breaches can still happen. Ideally, a company would regularly delete stored data so there's less information available for a hacker to steal in a breach. Some policies mention a time frame. Many don't, but they might discuss a way for you to manually delete your data or request to have your data deleted.
7. Which tracking technologies does the company use? Cookies are a well-known type of tracking technology. But a site might also use other trackers, such as web beacons and tracking pixels. The way to block or get rid of each one varies, so it helps to know which ones are being used.
8. How can I opt out or limit the data the company collects about me? See more on this topic in Step 4.

The AI responses to these questions weren't always helpful on their own. But they were usually enough to tell me whether the privacy policy mentions a particular topic.

Either way, I think it's always worth verifying anything your preferred AI chatbot tells you by searching the full text of the privacy policy itself for the relevant section.

3. Find the relevant section in the original text to get the full picture

Another useful feature of the AI summary is that it tells me the kind of language a particular policy uses, so I know what keywords to search for.

For example, Perplexity's privacy policy says, "We do not 'sell' or 'share' (as those terms are defined under the CCPA) (California Consumer Protection Act) personal information." Doing a search in the original privacy policy for "sell" or "share" would take you to that specific section and nowhere else.

Meanwhile, the AI summary mentioned that Perplexity uses my data for marketing and advertising purposes. By using CTRL+F (or Command+F on iOS) to search the full text of the policy for "advertising," I was taken to a section explaining how Perplexity "discloses" my information to advertisers and other third parties.

Assuming it is compliant with the CCPA, it's only disclosing de-identified information – data about me that can't be traced back to me specifically. But that can still include information such as my browsing activity, what devices I'm using and anything else it's collecting about me as long as that information doesn't tie that to, say, my name or address.

Since it uses the term "disclose" rather than "sell" or "share" in this section, I wouldn't have spotted that nuance if I had just searched the policy for the usual keywords without first getting the summary from AI.

4. Find and make use of every option you have to limit data collection

Maybe the most important use of the AI summary is that you can quickly figure out what choices you have for protecting your privacy.

In some cases, you might be able to opt out of having certain kinds of data collected or turn off certain cookies and other types of tracking technologies. In others, you might be able to request that data stored about you be deleted.

In an ideal world, you could choose to not use the particular website or app if you aren't comfortable with the data it's gathering or with whom it's sharing that data. In reality, some of the worst offenders when it comes to excessive data collection are major tech companies such as Google and Meta, and it's hard to navigate the internet without running into something owned by one of them.

Short of tossing every internet-enabled device you own and moving to the woods to live off-grid, you'll inevitably have to agree to privacy policies that you aren't entirely comfortable with if you want to use the internet.

If you don't have the wilderness survival skills to go off-grid, your next best alternative is to check that privacy policy and look for any options you have to keep your data as private as possible.

AI can help here because the specific language used can vary from one policy to the next. In some, the language used is "opt out." In others, those choices are referred to as "privacy settings" or "data settings" that you can adjust.

If the initial AI summary doesn't mention anything about your options for controlling the data collected or shared about you, ask a follow-up question to get a sense of what language to search for in the full text.

Once you find the relevant section, immediately make use of any privacy settings or adjustments available.

In some cases, this might be as easy as toggling certain features on and off in your account. In others, I noticed the company makes it a little cumbersome by requiring you to send an email to make the request.

What I learned from using AI to read privacy policies

One of the biggest lessons is that privacy is pretty much nonexistent online. Even when a website or app does allow you to limit data collection in some way, those limits are only a fraction of the enormous amount of information that companies are gathering about you.

By using AI to quickly summarize and skim through privacy policies, you have an opportunity to check what you're agreeing to before you do. For nonessential services such as, say, a new game your friend wants you to download, you can simply choose not to download it if your AI review pulls up too many red flags.

For services you need, such as a web browser or email server, you can quickly compare the policies of a few different services to find the one that offers you the most privacy.

In cases where you don’t have many alternatives — such as some Google services — you can, at least, find and make use of every privacy setting that service offers.

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“Fraud happens to everyone, even the smartest people,” says Phillip Reed, an asset protection attorney in Kalamazoo, Mich. “The tactics have gotten so sophisticated.” The Federal Trade Commission says 2.6 million consumers were victims of fraud in 2024, with losses of over $12.5 billion, a 25% increase from the previous year.

New developments, such as artificial intelligence and cryptocurrencies, have made cybercrime easier and more profitable than ever. With a little preparation and knowledge, you can protect your money and identity.

1. Digital crime is costing people more

While consumers lost a record amount of money to fraud in 2024, the number of complaints remained roughly the same as in 2023. In other words, the average incident got more expensive.

“Today’s fraudsters are patient. They aren’t in a rush to get $100 from you. They’re waiting to get $100,000,” says Kimberly Sutherland, global head of fraud and identity at LexisNexis Risk Solutions.

Investment scams were the largest category of losses at $5.7 billion, while Imposter scams were the second worst category, at $2.95 billion. Someone could impersonate one of your friends or family members and request financial assistance. With AI, they can spoof voices over the phone. Online dating scams gain a victim’s trust online through what appears to be a dream relationship before asking for money.

Theft from online shopping occurs more frequently but is less expensive in terms of the per-incident loss, according to Sutherland.

2. Retirees have a target on their backs

People over 60 were the most likely age group to report internet crime to the FBI in 2023, and lost the most money. Thieves see this generation as an easier target.

“They didn’t grow up with this technology as kids,” says Reed. “It’s not that they aren’t paying attention, but it’s something they had to learn and are now facing new threats.” At the same time, retirees’ lifelong savings create a tempting opportunity for scammers.

If you have any doubts, before agreeing to buying or providing any important information, share your emails, texts and popup images with someone else — a relative or a friend who can help you determine if it's a scam.

3. Strong passwords are worth the effort

Strong passwords are a simple and effective security measure. “It’s like locking your front door at night,” says Reed.

Avoid short codes with easily guessable words, such as names, addresses and common phrases. Strong passwords are at least 12 characters long, use a mix of upper- and lower-case letters, and include numbers and symbols.

You should have different passwords for every account. And avoid writing passwords down in an easy-to-spot location, as the wrong person could peek while visiting.

If keeping track sounds like a headache, you could use software like Bitwarden and LastPass to generate and store randomized passwords for all your accounts.

Enabling two-factor authentication further secures accounts. You’ll need to verify any login through your smartphone with a call or text.

4. Be proactive with safety measures

Your phone, computer, internet browser, and other software frequently recommend updates. Stay on top of them, as these include the latest cybersecurity systems.

Check your bank accounts and credit card statements weekly for unusual activity. “Scams often start with small transactions first, so you don’t notice. Watch out for a 34-cent charge at somewhere you’ve never shopped,” says Amber Schiffert, a financial planner with TARA Wealth in San Diego. You also could set up account alerts to receive a text, email or in-app message for every transaction.

5. Watch out for imposters

Cyberthieves constantly try to impersonate legitimate services: a text message claiming that you owe money for unpaid tolls, a phone call pretending to be from your internet provider, a computer screen popup saying it needs to fix a virus, an email claiming to be from the IRS saying you owe money, the list goes on. Seventy-eight percent of people reported receiving mobile scams at least weekly, according to a 2025 survey from Malwarebytes, which sells anti-virus software.

Slow down and verify everything. Cybercriminals often insist that you must act fast — or the “deal” will pass you by or your credit score will suffer. If you receive a call, hang up and contact the organization directly. Avoid clicking on links in emails, and refrain from replying with private information. You may want to establish a family code word that you can use on the phone to verify identities in case of AI voice fraud.

6. Be wary of deals too good to be true

Cyberthieves create spoof websites that resemble the brand and appear to link to legitimate companies that aren’t. They try to collect your credit card number, cash and personal information. Before placing an order, double-check that you are on the correct retailer’s page.

The same applies to posts on social media and other online marketplaces for selling goods and services. “If you see someone selling Taylor Swift tickets on Facebook for $400 when the market value is $4,000, don’t fall for it,” says Reed, the attorney from Michigan.

7 Guard your data like cash

Your personal data can be used for identity theft. If someone asks for information to verify your account, push back and ask if it’s really needed, especially for something personal like your Social Security number.

Consider what you reveal on social media platforms. Things like your date of birth, your childhood hometown and pet names could be used to answer security questions to access your digital accounts. Thieves could also use that information to impersonate you. Considering making your social media accounts private, so only people you know see what you post.

8. How you pay online matters

Credit cards have fraud protection, backed up federal law. If you report fraudulent charges within 60 days of receiving your account statement, your liability is limited to $50.

Other digital payment methods, such as electronic checks and payment apps like Venmo, have much less fraud protection. You can try filing a formal dispute with your bank or payment app, but there is no guarantee of a refund. “Think of it like giving someone cash with these payment options. You better be sure,” says Sutherland from LexisNexis.

And if you send cryptocurrency, that’s likely irreversible given the hidden nature of these transactions. It’s no wonder that people reported losing more money to bank transfers and cryptocurrency transactions than all other payment methods combined in 2024.

9. React quickly to possible fraud

If you suspect a problem, contact the bank, credit card company or payment app immediately. “That first 72-hour window is so important. It gives them time to lock down your account,” says Reed. The sooner you act, the higher your chance of them stopping the fraudulent transaction before it goes through.

You should also change the passwords on any exposed accounts. If you provided personal information, especially your Social Security number, consider placing a credit report freeze with the three major rating agencies. “As long as you’re not trying to buy a home soon or apply for other new lines of credit, we recommend using a freeze. It’s better safe than sorry,” says Schiffert, the financial planner from San Diego.

10. Authorities want to know what happened

Report incidents of cybercrime to federal agencies through the FBI’s Internet Crime Complaint Center and the FTC.

These agencies could help you retrieve lost money and assets while taking steps to bring justice against the criminals. “People feel too embarrassed to report, but they shouldn’t. It’s how authorities and businesses learn what’s needed to protect others,” says Sutherland.

Note: This item first appeared in Kiplinger Retirement Report, our popular monthly periodical that covers key concerns of affluent older Americans who are retired or preparing for retirement. Subscribe for retirement advice that’s right on the money.

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Smart glasses are gaining fans fast. Meta’s Wayfarer AI glasses have sold nearly 2.6 million units since their 2023 launch. Smart glasses have cameras, microphones, open ear speakers and other sensors to power an AI voice assistant to give directions, send messages, take photos/video, answer questions and more.

Meta and other tech companies see the devices as a new way to spur AI adoption and build a bridge to future augmented-reality glasses that are still years aways. Get users hooked on smart glasses and someday they’ll upgrade to a more advanced headset, the thinking goes.

Even Apple wants to tap the nascent market, which is poised to grow at nearly 50% per year through 2029, according to market research firm IDC. The company wants to launch smart glasses by late 2026, according to a Bloomberg report, though delays are likely. Apple has struggled to find users for its high-end Vision Pro virtual reality headset, despite Apple’s advanced VR hardware and software. The company likely sees smart glasses as a market that is too good to pass up, since it will lead to future headsets.

Meta’s flashy marketing campaign with top celebrities donning its eyewear highlights the big bet on the market. Bloomberg recently reported that the company plowed another $3.5 billion into eyeglass maker EssilorLuxottica, owner of Ray-Ban and Oakley, to expand its partnership.

Expect many more models and styles in the next couple of years. Meta’s Ray-Ban glasses start at $299; prescription lenses cost extra. An Oakley sports edition is water resistant, with better battery life. A much pricier model, which shows digital info on the lens, could come by year-end. But it won’t be easy to add more tech without making the glasses too bulky for most buyers.

Other companies working on new smart glasses include Snap, Google, Samsung and China’s Xiaomi, promising strong competition and improved devices for years to come. Don’t be surprised if smart glasses continue to gain traction as everyday consumer devices.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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There are just so many factors to consider during the initial stage: Where should I stay, does it make more sense to rely on Ubers or rent a car, what boat tour is the best bang for your buck, and on and on. The questions never seem to end.

Some people opt to hire a travel planner to avoid dealing with the logistics, but that costs money, while researching on your own doesn't. Unfortunately, it can be a slog to sift through all the information online — which is why I thought AI may be able to help make the planning process easier and more streamlined.

So, I used ChatGPT to guide me… and the results were unexpected, to say the least.

You're probably already using AI to plot your flights

It might sound strange to use AI to plan a trip, but the reality is it's likely already part of your process, Gagan Tandon, the managing director for AI & data services at TELUS Digital Solutions, told me. If you play around with Google Flights to compare ticket prices, or sign up for alerts from Hopper to know when costs are the lowest, you're using AI, he said. These apps, and others like them, have AI features built into them.

I did try using ChatGPT to ask what the cheapest travel options are from New York to Florida, hoping it would give me airline suggestions or layover advice. Instead, it recommended I take a days-long bus ride.

No thanks. Stick to the tools that are specifically built to help you when it comes to booking transportation.

AI makes it easier to decide where you want to stay

When I asked ChatGPT where I should stay in Key West, it emphasized why I needed to be in Key West proper (access to the main tourist highlights), but also offered suggestions for quieter nearby places to stay (Sunset Key, Stock Island). I'm unfamiliar with Key West, so this was a helpful starting point.

Plus, it listed off several different hotels, broken up by experience type: It had options for a luxurious stay, a charming boutique stay, an authentic historical stay and more. These descriptors were more useful than just looking at a list of hotels on Google and helped me select my top lodging choices much more quickly. (I was immediately into the ones described as "island vibes.")

I was also surprised to learn that I could ask ChatGPT which hotels in the area had availability the weekend of my trip — as just last year, ChatGPT didn't have very up-to-date information. However, it didn't provide actual prices, so I still had to leave the site to do more research. Sigh.

AI can help develop an itinerary… but it takes time to customize it

If you type "Give me a two-day itinerary for Key West" into ChatGPT, you get some great suggestions. On my first try, it broke down my entire day by the hour, suggesting restaurants, activities and even photo spots.

But it was pretty obvious that it was giving me the most popular things in Key West. Of course it had Duval Street, the Hemingway Museum and a kayaking tour on it. This is useful if you've just started researching a place, but the ideas are pretty generic and didn't include places that are less touristy and off the beaten path. Plus, while it gave a mixture of activities — Drinks! Beaches! Museums! – it didn't necessarily feel true to the trip I personally wanted to take.

However, there is a solution for that on ChatGPT: I just needed to make my prompt more detailed. On subsequent tries, I highlighted the trip atmosphere I was seeking and gave more detailed information ("focus on water activities, include a ghost tour, build in hotel breaks, no breakfast," for example). The resulting itineraries felt way more me.

Always double check AI's information

While it is possible to use AI to get recommendations for a customized trip, you do want to be wary, Tandon warned me. ChatGPT's information isn't always accurate, and since it doesn't provide links, it's not easy to immediately fact-check it.

"The AI is pulling from the web, so maybe it saw from a Reddit thread [saying] there's a cool cave by the beach. But that cave may no longer exist, or be off-limits for tourists. You don’t want to just trust everything it tells you," he said.

So, even though I liked the trip itinerary ChatGPT built for me, I still needed to take the time to make sure everything it recommended was actually, well, real. But even adding in the fact-checking process, it still was significantly easier and faster to use AI to plan my trip.

No, AI can't do everything for you, and there are certainly customization issues, but it was an excellent starting point for my itinerary. I may be naturally wary of AI, but I have to admit: I'll probably turn to it again for the next trip. After all, aren't we all searching for ease on vacation?

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One of China’s most potent trade weapons that it is wielding as the U.S. threatens new tariffs is a near-stranglehold on rare earth elements, a group of obscure minerals that happen to be vital to many high-tech applications and products. It’s not that rare earths are rare, exactly. But they are hard to mine and process. They aren’t evenly distributed across the world. Extracting and refining them is a messy process that can cause a lot of pollution.

China realized this decades ago and decided to exploit its sizable deposits of rare earths, ignoring the environmental damage. Its leaders wanted to corner the market, and they did. Consider the things that require rare earths: Drones. Missiles. Fighter jets. Spacecraft. Wind turbines. Electric cars. AI servers. That’s just a partial list. In general, rare earths are key to the magnets in advanced electric motors. Thus, they are vital for applications like advanced robots.

The U.S. has already eased up on tariffs in response to China’s recent ban on rare earth exports. But Beijing is still slow-walking sales of rare earths to American importers. What’s more, it still does not permit exports of them to U.S. defense contractors. Companies here and abroad are scrambling to lessen their dependence on rare earths where possible, knowing that China could cut off their supplies. BMW, for example, sells EVs whose electric motors don’t use rare earths. Other automakers are trying to do likewise. Japan has stockpiled a year’s worth of rare earths, after it suffered from an earlier Chinese export ban over a decade ago. But that is just a stopgap.

What’s needed is rare-earth mines and processing plants outside of China. Unfortunately, it takes time to open them: Three years, by one estimate. Still, expect a concerted push to reduce the world’s reliance on China. Countries with the most promising deposits: Brazil, South Africa, Namibia and other African nations. Greenland is also believed to have a rich trove of them, one reason President Trump is so keen on acquiring it, but mining may not be doable.

For now, the U.S. has only one functioning mine, called Mountain Pass, in California. New processing plants are a work in progress. One just opened in Malaysia. Australian miner Lynas is building another in Texas, but is waiting for new funding from Uncle Sam. There is also talk of a plant in Nebraska at NioCorp’s Elk Creek deposit. There are two major hurdles to building these plants: First, their wastewater and other toxic by-products generally provoke local opposition. Second, Beijing has positioned China as the main maker of the equipment for processing rare earths.

Ultimately, it’s going to take some political willpower, either in the U.S. or overseas, to support (and likely fund) alternatives to China’s monopoly on supply.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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From budgeting apps that offer personalized tips for reducing expenses to bank chatbots that deliver account details 24/7, a growing number of companies are incorporating AI into their financial tools and services. At the same time, many people are using conversational chatbot platforms, such as ChatGPT and Claude, for guidance on everything from rolling over a 401(k) to maximizing the benefits of a health savings account.

When used with care, AI can help us make better financial decisions. But it can also provide misleading and false information, as well as empower criminals to create sophisticated scams.

And right now, AI remains largely unregulated. A recent Pew Research Center survey found that 55% of U.S. adults and 57% of AI experts want more control over how AI is used in their lives.

So it pays to be vigilant to protect yourself while using AI — especially when you're using generative AI platforms such as ChatGPT and Claude that are powered by large language models. (LLMs, which are "trained" on data from a wide range of sources — such as website content, news articles and academic papers — can understand context and respond in a relevant, human-like manner.)

"New legislation will ultimately have to be introduced to protect consumers as we interact with these LLMs," says Andrew Lo, a professor of finance and the director of the laboratory for financial engineering at the MIT Sloan School of Management. "But until that day comes, I would encourage people to be very careful."

Here’s how to protect yourself, as well as ways to capitalize on AI.

Question AI's confidence

These tools often sound authoritative, even when they're wrong. Double-check answers from company chatbots and chatbot platforms.

Be especially careful with those that have a disclaimer stating they're in an early stage or testing phase. For critical or complex financial questions, ask the chatbot to connect you with a human, or call the customer service line and hit the prompts to speak with a live representative.

Be mindful that platforms such as ChatGPT, Claude and Perplexity can provide incorrect, misleading or fabricated information, in what's known as "hallucinating." They may also give you outdated material.

In short, don't rely on AI as a singular source of truth. "Use it to help make life easier, but not for vital or sensitive decisions," says Emma Foulkes, a certified financial planner and partner at Collective Wealth Partners in Atlanta.

Don't share sensitive information on LLM platforms

Never provide personal details such as your full name, address, account numbers or Social Security number on a platform such as ChatGPT.

"The moment that you start putting in sensitive information and getting value out of it, you're going to be tempted to give it more information," says Lo, adding that "once you give it that data, you are not getting it back."

Before you share anything, he says, ask yourself: Would I be comfortable if this appeared on the front page of the New York Times? And would I be okay with someone taking the information submitted, claiming it as their own and using it however they want?

Use AI as a creative brainstorming partner

A conversation with any number of AI tools and platforms can give you helpful advice on financial goal-setting, job-interview questions, budgeting and more.

For instance, you can provide general details about your life and then ask for ideas on how to reduce monthly expenses. Or you can go even deeper, asking it to produce recipes for 20 low-sodium dinners you can make at home that take less than half an hour to prepare and use less than $20 worth of ingredients. Within seconds, you’ll have a complete meal plan.

Tap into it as a junior research assistant

AI can assist you in gathering information — helping you compare credit card reward programs, say — and it can even put the data into a format that's easy to plug into a spreadsheet.

But it's not a substitute for expert advice, so remember to fact-check its responses. When using an LLM, ask it to provide sources so you can verify the information. (Keep in mind that LLMs can also generate links that don't work and cite fictionalized sources.)

Foulkes occasionally uses Perplexity, which acts like a supercharged search engine, for preliminary research — and she puts an emphasis on preliminary. Sometimes, Perplexity provides her with the sources she needs. Other times, it gives her random, unhelpful links.

Experiment with AI in low-risk ways

When it comes to high-stakes areas such as investing and financial planning, it's often better to rely on dedicated apps and websites from trusted providers, such as well-established banks and credible software companies. If you use general-purpose AI tools, they may not take important details, such as inflation, tax planning and health care costs, into consideration.

However, it can be helpful to explore what's out there in low-stakes situations to get an understanding of AI's limits and capabilities and stay on top of how AI is evolving. The bottom line is to proceed with caution and keep qualified humans in your financial life.

"AI is a brilliant product, but it can't deal with nuances," says Foulkes. "It doesn't have the expertise of a CPA, an estate-planning attorney or a financial planner."

Note: This item first appeared in Kiplinger Personal Finance Magazine, a monthly, trustworthy source of advice and guidance. Subscribe to help you make more money and keep more of the money you make here.

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AI chip designer Nvidia would jump out. So would data center operators and machine learning infrastructure plays such as Microsoft, Amazon.com and Alphabet. Software providers Oracle and Salesforce, which offer AI-powered features, would stand out, too.

The problem? They’ve been analyzed to death by Wall Street. And to borrow from the theme song of the TV sitcom Cheers, everybody knows their name.

“This cast of characters is pretty well understood,” says Andrew Choi, manager of the Parnassus Core Select exchange-traded fund.

But an emerging group of AI stocks doesn’t fit the typical profile and is flying under the radar. It’s possible to invest in the artificial intelligence–amplified digital revolution via less-obvious companies, such as so-called adopters, or beneficiaries of AI automation.

“You have to think a little bit out of the box,” says Robert Ruggirello, chief investment officer at Brave Eagle Wealth Management.

A good example is language-learning platform Duolingo (DUOL, $390), which uses an AI-powered chatbot and app-friendly purple-haired teen character named Lily to help people learn up to 40 languages by having interactive, real-time chats with her.

Or HVAC systems maker Trane Technologies (TT, $383), which uses AI to identify performance issues, better predict servicing needs and energy usage, and help systems work more efficiently. (Prices are as of April 30; names we recommend are in bold.)

AI, at its core, is a business productivity enhancer. So-called “reinvention-ready” companies that use generative AI (a type of artificial intelligence that enables machines to respond naturally to human conversation) show 2.4 times greater improvement in productivity and 2.5 times higher average revenue growth, according to a study by consulting firm Accenture.

But getting exposure to stocks benefiting from the use of AI is tricky.

There are dozens of mutual funds and ETFs with “AI” or “artificial intelligence” in their names, but they invest mainly in tech firms focused on the infrastructure build-out phase of this technology, such as makers of semiconductors, chip manufacturing companies, cloud computing and data center stocks, and software firms writing code.

A challenging adolescence

And with AI still in its adolescent stage (just 16% of organizations in 2024 had fully modernized, AI-led processes in place, Accenture found), pure-play funds focusing on the AI productivity investment theme don’t exist.

“There’s really no portfolio specific to that theme,” says Bryan Armour, director of passive strategies research for North America at fund-tracker Morningstar.

The still-young AI industry also makes it tough to precisely quantify the efficiency benefits and cost savings companies derive.

Analysts say AI has the potential to be transformative in some areas but provides just incremental benefits in others.

Investors, therefore, must do their own detective work to ferret out so-called AI 2.0 companies, or those benefiting most from AI-driven productivity gains and product breakthroughs.

A good starting point is to identify companies in sectors and industries outside technology that can benefit from AI automation-driven cost savings on a large scale or use machine learning to boost product innovation that spurs sales.

You’ll want to home in on companies boosting productivity and profit margins with the help of AI-driven efficiency gains and cost savings.

Just as Wall Street looks at same-store sales to gauge a retailer’s true strength, or customer acquisitions for clues about a streaming service’s growth, investors hoping to identify AI winners can measure progress by analyzing key metrics that measure efficiency gains. One gauge to focus on is revenue per employee.

“For a positive AI impact, revenue per employee should increase over time,” says Ulrike Hoffmann-Burchardi, head of the chief investment office, global equities, at UBS Financial Services.

AI can boost efficiency (especially in businesses that rely on human workers who perform repetitive manual tasks) by increasing worker output or by reducing costs via headcount reductions.

A second data point to watch is profit margins. “AI should help drive margin expansion,” says Jeremiah Buckley, portfolio manager at Janus Henderson Investors, meaning a greater percentage of each sales dollar is retained as profit.

Other key measures to track are employment headcounts and costs (are they falling?); customer-service efficiencies (are phone, online, or chat wait times shrinking?); and, of course, sales (are they increasing?).

“AI is just one more compelling rationale to consider when picking stocks,” says Choi of Parnassus Funds.

Beyond the Magnificent Seven

AI-driven productivity is the next long-term propellant of stock prices, as the internet was 25 years ago, according to Janus Henderson Investors, with the technology seen as infiltrating every sector, industry group and business.

One investment approach, therefore, is simply to buy a broad, low-cost index fund. For another approach, Ed Yardeni, president of Yardeni Research, touts the “S&P 493” — a reference to the stocks in the S&P 500 index other than the Magnificent Seven — as “big beneficiaries” of the expected AI productivity boom.

Exposure to those 493 large-cap stocks is available via Defiance Large Cap ex-Mag 7 (XMAG, $20), a $32 million ETF that just opened in October — so it doesn’t have enough of a track record to recommend it. The fund tracks an index of all S&P 500 stocks except for the Magnificent Seven.

Certain sectors stand out in the search for AI 2.0 winners. We zero in on three below.

A good fit for finance

One place to look for AI adopters with upside potential is your local bank, where many tasks and client dealings once performed by humans are now handled by AI-powered tools, such as chatbots and virtual assistants.

That frees employees to focus more time on products and customer touchpoints that drive revenue. Big banks have tens of millions of customers, countless daily customer service interactions, mountains of personal and financial account data, and a huge responsibility to spot and fight fraud, and are poised to profit from machine-driven efficiency gains on a massive scale.

“Big banks,” says Yardeni, have “the most potential for bang-per-buck productivity gains.”

Erica, an AI-driven virtual financial assistant created by Bank of America (BAC, $40), for example, has interacted with customers more than 2.5 billion times since its 2018 launch. Last year, it helped 2 million customers a day, the bank says.

At JPMorgan Chase (JPM, $245), the nation’s biggest bank, most employees have access to large-language-model tools that enable them to use generative AI to interact with customers and assist with various work tasks.

JPMorgan is also adding generative AI to call centers to help agents more quickly answer questions about car loans, mortgages, credit cards and deposit accounts. AI also helps detect fraud, which minimizes write-downs for theft-related losses.

“JPMorgan has been out in front of this,” says Brave Eagle’s Ruggirello.

Investors betting that AI will boost the U.S. banking industry broadly might consider Invesco KBW Bank ETF (KBWB, $61), which invests in two dozen banks and sports a yield of 2.9%.

Insurance, a data-processing-intensive business, is another beneficiary of AI. Property and casualty insurers such as Allstate (ALL, $198) and Progressive (PGR, $282) are using AI to enhance underwriting and claims processing, refine risk assessments related to weather, and improve pricing strategies.

Handling claims for a car totaled on a highway or a home damaged by a hurricane, for example, can now be done in large part using AI tools.

“A lot of this work is becoming more and more digital,” says Choi.

Modernizing industry

Efficiency, precision and cost savings are the hallmarks of industrial businesses, and AI could do for manufacturing companies today what the assembly line did for autos a century ago.

Machine learning is already making an impact on product designs, predictive monitoring technologies, and energy and operational efficiency, as well as lowering costs through automation and advanced robotics.

Gregg Fisher, founder of Quent Capital, is bullish on German-based tank manufacturer Rheinmetall (RNMBY, $339). It offers an AI-supported navigation system that enables tanks to maneuver complex terrains autonomously, reducing the need to put human operators in dangerous wartime situations. The system can be installed in existing and new tanks.

“Because of the war in Ukraine and what’s happening in Europe, the Middle East and the rest of the world, [Rheinmetall] can’t keep up with the orders they’re getting,” says Fisher.

Another industrial stock with AI chops is Axon Enterprise (AXON, $613), the maker of non-lethal Taser stun guns and a suite of AI-enhanced public safety tools, says Bryan Wong, manager of Osterweis Opportunity Fund. Axon’s AI tools can auto-generate police reports — which can eat up 40% of an officer’s day — in half the time by transcribing audio from officers’ body-worn live-streaming cameras.

The technology can create court-ready documents in minutes and scan license plates of vehicles traveling 140 miles per hour, across three lanes of highway, to search for suspects.

“Think about the cost of an officer’s time,” says Wong. “If you can save even one hour, you can redeploy the officer back toward policing.”

Axon is the market leader in body-worn cameras, according to market-research firm Mordor Intelligence. Still, Axon’s growth runway is long, as its market penetration of law enforcement is less than 15%.

Agriculture heavy-machine maker Deere (DE, $464) is using AI for precision farming, using machine vision to distinguish weeds from crops.

“This See & Spray system only sprays herbicide on the weeds,” says Ruggirello, saving farmers time and money by significantly reducing the amount of herbicide they have to put down.

A prescription for health care

AI can speed up drug development by pharmaceutical and biotech companies, and it can be a boon to health insurers such as Cigna Group (CI, $340) that are looking to automate and better analyze claims processing and improve customer service. The technology can also assist doctors with data-driven health decisions and earlier disease detection.

Intuitive Surgical (ISRG, $516) uses AI technology in its surgical robotics systems. Intuitive, best known for its minimally invasive procedures, draws on its database of more than 10 million procedures to provide insights that help speed surgeon training, assess patient risk factors and predict potential complications, not to mention improve patient outcomes.

“You can learn quite a bit from that huge collection of data,” says Choi.

When it comes to AI, the early adopters are the ones to watch. As the AI rollout matures, says Jay Jacobs, U.S. head of thematic and active exchange-traded funds at money management firm BlackRock, the focus will shift from whether it’ll have a big impact (it will).

Now, “it’s more about who’s going to adopt it early and use it effectively, versus the companies that are going to fall behind,” he says.

Note: This item first appeared in Kiplinger Personal Finance Magazine, a monthly, trustworthy source of advice and guidance. Subscribe to help you make more money and keep more of the money you make here.

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With the rapid rise of artificial intelligence, a sea change in cybersecurity is underway. As new threats emerge from generative AI adoption, AI-enabled security tools are also fortifying defenses.

AI’s rise has prompted higher spending on more advanced IT security. In 2025, security spending is set to grow by 12.5% in the U.S. versus last year, hitting $131 billion, according to technology market research firm IDC. Global growth will be similar, led by large companies, but even small businesses are spending more. The top spending sectors are finance, government, telecom and health care, looking to buy tools to secure cloud apps, manage digital identity and analyze cyber threats.

Attacks are worsening across the board, with an increase in speed, scale and sophistication. AI is supercharging phishing emails and voice clones through AI-created text and audio that often trick victims into sharing private info or clicking on malware. Ransomware is on the rise, too. Cyberthreats are growing across the globe. China’s cyber espionage, including targeted attacks, is surging. Iran is using AI to find security flaws to exploit and to spread misinformation online. That’s sure to increase. Russia, too, is using AI for attacks and digital propaganda.

Physical infrastructure remains a ripe target. This includes chemical plants, electric grids, dams, hospitals, transportation systems and nuclear plants. A recent example is China’s Salt Typhoon intrusion into U.S. telecom networks.

Employee use of AI, much of it unsanctioned, gives security pros heartburn. Start with the risk of divulging company secrets as workers share data with public AI chatbots, which may be insecure. Software from Palo Alto Networks and others tracks AI use in a network to protect data and block unapproved AI apps. Other AI threats include “prompt injection” attacks, when an AI chatbot is tricked to override built-in policies, giving access to unauthorized company data or systems. “Hallucinations,” which are inaccurate but true-sounding responses, also pose a security risk.

AI has big promise for improving cybersecurity software, but it brings risk, too. Some things AI can already do: Find security flaws in software and help patch them. Develop software that resists security flaws. Monitor threats, pinpoint real dangers and alert human cyber pros. AI security chatbots can give security staff detailed answers on threats or company policies to help them solve issues.

One of the most exciting developments is “AI agents” that can do security tasks autonomously. Built by companies such as Amazon, Microsoft, Google, CrowdStrike, OneTrust and Radiant Security, the tools can patch security flaws, thwart data breaches, track insider threats, simulate attacks and more. Another use for autonomous agents is issuing employee log-in credentials to a piece of software via email. A tedious task that is now done manually by IT staff.

But there’s fear that autonomous tools will make mistakes or go rogue. These AI agents need to be secure themselves, with clear guardrails and regular audits. “Behind this incredible era of agentic AI are intricate security considerations that organizations must prepare for today,” said Hammad Rajjoub, director of security at Microsoft, at a recent conference. There are already plans for deploying AI agents to guard other agents.

Despite the new AI threats, basic cybersecurity precautions still mitigate risks for businesses. Use strong usernames and passwords, plus another factor, such as a one-time PIN or fingerprint. Regularly update and patch software. Closely vet security vendors and new AI tools. Minimize data stored. Provide regular security training to staff. Prepare a security incident response plan and regularly test it.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Large language (deep learning) models are now helping us with almost everything in our daily lives, from tackling to-do lists to detecting diseases to picking stocks to buy.

It's that last one that's the focus of this article. Given AI's ability to analyze massive amounts of data in a very short time — a feature that requires an enormous amount of energy — the technology is a natural fit for investors, day traders, hedge funds and the like.

As an example, most banks and brokers now offer robo-adviser accounts, which use AI to build and manage investment portfolios at a much lower cost than those maintained by humans. (Still, financial planning should likely be left to the actual people.)

As for those do-it-yourself (DIY) investors, there's a laundry list of stock-picking platforms such as Danelfin that use AI to spit out lists of the top stocks matching their specific criteria.

I decided to test AI's predictive capabilities, and, on Friday, May 30, I asked Google's Gemini AI chatbot where I should invest in June. I also asked for a list of the best stocks to buy for the month.

Here's what it had to say and how its predictions matched actual market movement. All returns are through the June 30 close.

Where to invest

When I asked Gemini where to invest in June, it offered several suggestions of "potential investment opportunities and considerations," including the industrial sector and select tech stocks.

The industrial sector, according to Gemini, "is seeing momentum from rising infrastructure investment," as well as efforts to "revitalize domestic manufacturing."

Industrial stocks, as measured by the Industrial Select Sector SPDR Fund (XLI), rose a little more than 3% in June, putting them right in the middle of the pack as far as the 11 S&P 500 sectors go.

Among the month's biggest industrials gainers were GE Aerospace (GE, +4.7%), GE Vernova (GEV, +11.9%) and Howmet Aerospace (HWM, +9.6%).

The chatbot also advised keeping an eye on select tech stocks "that are drawing attention," including Nvidia (NVDA), which finished the month up 16.8%, and Microsoft (MSFT), which gained 8%.

The stock market closed out June with strong gains as investors cheered positive developments in President Donald Trump's tariff policies, including easing trade tensions between the United States and China.

For the month, the tech-heavy Nasdaq Composite emerged as the clear winner, rising 6.6% to end June at a record high. The S&P 500's 5% return was enough to send it back into all-time-high territory, while the blue chip Dow Jones Industrial Average added 4.3%.

Best stocks to buy in June, according to AI

When I asked Gemini on May 30 what the best stocks to buy in June would be, it offered several suggestions.

It tapped Alphabet (GOOGL) as a stock pick that's "favored by fund managers," and is "positioned well for growth," given the company's "dominance in search (Google), YouTube, Android and Google Cloud."

Gemini added that some analysts feel GOOGL is undervalued.

GOOGL shares rose 2.6% in June, lagging the S&P 500's 5% return. Longer term, the communication services stock is down 6.9% for the year to date and has shed 3.3% the past 12 months.

Nike (NKE), an athletic apparel and footwear maker, is another name that Gemini suggested was a stock to watch in June, given "recent analyst discussions and market activity."

NKE shares were down more than 9% for the year to date heading into June, but pared this deficit to 6.9%, thanks to a well-received earnings report.

HSBC Global Research analysts think the blue chip stock has finally reached an inflection point, and upgraded it to Buy from Hold after earnings.

"We think there is more than tangible evidence that Nike has a path to see its sales rebound in the not-too-distant future, and its margins to be repaired, and this despite an unfavorable tariff headwind," they wrote in a note to clients.

HSBC adds that Nike appears to be "a battered leader with a convincing reboot," and that its "full refreshed team … is acting with speed and experience."

The bottom line on AI vs the stock market in June

Gemini notes that its recommendations are "for general guidance only and does not constitute financial advice," which I appreciated.

It also reminded me of the risks involved with investing in the stock market, such as losing my money, and advised me to conduct my own due diligence and consider speaking with a financial adviser.

I would never blindly invest in anything an AI chatbot recommended — and neither should you.

Still, it's an interesting exercise to see how picks made by AI would perform throughout the month — so much, I'm doing it again for June.

Check back next month to see how AI's stock picks fared. Hint: We're watching Jabil (JBL) and cybersecurity stocks.

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Or dirty dishes in the sink.

Or a growing dread of leaving the house.

These are some of the common signs health professionals say indicate a need for care. It’s also a growing reality for people as we live longer. But with rising caregiving costs and a national shortage of caregivers, the question is shifting from “who will care for me when I’m old?” to “what will care for me?”

Consider nearly half of U.S. states (48%) are on the brink of an unpaid family caregiving emergency, according to Columbia University’s Mailman School of Public Health. The U.S. will need an estimated 4.2 million new home care workers by 2026, a gap that won’t be easily filled.

Two in five U.S. adults are now family caregivers, and nearly all face financial strain and burnout, research from Edward Jones finds.

This is where artificial intelligence (AI) is stepping in. While older adults are often excluded from AI design, caregiving is one exception. AI-driven products aim to keep older people connected, enhance health monitoring and help them remain independent.

But can these technologies live up to their promises — and what about the risks? Should you start preparing for a future that might include a robot sidekick?

How AI is transforming caregiving

Imagine being alone at home, engrossed in a book. Suddenly, a voice calls from across the room: it’s a reminder to take your medication. What could have been a dangerous oversight now becomes a simple conversation.

A tabletop AI companion

That’s one of the capabilities of ElliQ, an AI companion robot designed to engage older adults and track their well-being. The system's "face" lights up, moves and speaks to the user in a way that feels almost human.

“We hear from families every day that ElliQ is helping their loved ones feel more connected and less alone,” an Intuition Robotics company representative says. “Users interact with ElliQ on average more than 30 times a day, with 90% saying it reduces their loneliness and 95% reporting improved wellness.”

Makers of these AI companions hope not only to extend care when loved ones can’t be there and provide families with real-time insights, but also to make care more affordable and accessible.

As the company notes, paid human caregivers typically cost about $30 an hour, while AI companions cost just $0.30 an hour. “That means 100 older adults can be offered assistance for the cost of supporting one.”

Hybrid AI and human caregiving

Combatting loneliness and spotting early cognitive decline are two of AI’s biggest current opportunities.

“Being above 65 and lonely is worse for you than smoking 15 cigarettes a day, in terms of premature death risk,” explains Neal Shah, CEO of CareYaya. This nonprofit tech startup connects families with trained student caregivers and is launching AI applications to complement human care.

For instance, it offers a phone-based AI companion that uses language models fine-tuned for older adults to help boost mood and identify red flags in mental health or memory, prompting human follow-up.

The company has also developed tools designed to relieve caregiving stress by automating administrative tasks such as managing insurance claims — work that consumes an average of 13 hours a month for family caregivers, Shah notes.

Training is another promising area, as most family caregivers receive less than two hours of formal training. AI-driven micro-learning apps can now deliver quick, personalized instructions.

Looking ahead, Shah envisions AI companions that could read facial expressions or gait changes to trigger human intervention, as well as real-time translation tools to bridge cultural and language gaps in caregiving.

More options for AI companions

There are several additional for-profit companies offering AI companionship over the phone or other hardware. These programs engage seniors in conversations about their lives, ask follow-up questions and make suggestions for solving problems. They recall past conversations and may be able to help schedule medications.

Meela is a personalized AI voice companion that costs about $40 per month. Meela does not require any hardware other than a phone.

ONSCREEN calls seniors to combat loneliness, but also offers video engagement by accessing a user's television or tablet. Pricing depends on the service you select. The service is only offered in English.

Grandpad is a tablet with large icons and programs designed for seniors. This hardware solution garners mostly positive reviews from Senior Living.

These are just a few options available now for senior companionship and care. If you are ordering for a loved one, be sure to try the system out yourself and check for privacy controls. Someone with mild dementia may be able to use many of these options, whereas someone with more advanced dementia might be limited to answering a phone call. If you're unsure what service would work for a loved one, ask a geriatric social worker for advice.

The limits and risks of AI and AI companions

While the potential is exciting, experts caution against seeing AI as a cure-all.

Human connection

“Our research shows that digital and AI-driven companions can play a positive role by offering opportunities for engagement,” says Dr. Barbara Barbosa Neves, sociologist of aging and technology at the University of Sydney. But, she says, “Social connection and well-being in later life aren’t one-size-fits-all. They require a mix of approaches, tailored to the diverse needs, aspirations, life experiences and capabilities of older adults.”

Many older adults, she adds, are concerned that relying on AI could reduce time spent with loved ones and deepen feelings of detachment. Some have described AI companions as patronizing or infantilizing, a way for society to sideline and forget about them.

“AI may facilitate contact, but it doesn’t always support meaningful relationships that address loneliness,” she explains. “For some older people, especially those experiencing prolonged loneliness, technology can only go so far. In some cases, it may make people feel lonelier and more isolated.”

AI Bias

Another concern is algorithmic bias. Many AI systems are built without sufficient representation of older adults, leading to tools that misinterpret their needs or exclude them entirely, Dr. Neves says.

Focus on areas where AI excels

Ultimately, Dr. Neves warns against “techno-solutionism” — the belief that technology in isolation can fix every problem. “Aging is a natural part of life — a sign that we’re alive — not a problem to be solved!”

Shah offers a grounded perspective, viewing AI as a tool to support, not supplant, human caregiving. “Think of AI as your co-pilot, not the captain,” he says. “AI excels at scalable tasks — reminders, paperwork, conversation. Human caregivers excel at empathy, touch and complex judgment.”

How to plan for your future caregiving needs today

Whether caregiving becomes more tech-driven or remains a largely human effort, one thing is certain: planning for potential care needs is critical.

“Healthcare and long-term care costs pose one of the most serious risks to retirement security,” says David Rosenstrock, financial advisor at Wharton Wealth Planning. A couple with high drug costs may need about $325,000 saved by age 65 to cover health care expenses in retirement.

He suggests, “Health Savings Accounts (HSAs) can be a great and flexible way to plan for future health expenses, if you start early and contribute systematically.”

Long-term care insurance may also be worth considering, says advisor and CFP® Catherine Valega of Green Bee Advisory. “The new policies leverage your insurance dollars for long-term care expenses, and if unused, your heirs receive a death benefit.”

When using AI tools, data security is another key concern. Shah encourages families to ask vendors where data is stored and who can audit their models.

Finally, don’t overlook family conversations. Jessica McNamee, wealth management advisor and founder of Sirius Wealth Strategies, says: “The most common mistake I see is not asking aging parents or family members what role they expect others to play in their care. It is so important to open the lines of communication between generations.”

That’s because caregiving, no matter how burdensome, remains deeply meaningful. In fact, 80% of family caregivers say the role has strengthened their relationships with loved ones, with most reporting feelings of personal fulfillment and gratitude.

And it’s unlikely to change, no matter how advanced AI becomes. “I think even the best AI will remain just tools,” Shah says. “The heart of caregiving is still a reassuring human touch, eye contact and the dignity of being heard by another person.”

So even if technology makes caregiving easier, it won’t make it any less human.

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The move wasn't just about bulking up Salesforce's enterprise software portfolio – it was also a strategic play on artificial intelligence (AI). Bloomberg reports that International Business Machines (IBM) was also in the running for the deal, highlighting just how competitive the AI space has become.

Large-scale acquisitions like this one have become relatively rare in the public markets lately.

Higher interest rates, economic uncertainty, and market swings have made companies more cautious about making big deals.

In fact, the number of publicly traded companies pursuing large acquisitions has fallen sharply in recent years – from 1,423 in 2021 to just 815 so far in 2025, according to Kaidi Gao, senior venture capital analyst at PitchBook.

Still, M&A activity is starting to bubble up. The tech sector, in particular, seems more willing to open its wallet – especially when it comes to fast-growing fields such as AI, cybersecurity and fintech.

Just look at Meta Platforms (META), which is reportedly eyeing a $14 billion investment for a 49% stake in Scale AI. The deal would include not only a major equity share but also an effort to bring Scale's high-profile CEO, Alexandr Wang, on board.

Tech deals to watch

With this renewed momentum in tech dealmaking, it's worth asking: Who might be next? Here are four companies that could be on the radar.

Innodata

Innodata (INOD) isn't exactly a household name, but for over three decades, the company has been quietly building its credentials in digital content and data services. And since 2019, INOD has been aggressively pivoting its business to AI.

The company organizes its operations around two main customer groups: the "Builders" – think Big Tech firms actively developing their own generative AI models – and the "Adopters," businesses looking to integrate AI into their operations.

For the Builders, Innodata supplies the backbone: annotated datasets in over 85 languages, pipelines for fine-tuning and safety protocols to help ensure models behave responsibly.

Innodata's consulting arm manages the Adopters by helping clients utilize AI operations (AIOps), maintain model governance and implement domain-specific platforms in areas such as media monitoring and regulatory compliance.

One of Innodata's core strengths lies in its platform strategy. Unlike many smaller firms that focus on a single niche, Innodata has built a full-stack ecosystem.

Vertically, it offers tailored solutions for specific industries, including health care, legal and media. Horizontally, it supports broader AI functions including annotation, document intelligence and model evaluation.

At the center of it all is GoldenGate, Innodata's proprietary low-code platform that enables customers to build, deploy and scale AI applications securely. With a global team of over 6,000 specialists and operational hubs in more than 20 locations, the company can serve multinational clients with complex, multilingual needs.

The numbers tell a compelling story. In the first quarter of 2025, Innodata posted a 120% jump in year-over-year revenue, while net income surged to $7.8 million from $1 million the year prior.

Given its accelerating revenue, proprietary platforms and deep integration into the generative AI pipeline, Innodata could be an attractive acquisition target among tech stocks.

Companies such as Microsoft (MSFT), Alphabet's (GOOGL) Google, Amazon (AMZN), and yes, Meta, are pouring billions into AI, and owning a firm like Innodata could help them bolster the infrastructure they need to build smarter, faster and safer systems.

UiPath

UiPath (PATH) was one of the first movers in Robotic Process Automation (RPA) – a field that helps businesses eliminate repetitive tasks by letting software bots mimic human actions, such as logging into systems, copying and pasting data, or navigating through clunky legacy workflows.

But as automation needs have grown more complex, so, too, has UiPath's ambition.

Today, the company is positioning itself as more than just an RPA vendor. It's now offering a broad enterprise automation platform that's increasingly infused with AI.

The latest evolution is what UiPath calls "agentic automation." This is essentially AI-powered agents that can independently operate across different systems, make contextual decisions and adapt on the fly.

This new wave of automation is already seeing meaningful adoption. UiPath customers have run more than 250,000 AI agent tasks and launched over 11,000 automated processes using the company's Maestro orchestration engine.

For Q1 of fiscal 2026, the company reported $357 million in revenue, a 6% increase from the year prior. Annualized recurring revenue (ARR) grew by 12% to $1.7 billion.

PATH's balance sheet remains strong, too, with free cash flow of $117 million and $1.6 billion in cash, cash equivalents and marketable securities.

Strategic alliances have been a key part of UiPath's growth playbook. The company is working with Google Cloud on AI agents for medical summarization, integrating with Microsoft Copilot Studio for bidirectional workflows, and teaming up with Deloitte on enterprise resource planning (ERP) transformations.

High-profile customers such as Delta Air Lines (DAL) and Continental Resources add credibility to the platform's scalability and effectiveness.

As enterprise automation becomes a cornerstone of digital transformation, UiPath's combination of AI, orchestration and a robust partner ecosystem makes it an intriguing acquisition candidate.

Companies such as Microsoft, Oracle (ORCL) or ServiceNow (NOW) – each with their own automation ambitions – could benefit from bringing UiPath's capabilities in-house.

"UiPath's key advantage is solving enterprise AI's biggest challenge: trust and governance at scale," said Nandan Mullakara, founder of Bot Nirvana.

"They have existing customers already using the platform with established guardrails. As Agentic AI is expected to dominate automation, UiPath's enterprise relationships and proven orchestration infrastructure will become exponentially more valuable," Mullakara added.

CyberArk Software

CyberArk Software (CYBR) has long been a dominant player in privileged access management, helping enterprises control who and what gets access to critical systems.

But as cloud adoption, AI automation and machine-to-machine interactions redefine corporate IT environments, CyberArk has expanded far beyond its original niche.

Today, the company's Identity Security Platform offers protection not just for employees and administrators, but also for non-human users such as bots, devices and autonomous AI agents.

In the first quarter of 2025, CYBR revenue jumped 43% year-over-year to $318 million. Free cash flow hit $96 million, while non-GAAP operating margin improved to 18%, up from 15% the year before.

CyberArk's expansion hasn't been purely organic. In 2024, the company acquired Venafi for $1.5 billion, a deal that brought machine identity and certificate lifecycle management into its portfolio. That move alone expanded CyberArk's total addressable market by roughly $10 billion.

Then came the 2025 acquisition of Zilla Security, which enhanced the firm's capabilities in identity governance – a critical area as organizations look to tighten access controls across sprawling hybrid environments.

With recurring revenue, free cash flow, and a strong position in the AI-era security stack, CyberArk is starting to look like a natural acquisition candidate.

Tech giants such as Microsoft, Oracle, or even ServiceNow could see the cybersecurity stock as a strategic bolt-on to bolster their zero-trust and identity offerings.

And Alphabet's recent $33 billion bid for cloud security startup Wiz signals an appetite among large platform players for high-growth, identity-focused firms – and CyberArk fits that mold.

As identity becomes the new perimeter, its blend of technical depth and predictable financials makes it a valuable asset in a crowded field.

Marqeta

Marqeta (MQ) is a fintech company revolutionizing payments with its cloud-native card-issuing and processing platform.

Through flexible, open APIs, it enables clients to design fully customized debit, prepaid and credit card programs. Its modular offerings include money movement, risk management, rewards and seamless integration with issuing banks and network partners.

Customers can embed genuine payment experiences directly into their apps and websites, empowering launches such as Square's Cash Card, Affirm's BNPL cards, and crypto-enabled products including Bitpanda's new card across 26 European countries.

Marqeta has posted strong expansion in recent years. Total payment volume (TPV) climbed from $166 billion in 2022 to $291 billion in 2024.

In Q1 2025, TPV hit $84 billion, representing year-year growth of 27%. Net revenue rose 18% to $139 million and gross profit jumped 17% to $99 million. Marqeta's gross margin arrived at 71%, the same as the year prior.

Meanwhile, Marqeta's stock remains modestly valued at 2.6 times gross profit and its market cap hovers around $2.5 billion.

This makes it an interesting top tech deal target, especially in light of its issuer-processing infrastructure and strong balance sheet with about $1 billion in cash.

Suitors could include private equity groups or financial services incumbents such as Mastercard (MA), Visa (V), Fiserv (FI) and Fidelity National Information Services (FIS).

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AI isn’t just coming for white collar jobs. It’s also quickly being adopted in blue collar fields, taking on administrative tasks to save time, score more sales and boost customer satisfaction.

Many home service contractors have already tried AI for work, especially as it gets integrated into popular trade-specific business software. There’s a growing number of HVAC pros, electricians, plumbers, landscapers, painters, cleaners and home remodelers who use AI regularly.

Tradespeople who are AI users are saving four hours per week on average, according to a recent survey by Housecall Pro, a software platform for trade professionals. The survey found that 40% of their customers are actively using AI, with workers under 35 especially likely to use AI daily. Both big and small companies are part of the trend, even solo operations.

“Our customers are used to using tools in their business and see AI as another tool, like any other tool in their tool bag,” says Roland Ligtenberg, senior VP of innovation at Housecall Pro.

Back-office work
Top uses today include marketing, customer service, scheduling and paperwork. AI tools can automate marketing content for websites or online ads. Housecall Pro’s “Write it for me” tool helps craft website copy, customer responses and emails, simply by providing a short prompt. An AI voice assistant can answer calls 24/7, book a job and put it in the calendar. Customer emails can get automated responses and suggested appointment times. AI-generated reminders, sent via text or email, can help secure a job after giving an estimate.

AI can also help with data entry and financials, such as automated invoices or pricing recommendations. Need to know how many water heaters Joe installed last month, so you can pay him? Just ask an AI chatbot.

Expect AI to soon become standard for many home services companies. Vendors are looking carefully at what may spark more adoption. Some businesses want more information before they trust and understand AI, waiting to see detailed case studies and clear examples of a good return on investment.

A 'one-stop shop' for trades
Besides Housecall Pro, other software vendors with AI include Jobber and ServiceTitan. Housecall Pro’s basic package for one user starts at $59 per month and includes tools for scheduling, quotes, booking, invoices and more, plus access to their AI tech. ServiceTitan has a personalized AI assistant dubbed FieldAssist to answer questions related to your company’s data.

Ligtenberg notes that using AI with Housecall Pro’s cloud platform means companies don’t have to pay attention to confusing and constant AI updates at leading tech companies. As AI models improve, Housecall Pro can swap in any underlying AI tech upgrades to improve voice assistants or other tools. “Our customers just want everything in one place,” says Ligtenberg.

Trade businesses are often experimenting with low-risk tasks first, such as writing marketing copy, where mistakes wouldn’t be costly to fix. Soon, more will shift to more important work, such as scheduling and dispatching, which needs to be highly accurate, to AI tools.

AI can be used for old-school media, too. Housecall Pro’s AI can come up with pithy text for a 4-inch by 6-inch printed postcard mailed to prospective customers, a tried and true marketing practice that local and national trades companies still rely on.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Engineers are training machines to solve complex problems, mimic human reasoning and bring robots one step closer to life.

Yet, while the AI advances emerging from Silicon Valley might resemble the futuristic tech of Star Wars, they’re missing a familiar story arc — the presence of an older, wiser guide. Luke had Obi-Wan. Oprah Winfrey had Maya Angelou. Bill Gates turned to Warren Buffett.

In the past, young tech visionaries often sought seasoned mentors to help turn raw innovation into lasting impact. Steve Jobs mentored a young Mark Zuckerberg, for example. Today, the future is being written mainly by the young.

That generational imbalance is striking, especially when you consider who will be most affected.

How AI is missing the wisdom of older adults

According to AARP, 59% of Americans age 50 and older say today’s technology isn’t designed with them in mind. That’s a massive blind spot, given that more than 120 million Americans are now 50 and older. By 2030, at least 21% of the population will be 65 or older, and the first wave of millennials will begin turning 50.

Steve Jobs once said, “Design is not just what it looks like and feels like. Design is how it works.”

That’s where many older adults feel left behind. “I think the biggest disconnect is in what’s prioritized in tech itself,” says Brittne Kakulla, senior research adviser at AARP. “Older adults prioritize function over flash, which can be counter to the tech industry’s obsession with speed and novelty.”

This raises a central question: How well will AI work as it becomes integrated into everything from health care to personal finance if younger generations primarily program it?

Researchers and advocates say the stakes are high. Excluding older adults from the design, testing and governance of AI could lead to systems that not only overlook their needs but also fall short for everyone.

Ghost in the machine: How AI is trained and why bias is built in

Artificial intelligence systems are designed to recognize patterns and make decisions by analyzing vast amounts of data. Through machine learning, these systems “learn” from what they’re fed — whether it’s language, lab results or consumer behavior — and generate outputs based on that information.

What goes in determines what comes out. If that input reflects bias, or if the teams building the models lack diversity, those flaws are embedded into the technology itself.

A review published by the journal Nature identified age-related bias throughout the machine-learning pipeline, from how data is selected and labeled to how models are evaluated.

Real-world examples are already raising red flags. A 2024 study found that AI chatbots, often powered by "large language models" (LLMs), such as Copilot and Perplexity, frequently returned responses laced with age-related stereotypes, evidence that bias isn’t theoretical, but built into the behavior of the tools themselves.

Compounding the issue is the malleability of these systems. While most large language models rely on massive datasets, their personalities and tones can be quickly altered.

Elon Musk’s Grok, for example, sparked backlash after parroting false narratives about a white genocide in South Africa. Even when users asked about such unrelated topics as baseball, Grok responded with the false genocide story.

How to give feedback

When using an LLM or chatbot, pay attention to age-related content. If you find it to be biased or inaccurate, you can usually provide feedback by clicking on a thumbs-up or thumbs-down sign, or clicking on "report."

As philosopher Matteo Pasquinelli told The New York Times, “AI needs us: Living beings, producing constantly, feeding the machine. It needs the originality of our ideas and our lives.”

What if that perspective is incomplete?

What happens when older adults are left out?

Take health care, in which AI already plays an increasing role in diagnosing disease, managing treatment plans and predicting medical outcomes.

A policy brief issued by the World Health Organization warns that when these systems rely on data skewed toward younger populations, they can “systematically discriminate on a much larger scale than biased individuals.” The authors note that AI tools might miss symptoms, delay diagnoses or reinforce disparities in care for older adults — simply because they weren’t designed to recognize what aging looks like in the data.

The consequences extend well beyond health care. In the workplace, AI is rapidly reshaping hiring and skills expectations. Nearly one in four U.S. tech job postings sought candidates with artificial intelligence skills, according to job-listing data. Yet, older workers are being left behind, not due to their capabilities, but rather due to perception.

A survey by the nonprofit Generation found that just 32% of U.S. employers said they would “likely” consider candidates age 60 and older for roles involving AI tools, compared with 90% who would consider applicants under age 35. Yet, when those same hiring managers were asked to assess the performance of midcareer and older workers already on their teams, 89% said these employees performed as well as, if not better than, their younger peers.

When those biases shape who builds and trains AI, the result could be technology that’s less accurate, less inclusive and less effective for everyone.

The case for inclusion: why AI needs older adults

The stereotype that older adults are tech-averse doesn’t hold up. AARP reports that generative AI use among Americans age 50 and older doubled in 2024, from 9% to 18%, and another 30% express excitement about its potential.

Workplace adoption is rising, too. According to Generation, 15% of midcareer and older workers already use AI tools regularly, most as self-taught “power users” who turn to them multiple times a week.

“The growth in AI adoption suggests it’s becoming more relevant to older adults,” says Kakulla.

Advocates argue that including older adults in AI development can lead to more functional, ethical and widely usable tools.

This can mean building age-diverse teams in which mid- and late-career professionals help identify blind spots; ensuring training data reflects aging populations, not just digital natives; and creating AI oversight roles that draw on the experience and judgment that only decades in the workforce can provide.

Kakulla also emphasizes, “Tech companies need to account for diversity across the entire life stage, and design for the life stage.” She points to translation tools, popular among older adults, as a good example: The same AI feature could: help someone in their 50s while traveling; support speech-to-text needs in their 70s; and aid communication with a caregiver in their 80s.

Ultimately, what AI becomes depends on who trains and guides it. To ignore older adults in that process is to repeat one of humanity’s most enduring mistakes: Devaluing wisdom until it’s too late.

As Benjamin Franklin once put it: “Life’s tragedy is that we get old too soon and wise too late.”

It’d be wise not to program that tragedy into our machines.

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It's that last one that is the focus of this article. Given AI's ability to analyze massive amounts of data in a very short amount of time — a feature that requires an enormous amount of energy — the technology is a natural fit for investors, traders, asset management firms and the like.

As an example, most banks and brokers now offer robo-adviser accounts, which use AI to build and manage investment portfolios at a much lower cost than those maintained by actual people. (Still, financial planning should likely be left to the humans.)

As for those do-it-yourself (DIY) investors, there are a seemingly endless number of stock-picking platforms such as Danelfin that use AI to spit out lists of the top stocks matching their specific criteria.

I decided to test AI's predictive capabilities, and, on April 30, I asked Google's Gemini AI chatbot where I should invest in May. I also asked for a list of the best stocks to buy for the month.

Here's what it had to say and how its predictions matched actual market movement. All returns are through the May 30 close.

Where to invest

When I asked Gemini where to invest in May, it offered several suggestions of "potential areas to explore," including the technology sector and "select growth stocks."

Companies in the technology sector, specifically those focused on artificial intelligence (AI), "continue to show strong growth potential," Gemini said.

The chatbot also advised to "keep an eye on companies with strong growth momentum," such as Amazon.com (AMZN), which "appears to be a high-quality growth stock with potential."

The stock market closed out May with strong gains as investors cheered positive developments in President Donald Trump's tariff policies, though tensions between the United States and China appear to be on the rise heading into June.

For the month, the tech-heavy Nasdaq Composite emerged as the clear winner — rising 9.6% vs the blue chip Dow Jones Industrial Average's 3.9% gain and the broader S&P 500's 6.2% return.

Growth stocks, as measured by the S&P 500 Growth Index, did well in May, returning more than 9%.

As for Amazon, it finished the month up 11.2%. Truist Securities analyst Youssef Squali sees even more upside for the Dow Jones stock, as evidenced by his $226 price target — 10% above current levels.

"The potential for higher prices from tariffs remains a risk, but Amazon is better positioned than most to weather the storm" thanks to "the marketplace nature of its business model, its expansive scale, its superior logistics network and the diversity of its offerings," Squali wrote in a May 23 note.

Best stocks to buy in May, according to AI

When I asked Gemini on April 30 what the best stocks to buy in May would be, it offered up several suggestions.

To start, it tapped Palantir Technologies (PLTR) as a growth stock "with potential." The chatbot said the company's AI-powered data analytics software "increasingly valuable for businesses and governments," which could lead to "strong revenue growth."

PLTR shares climbed 11.1% in May, outperforming the S&P 500's 6.2% return. Longer term, the AI stock is 74% higher for the year to date and is up more than fivefold in the past 12 months.

Albemarle (ALB) — a lithium producer — is another name that Gemini suggested could be one of the best stocks to buy in May.

"Albemarle's stock has been somewhat beaten down, but it offers a growing dividend and exposure to the electric vehicle market," the chatbot explained.

ALB shares were down 32% for the year to date heading into May and fell another 5% through the month.

Still, Argus Research analyst John Eade thinks the lithium stock is "materially undervalued based on ALB's size, global scale, low-cost operations, and asset portfolio." He thinks the shares are trading at an attractive entry point.

While the current trends in the lithium market are negatively impacting Albermarle's earnings, "the company's balance sheet is solid, and management is taking steps to reduce costs and conserve cash," he adds.

The bottom line on AI vs the stock market in May

Gemini notes that its recommendations are "for informational purposes only and should not be considered financial advice," which I appreciated.

It also reminded me of the risks involved with investing in the stock market, such as losing my money, and advised me to conduct my own due diligence and consider speaking with a financial adviser.

To be sure, I would never blindly invest in anything an AI chatbot recommended — and neither should you. Still, it's an interesting exercise to see how picks made by AI would perform throughout the month.

So much so that I'm doing it again for June. Check back next month to see how AI's stock picks fared. Hint: We're watching industrial stocks and Broadcom (AVGO).

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While robo-advisers and AI-driven strategies can optimize investments, they cannot replace the tailored, long-term planning strategy by human retirement planners with real-world experience needed for long-term financial success and a well-funded retirement.

People need a custom-built financial plan across five critical areas — investment risk, income, health care, taxes and estate planning — that aligns with personal goals and risk tolerance when life changes. Human retirement planners are better equipped than AI to handle the nuances and numerous moving parts of a retirement plan.

The Kiplinger Building Wealth program handpicks financial advisers and business owners from around the world to share retirement, estate planning and tax strategies to preserve and grow your wealth. These experts, who never pay for inclusion on the site, include professional wealth managers, fiduciary financial planners, CPAs and lawyers. Most of them have certifications including CFP®, ChFC®, IAR, AIF®, CDFA® and more, and their stellar records can be checked through the SEC or FINRA.

As Stephen Covey said, "Begin with the end in mind." A strong financial plan that you understand and checks all five critical areas listed above is the best way to set yourself up for success to reach your financial goals.

Start where you are

It’s crucial to start where you are today and plan for the retirement you want to achieve — and a retirement planner with real-life experience is the best way to help you get there.

The importance of working with a retirement planner rather than relying on AI is highlighted in the distribution phase, or what we call “Phase II.”

You’re retired at that point. The paychecks stop coming, and you rely on assets to support you. You face major changes across the board, in taxes, investment planning, estate planning, health care, Medicare, Social Security, etc.

You have too much at stake to let AI take control of every aspect of your retirement plan, especially when market corrections midway through retirement are practically inevitable.

Here are some areas of retirement planning in which AI falls short:

It leaves some missing pieces

AI cannot anticipate complex tax strategies, estate planning needs or long-term care costs — key factors that affect wealth over time.

A financial plan must integrate all these elements.

It relies on set-it-and-forget-it investing

AI offers algorithmic rebalancing and investment suggestions, but blind trust in algorithms can lead to missed opportunities, unexpected tax burdens and lack of preparedness for economic shifts.

It fails to bridge the emotional and behavioral gap

AI lacks the ability to coach people through emotional elements such as market downturns, major life events or personal financial decisions that require a human touch and strategic adjustments. In these cases, people need personalized service and a problem-solver they can relate to.

A retirement planner factors in your circumstances and values, placing relationship-first planning over rule-based automation. A trusting relationship built between planner and client is especially valuable when financial adversity hits.

It can't talk back

True financial security comes from understanding your financial plan and ensuring it is adaptable, not just automated. AI can assist, but individuals must take ownership of their financial future.

A big part of the planner-client relationship is being able to have hard conversations to understand what the client wants and integrate those goals.

Looking for expert tips to grow and preserve your wealth? Sign up for Building Wealth, our free, twice-weekly newsletter.

AI’s impact on many industries can’t be overstated, but in the financial industry, the role of advisers remains irreplaceable. Their expertise, empathy and overall experience enable them to provide direction over the long term and identify alternatives when adjustments are necessary.

Retirement financial planners help their clients through all kinds of life events and, along with managing the five moving parts of retirement, give sound advice and provide clients with an emotional safe space. Such an all-around, holistic approach cannot be duplicated by AI.

At best, AI can provide technological supplements to the real plan, but not all the plan’s components or, most importantly, the human connection.

Dan Dunkin contributed to this article.

Appearances on Kiplinger.com were obtained through a paid public relations program. The columnist received assistance from a public relations firm in preparing this piece for submission to Kiplinger.com. Kiplinger was not compensated in any way.

The Retirement Solution is an investment adviser registered under the Investment Advisers Act of 1940. Registration as an investment adviser does not imply any level of skill or training. For more information please visit: adviserinfo.sec.gov and search for our firm name. DA-003101.2

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This article was written by and presents the views of our contributing adviser, not the Kiplinger editorial staff. You can check adviser records with the SEC or with FINRA.

AI generally refers to computers and software that perform tasks normally done by humans or that exhibit human-like intelligence to do things such as learn, reason or act. AI can be used to process large amounts of data, identify patterns and provide recommendations.

"The goal of AI," according to a useful primer by Stanford University's IT department, "is to develop machines that can operate independently, adapt to new situations, and improve over time, ultimately enhancing efficiency and productivity across various domains, from healthcare to finance to transportation."

Still, there isn't one agreed upon definition of AI, which sometimes leads to confusion. It also makes regulating AI trickier, since a definition needs to be pinned down to avoid unintended consequences. For example, a broad definition of AI could cover simple spreadsheet software, like Microsoft Excel.

And while "AI" as a talking point exploded recently with the launch of generative AI, the technology has been around for years. In fact, AI technology has already long been part of daily life, used for email spam filtering, language translation, music recommendations, credit card fraud detection, wireless communications and much more.

As AI tools start working and become commonplace, they often fade into the background, becoming just another app or piece of software. So, what's changed recently, and what should you know about it? The most revolutionary update is the availability of generative AI.

What is generative AI?

Generative AI is a specific type of AI that creates content, including text, images, video and audio.

The major tech advance exploded onto the scene in November 2022, when start-up OpenAI released its AI chatbot ChatGPT to the public. Many users were amazed at how the online tool could rapidly churn out a limerick or provide detailed answers to complex questions.

Generative AI can be a general-purpose AI with a wide range of knowledge, contrasted to AI that can do narrow or specific tasks. Users don’t need any technical know-how to get started, which many experts say is a key breakthrough, since it opens the floodgates to rapid adoption.

To use generative AI, users simply type commands in plain English. These so-called prompts give the AI chatbot and other tools all they need to start creating. Don’t like the results at first? You can continuously refine the results with additional notes and questions. Anyone who has used internet search or an online messaging tool can quickly grasp an AI chatbot.

The technology behind generative AI

Generative AI stems from AI systems known as large language models (LLMs), which are trained on massive amounts of data, such as the text of websites, with vast amounts of computer power. These models learn patterns in language to predict the next word. The results are often startling, from in-depth research reports to data crunching, often done in seconds.

LLMs can be trained on images and video, too, to create tools that generate photos, Hollywood-like movies or 3D games. Another top use is debugging and generating computer code, a task many companies are unleashing to their computer programmers.

Tech giants Alphabet (GOOG), Amazon (AMZN), Microsoft (MSFT) and Meta (META) are spending astronomical sums to build huge AI data centers, mostly powered by Nvidia (NVDA) chips, to train and run internal AI models and host AI cloud computing for customers. Many in the tech industry consider generative AI the next big tech platform, a major transition similar to, or perhaps even more important than, the shift from PCs to mobile phones.

Generative AI takes huge amounts of computing power, and electricity, to work. And tech giants are spending so much so fast, some analysts worry about overspending.

Is AI good or bad?

AI, on its own, is neither. It's better to think of it as a powerful tool, like other advanced technologies.

Put into action, AI brings huge benefits and, yes, plenty of risks. Good or bad outcomes come from how humans and society decide to use powerful AI and what guardrails are put in place.

The emergence of generative AI has sparked a new excitement around the potential for good, along with new fears over AI safety.

Consider the potential for AI to boost economic growth, aid scientific discovery and improve public health. Generative AI tools are already helping businesses write emails, summarize documents, create presentations and analyze company data. Small businesses can create slick online video ads without needing any technical expertise. There is a growing list of positive uses of AI in medicine, including sequencing protein structures, analyzing medical images and transcribing doctor visits.

AI apps can help organize family calendars and manage household chores. Or even do the shopping for you, with the emergence of AI agents. There are AI voice assistants, tutors and personal trainers.

Traditional AI brings a range of risks, including the potential for bias or threats related to privacy and security. But generative AI brings at least a dozen new risks unique to the underlying tech. For example, AI chatbots can produce false content, known as hallucinations. These falsehoods can seem authoritative and even come with detailed, but fake, citations.

Generative AI can leak private data, offer dangerous or violent recommendations or infringe on intellectual property. AI chatbots can be tricked into spilling a company's or AI model’s internal secrets, even if they are designed not to. Companies building AI tools are well aware of these risks and trying to find ways to mitigate them, especially for high-risk settings, such as in the military.

Criminals and foreign actors can use generative AI as a low-cost tool to mass produce online spam content or email phishing scams – or for creating propaganda and misinformation in huge volumes cheaply.

In many conversations, the bad aspects of AI often swamp the good. But it’s worth keeping in mind the huge potential of AI to improve society, just as great technological shifts of the past have.

Can I use AI for free?

Yes, plenty of chatbots are free, including tools from OpenAI, Meta, Anthropic and Google. Free chatbots come with limitations, though, such as limits on daily usage. Web search from Google now includes expanded AI answers, while AI web search start-up Perplexity offers free AI results.

You may already use generative AI without knowing it, since the tech is quickly being integrated into popular social media and messaging apps, such as Facebook, Instagram, WhatsApp and X. Meta says it already has 1 billion active AI users, since it's building AI into its apps' search tools. Meta is also releasing a standalone, free AI app.

Consumers are finding AI integrated into their smartphones and PCs, too. Users can get real-time translation of foreign languages during phone calls or text messaging, or have long articles or email chains summarized in a few easy-to-read bullet points.

Paid chatbots and other tools have more features, work faster and can provide better responses, along with fewer or no restrictions on use. More and more businesses are adopting paid tools for workforces to organize email, transcribe meetings, analyze data, create marketing copy, do research and much more.

Pricing varies. OpenAI's ChatGPT has a "Plus" version for $20 per month and a "Pro" version for $200 per month. Anthropic's Claude has plans that run $17 per month and $100 per month. Microsoft's Copilot Pro costs $20 per user per month.

How is AI used in finance?

Like other industries such as medicine and retail, there is a growing list of practical uses of AI in finance. Financial services companies are using it to process customer calls, fight financial fraud, create personalized marketing material, forecast sales, interpret regulations, understand tax law and more.

Bank of America, for example, says 90% of its employees use AI to help with IT issues, health benefits and other employee questions. The company also uses it to help with client questions, summarize research and prepare meeting materials. And its AI customer assistant, Erica, has been used more than 2.5 billion times.

Nearly half of consumers have or are considering using generative AI tools for personal finances, according to a survey by Experian last year. Two-thirds of Gen Zers and millennials are using the tech to manage their finances. Thirty-eight percent of those surveyed said they trusted generative AI as much or more than human advisers. The popular investing app Robinhood will launch an AI virtual assistant this year to subscribers on the Gold $5 per month plan.

Don't be shocked if you find out your personal financial adviser is using generative AI. The CFP Board, a trusted organization for financial planners, published a guide on generative AI earlier this year for Certified Financial Planners.

The guide addresses ethical issues and notes that generative AI can be used for a range of tasks, such as summarizing client meeting notes, conducting initial research and refining marketing materials. But it also highlights that generative AI can produce inaccurate information and that financial advisers are responsible for the final work product.

Because AI chatbots are growing in popularity, it’s no surprise that people are using AI to pick stocks. When it comes to personal finances, be wary of giving away sensitive financial information to AI chatbots and look out for inaccuracies. It still pays to have trusted sources and human judgment.

Learn More About AI

• How AI Can Be Used in Investing
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Here are five futuristic car technologies that are no longer reserved for luxury models and are becoming increasingly common on the road today.

1. Self-driving car technology

The concept of self-driving cars goes back to the 1920s.

Former U.S. Army electrical engineer Francis P. Houdina invented a radio-controlled car using a 1926 Chandler. Radio signals operated the car's motor and steering, while a second vehicle followed behind, transmitting the commands that guided the Chandler's movements.

We suspect that if Houdina were alive today, he'd be amazed to see how far things have come.

California-based Waymo is one of the first autonomous ride-sharing services. After conducting millions of miles of road testing and even more hours of simulation, the service offers a dependable and safe way to get around without you having to press your foot on the gas, steer, even make small talk with a driver.

Before introducing the service to a new city, the Waymo Driver takes in every detail, from signs and crosswalks to road orientation. Instead of using GPS to navigate, Waymo uses detailed, customized maps, artificial intelligence (AI) and real-time sensor data to ensure your ride is safe.

One of the biggest concerns with self-driving cars isn't the actual car, but other drivers on the road. Predicting the unpredictable can be next to impossible, but Waymo has found a way to make it work. It uses data gained from testing to predict how other drivers, pedestrians and other road obstacles will move. It factors in all possible paths in real time to avoid hazards and get you to your destination safely.

Currently, Waymo is only available in Phoenix, San Francisco, Austin and Los Angeles, with future launches slated in Miami and Atlanta. If you live in one of these cities, you can download the Waymo app and experience the future today. Pricing is similar to other rideshare apps and the service is slick and efficient, as you might expect from a robotaxi.

Other technology companies are rapidly moving into this space. Hyundai has recently announced a partnership with Avride to make its own fleet of robotaxis, and Elon Musk has announced that the first Tesla robocars will launch in June 2025 in Texas.

Driver assistance features in your car
Car manufacturers, meanwhile, are perfecting their own versions of advanced driver-assistance features — such as lane centering and hands-free highway driving — across more models and trim levels.

Ford BlueCruise is a driver-assistance feature that can steer, brake and accelerate while you enjoy your drive hands-free. Other car manufacturers such as General Motors, Tesla and BMW also have installed similar driver-assistance technologies.

All this shows that while self-driving cars — and the related technological advancements — are the future, you'll be able to experience it sooner than you think.

2. Biometric car keys

Keys? Those are a thing of the past. But soon, key fobs might be gone.

For example, the 2025 Hyundai Genesis GV60 allows you to unlock your car with your face. All you need to do is touch the handle to activate the door-mounted camera, show the camera your pearly whites, and the door opens for you.

It doesn't stop there. Once you're inside the spacious and stylish cabin, you can start your vehicle using fingerprint authentication.

Hyundai isn't the only manufacturer offering this technology. Tesla has used biometrics for years. Their Model 3 and Model Y have a facial recognition camera that recognizes who's driving and sets preferences, such as seat location, cabin temperature and more.

Meanwhile, Subaru's DriverFocus uses an infrared camera to recognize and set driver preferences. It can also determine when a driver is distracted and alert them. It won't be long before more cars have this accessibility.

3. EV range choice, at last.

One of the biggest car innovations concerns the EV market. Unveiled at the 2025 New York auto show, the 2026 Kia EV4 is a perfect example of how far electric vehicles have evolved.

"The 2026 Kia EV4 has two battery capacities, one that will run 300+ miles and another that will be in the 225 to 250 mile range," says Brian Moody, an executive editor with Autotrader. "A smaller range makes sense when the price is right."

This smaller range is in line with other EV models available now, which have average ranges of 235 to 300 miles per charge. What makes this so noteworthy is the fact that you, the customer, can choose. Unlike the Tesla Model 3, which comes with one battery option, the EV4 offers customers a choice of battery size, and the lower-range battery option comes at a lower-price entry point.

Along with flexibility in range choices, Kia expedites charging batteries. DC quick-charging takes you from 10% to 80% in 29 minutes with the light battery and 31 minutes for the Wind & GT-Line battery, with a 400V dedicated platform for EVs.

That's competitive, but generally slower than Tesla's superchargers, which can give their vehicles 150 to 200 miles of juice in 15 to 30 minutes. While Tesla currently leads in ultra-fast charging speeds, Kia is narrowing the gap. Expect to see more manufacturers offering different battery options for their EV models, giving customers more affordable entry points into the market.

4. Adaptive technologies

To get the best safety and technology features, you'd usually have to shell out some serious dough for an upgraded package, which "can cost between $2,500 to $5,000, and in some cases, up to $10,000," says Moody.

Adaptive technologies run the gamut from cruise control, hazard detection and accident prevention (applying emergency braking when hazards or pedestrians are detected.)

Subaru is one of the manufacturers bringing more of these features to more of its vehicles. One example is the installation of EyeSight on their manual sports cars.

Eyesight uses two front-facing cameras to scan the road for obstacles, pedestrians or anything else it deems a hazard. If it detects a hazard, the EyeSight technology can lower your car's cruise control speed or apply emergency braking.

Subaru's approach to offering more adaptive technologies in more models could signify a shift that other manufacturers follow, meaning you could have more top-of-the-line safety features without having to pay an upgrade fee.

Another nifty feature is AI voice assistants. Kia uses the SoundHound AI assistant, which they dub the "digital co-pilot" for your adventures. You can use the AI assistant to power certain car functions such as playing music, adjusting cabin temperature or getting directions.

As adaptive technologies grow and use more AI, you'll start seeing these features in more vehicles, even in base and midrange options.

5. AI-powered predictive maintenance

Modern cars now come with a wealth of technological features to help you stay informed about your car’s health and performance.

For example, General Motors uses OnStar, which sends drivers a vehicle condition report every month. This report uses an easy-to-understand color code to flag key systems such as brakes, oil life, engine performance, transmission and tire pressure.

Any area designated in green means the part is in good shape. Yellow indicates you'll need service soon, while red requires prompt attention.

OnStar will also notify you when you need to bring your car in for service and can help you locate the nearest dealer. In 2025, all General Motors models come equipped with OnStar Basics, including Chevy, Buick and GMC.

While some vehicle manufacturers have had such features for a while, artificial intelligence (AI) is now taking vehicle maintenance to the next level.

AI predictive maintenance analyzes a range of data, including recalls, to determine if or when future problems could arise. It can predict when car parts will fail and alert you beforehand, so you can address problems before your vehicle breaks down.

Along with using historical data, AI analyzes real-time information gained from a vehicle's sensors to monitor engine, transmission, braking, steering and other performance components. This allows for more accurate diagnostics and timely alerts.

Altogether, AI can help properly diagnose any issues, or future issues, accurately — and it's more cost-efficient than traditional scheduled (or reactive) maintenance. Having this extra monitor not only makes your vehicle safer, it can extend its operating life, as well.

The bottom line

Car features have come a long way from rearview cameras. Features that once seemed futuristic, such as self-driving and adaptive technologies, are becoming more accessible every year.

EVs are also getting into the mix. Brands such as Kia are providing more ranges in their EV models to accommodate a growing base of prospective buyers, while biometric features help you start your vehicle with the push of a button.

As these innovations spread, they'll make even the most mundane commutes safer and more enjoyable.

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Insufficient electricity, Nvidia chip shortages and tech advances hitting roadblocks are some of the potential factors that could slow down AI development. Now there’s a bigger worry: The states and how they regulate AI.

There have been hundreds of AI bills introduced in the states this year alone. These include transparency rules, consumer protections, inspections of top AI models for compliance, and efforts to promote AI adoption. Colorado was a first-mover, passing a comprehensive AI law last year that covers high-risk AI systems, discrimination and transparency.

That’s prompted an unusual idea on Capitol Hill: Block states from regulating AI for the next decade. A recent draft of the emerging Republican tax and spending bill includes the decade-long restriction, with an expansive definition of AI and few exceptions. One of the main carve-outs is allowing states to pass laws that promote AI use and adoption.

The proposal sets the stage for a fierce debate this year and beyond, even though that specific proposal is not likely to make it into law anytime soon. A moratorium would prevent states from enacting or enforcing AI-specific bills related to chatbots, social media, deepfakes, medical software and much more. Advocates for the pause say AI harms can be addressed with other state laws related to unfair or deceptive practices, consumer privacy, discrimination and more.

Many Republicans, technologists and analysts argue the U.S is at risk of choking innovation in the nascent field of generative AI. “The United States is hurtling toward a fragmented web of conflicting rules that create uncertainty, raise costs, and stifle innovation,” Hodan Omaar, senior policy manager at the Information Technology and Innovation Foundation, a Washington, D.C.-based think tank, said in a statement. Even Colorado Governor Jared Polis, a Democrat, now favors a federal moratorium, saying the state’s law, which he signed, went too far.

Preempting state laws is nothing new for Congress and is a familiar proposal in tech policy. But doing so without a federal framework in place is a novel idea in recent times and speaks to how quickly AI is being adopted.

A moratorium provides time to write federal rules, but it’s not clear when that would happen. “In the absence of federal protections, the proposal to block state and local action on AI for the next 10 years places the development, deployment, and use of AI into a lawless and unaccountable zone,” says Travis Hall, director for state engagement at the Center for Democracy & Technology (CDT), a Washington, D.C.-based nonprofit focused on digital rights.

Some analysts point to the 1990s when federal laws preempted state internet regulations to encourage growth of the emerging technology.

Bipartisan agreement is likely needed to halt the patchwork of state laws, but it’s hard to see the two parties compromising anytime soon. There’s no shortage of federal AI bills, including legislation calling for new studies, standards for disclosure and more R&D funding, with more bills on the way.

That means that tech companies, and their investors, are facing a tangled web of state regulations and compliance, which could drag on for years.

A similar state of limbo happened with state privacy laws. California’s sweeping privacy law prompted a big push for federal privacy rules that would preempt the rising patchwork of state laws. California’s law has been in effect for five years and there’s still no federal legislation in sight.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Meanwhile, mega-cap tech stocks such as Apple (AAPL), Amazon.com (AMZN) and Google parent Alphabet (GOOGL) are all in the red since January 1 despite being go-to leaders over the last few years.

As the old saying goes, however, past performance is no indicator of future returns.

We could very well see old Silicon Valley favorites rise again – or, on the other hand, we could see the market stumble across the board as other companies start to underperform, too.

But for trend-following investors who believe current momentum sets the tone for what's next, it's worth watching the following five momentum standouts that have skyrocketed in 2025 and stand apart from the rest of Wall Street.

Each has a unique business model driving its success as well as unique risks to continued growth.

All are momentum stocks that are valued at more than $800 million to prove a measure of stability. And all have more than doubled since where they were trading in December, though some have surrendered some gains amid this year's volatility, including a significant stock market sell-off.

Here are five momentum stocks that have posted impressive gains in a tough year and are well-positioned for more upside from here.

Data is as of May 21.

• Market value: $1.3 billion
• Sector: Health care
• YTD return: 120.3%

Grail (GRAL, $37.45) is a cutting-edge medical firm working on the next generation of cancer diagnostics tools that will allow doctors to identify at-risk patients early on and in minimally invasive ways.

This could be a game-changer on multiple levels: improving outcomes, keeping the total cost of care in check and, ultimately, fighting back against deadly cancers around the world.

Grail's goals are praiseworthy, but its corporate history is not without its challenges, including a little bit of geopolitical controversy.

The company was founded within parent firm Illumina (ILMN) before being spun off in 2016. It was reacquired in 2021 and divested again in 2024 after a battle with European regulators.

Uncertainty put a damper on long-term strategy and caused volatility in the share price. But the stock is up 188% from its June spinoff.

That includes a 120% run since January 1 thanks to news that its Galleri blood test will see sales jump as much as 30% this fiscal year to deliver on its long-term growth prospects.

Innovative development-stage health care stocks are always risky, since a bad result from FDA reviews and patient trials could drive the company to zero almost overnight.

But, from what we've seen, GRAL is a momentum stock with a lot of promise that seems to be delivering in 2025 and beyond.

• Market value: $13.0 billion
• Sector: Consumer defensive
• YTD return: 153.1%

Hims & Hers Health (HIMS, $) is a mid-cap telehealth company that takes some of the embarrassment out of confronting personal issues like hair loss and sexual performance through virtual visits and mail-order treatments.

It offers a range of health and wellness services including mental health visits and consultation on prescription medications as well as recurring fulfillment on those drugs.

Beyond its prescription operations and licensed healthcare staff, HIMS also offers a host of over-the-counter products and cosmetics including vitamin supplements and skincare treatments to ensure its customers are doing their "self care" the right way.

This one-two punch of serving two fast-growing marketplaces with minimal overhead has fueled an amazing revenue surge of almost 70% in fiscal 2024, with projections for more than 40% growth in fiscal 2025.

It's no surprise this momentum stock is also up dramatically.

And, lest you think this is just a low-cost leader chasing market share at a loss, HIMS is comfortably profitable and projecting better earnings this year – four times better, in fact.

Full-year earnings are set to leap from 22 cents per share to more than 80 cents, according to the latest forecasts.

• Market value: $24.9 billion
• Sector: Technology
• YTD return: 40.3%

Super Micro Computer (SMCI, $41.63) was founded way back in 1993. The company helped build the early backbone of the internet through server sales and support. It remains one of the largest producers of high-performance servers and data-storage infrastructure in the world.

And, in the age of data-intensive artificial intelligence as well as data-hungry cloud computing services, SMCI hardware is in demand more than ever.

Super Micro Computer hit a bit of a roadblock last year, delaying its annual report due to accounting issues and being de-listed from the flagship Nasdaq-100 index as a result.

But SMCI stock surged in January and into February on news it would meet its deadline to file a revised report – as well as on hope the results would meet Wall Street estimates.

That includes a fiscal 2025 forecast of 60% revenue growth and expectations the stock will rejoin major tech indexes and re-attract institutional buyers.

As a result of these developments, this momentum stock surged as much as 97.7% as of February 19. SMCI has been volatile since then but continues to stand apart from the broader market this year.

• Market value: $10.1 billion
• Sector: Health care
• YTD return: 84.9%

If you've been chasing AI stocks over the last year, you know all too well it's easy to arrive late for the biggest moves after other investors crowd in first.

But Tempus AI (TEM, $58.23) is one of the late-bloomers in the space, getting a huge boost only recently thanks to a new software service and insider buying activity.

Specifically, the health care AI company unveiled new functionality in its generative AI assistant, Tempus One, which helps physicians and researchers assess clinical data and bring new drugs to market faster.

Precision oncology treatments are now the norm, as no form of cancer responds the same way even if patients present similar charts.

With many oncologists and primary care physicians too busy or overwhelmed with data to tailor treatments, Tempus One offers breakthrough capabilities to make sense of unstructured data.

Tempus AI is still unprofitable. But, thanks in part to Tempus One, management forecast nearly 80% revenue growth in its next fiscal year.

And TEM has attracted the attention of former Speaker of the House Nancy Pelosi, who disclosed a major purchase of call options in the stock.

The "smart money" seems to like what it sees in this AI play, and the momentum stock has put up tremendous returns as a result.

• Market value: $832.5 billion
• Sector: Consumer discretionary
• YTD return: 416.5%

The fashion industry doesn't know how to take a break during a recession. Sales of expensive clothes and luxury goods historically remain quite durable even if other discretionary categories see rollbacks.

ThredUp (TDUP, $7.04) is capitalizing on this long-term trend through an innovative "virtual thrift shop."

This isn't like searching through the racks at your local Goodwill or surfing unwearable bargain items on eBay (EBAY). ThredUp is the go-to destination for more than 50,000 brands, from The Gap to Gucci. And the bargain-conscious can sometimes find high-end deals at 90% off the former retail price.

There is a counter-cyclical element to the ThredUp business model, as hard times leave people less willing to pay full price (even if they maintain their distinct tastes).

So TDUP stock can stand up in a spending downturn. And when times are good, as they have been in recent years, the sky is the limit on how much it can grow.

The retailer is expected to record roughly double-digit revenue growth for the fourth quarter. More importantly, management expects to see significant improvement in margins as it moves towards profitability.

There is risk here, as selling apparel isn't exactly a business with a wide moat. But ThredUp continues to connect with both buyers and sellers.

And this momentum stock may have a value proposition that lasts as it expands its digital footprint.

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In past years, schools have raced to adopt smartboards, laptops and learning apps. Now, artificial intelligence is the latest tech craze inspiring high hopes of improving education.

AI teacher training
Already, most teachers are being provided AI training, according to recent research by the RAND Corporation. Three-quarters of K-12 districts will have provided training on AI use by this fall, though the training varies widely and is most often optional. But not dealing with AI isn’t an option as students increasingly use AI tools, such as ChatGPT, on their own for homework and research, and the issue of AI plagiarism gets worse.

Cue a new White House initiative that aims to give K-12 students basic AI competency and to train teachers on best practices. The executive order includes a nationwide competition to highlight top AI uses, a push for public-private partnerships, and new federal funding for AI projects. There will also be a focus on apprenticeships and career options for high schoolers. The goal is to “ensure the U.S. remains a global leader in this technological revolution.”

The new federal effort aims to address one of the big current roadblocks. There is “a scarcity of external experts who are capable of providing appropriate training” for teachers, RAND found. One school leader told RAND that AI best practices simply don’t exist yet: “There are people that are claiming to have the best practices and are making money hand over fist.” The executive order aims to establish comprehensive AI teacher training and professional development.

Pushback from schools and parents
It will be a huge challenge to improve education outcomes with AI, though, as schools are tasked with adding AI in all subjects to students as young as kindergartners. Many schools are struggling to lift test scores back to pre-pandemic levels, and the adoption of AI is sure to be rocky.

Pushback from teachers and parents will be common, with worries about the risks of generative AI and the potential of it hindering learning. AI adoption could come into tension with the push to get smartphones and screens out of classrooms so kids can focus. Plus, measuring AI’s effect on educational outcomes could take years and will require careful tracking and data collection.

But there are lots of potential benefits of AI: Students can get a personalized, conversational tutor. Teachers can get help with administrative tasks, training and curriculum creation. And students graduate with in-demand AI know-how.

Education tech
The trend will open the floodgates to spending on AI education tech. There will be a shift of federal education funding and grants to all sorts of AI efforts, prompted by the recent White House action. Private organizations are likely to spend big on new AI initiatives. Meanwhile, states and local districts will budget more for AI tech. Expect some states to go all-in, while others go slow.

The new AI investment will go to large companies, such as Microsoft and Google; AI labs, such as OpenAI and Anthropic; and a range of edtech players and other start-ups.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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Several highly anticipated upcoming IPOs have hit the brakes. StubHub, a ticketing marketplace, has shelved its plans, while Klarna – a buy-now-pay-later platform – continues to delay its long-anticipated debut. Both were widely believed to be ready to launch their IPOs in April.

Chime, a well-known fintech player, and Hinge Health, a digital health startup, have also opted to wait to go public.

If this feels familiar, that's because it is. IPO volumes have been underwhelming for the better part of the past three years.

In 2022, just 71 companies went public, raising a mere $7.7 billion, according to Renaissance Capital, which is a provider of pre-IPO research and IPO-focused ETFs.

Activity picked up in 2023 with 150 deals totaling $29.6 billion. But that still paled in comparison to the IPO boom of 2021, which saw 397 offerings raise a staggering $142.4 billion. Even in 2020, amid pandemic uncertainty, there were 221 initial public offerings for $78.2 billion.

In 2025, only 70 offerings have raised $9.9 billion. That's barely on pace with last year.

So what's happening? And when might the IPO market get back on track?

Volatility, valuation concerns keep IPOs on ice

The U.S. IPO market remains mired in uncertainty. Much of the recent chill stems from renewed global trade tensions – specifically, President Donald Trump's "Liberation Day" tariffs that were announced on April 2, which sparked retaliatory moves and reignited fears of a broader trade war.

This uncertainty, coupled with a sell-off in tech stocks and increasing market volatility, has made pricing new offerings a major challenge.

"There was a pretty clear shift in IPO sentiment after the tariff announcements, which introduced a lot of uncertainty into the market," says Avery Marquez, director of investment strategies at Renaissance Capital.

"Volatility can be a strong headwind for new issuance, even when investor sentiment and risk appetite are robust. But this came while the trading environment was already somewhat weak in the wake of the mid-Q1 sell-off," Marquez adds.

Beyond tariffs, macroeconomic pressures – including inflation, higher interest rates and geopolitical instability – have spooked investors.

Given the cloudy outlook, major public companies such as Ford Motors (F), General Motors (GM), United Airlines (UAL), Mattel (MAT) and UPS (UPS) have scaled back or withdrawn their financial guidance.

It's no wonder, then, that executives at IPO-bound firms are also treading carefully.

Meanwhile, some of the most promising startups, especially in AI, are opting to stay private longer. OpenAI's $40 billion raise at a $300 billion valuation is just one example of a company flush with cash that sees little reason to brave the public markets at the moment.

"Today's founders have a far wider array of financing options available to them," said David Spreng, chairman, founder and CEO of Runway Growth Capital.

Expansion in the private credit and venture debt markets allows private companies with solid fundamentals to get the capital they need, Spreng adds. "Rather than rush toward an IPO, many late- and growth-stage businesses are choosing to stay private longer, using minimally dilutive debt to extend their runway, strengthen their businesses and preserve ownership."

Are there signs of a thaw?

Still, there are glimmers of optimism that activity in the IPO market is starting to pick back up.

The Renaissance IPO ETF (IPO) share price has recovered to levels not seen since early February, reflecting a modest revival in investor interest.

The Cboe Volatility Index (VIX), a measure of "fear" in the stock market, has also eased off recent highs, suggesting a slight calming of investors' nerves.

And new deals are happening, albeit selectively. Two insurance firms, American Integrity (AII) and Aspen Insurance (AHL) went public in early May and collectively raised more than $500 million.

And while the CoreWeave IPO – a provider of infrastructure for AI developers – underwhelmed at first, the stock has since climbed above its IPO price, a positive sign for others waiting in the wings.

Market watchers believe that when IPO activity resumes in earnest, it will center on well-established, cash-flow-positive businesses in resilient sectors – think defense and artificial intelligence (AI).

Ultimately, the IPO market tends to rebound faster than expected once conditions improve. The key will be less about chasing the next unicorn and more about rewarding strong fundamentals. Until then, companies and investors alike are playing a cautious, wait-and-see game.

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The tech industry is buzzing about AI agents. Part of the excitement stems from the distinctive, and almost human, way some of them work: They “see” your screen.

Microsoft recently unveiled a way to build an AI agent that “follows a loop of seeing, thinking, and doing,” says Sangya Singh, VP of Power Platform Intelligent Automations at Microsoft. The process goes something like this: An agent uses AI vision to look at the screen, capturing screenshots and interpreting the pixels, so it can navigate a computer desktop or web browser, including buttons, forms and web pages, says Singh.

It’s powered by large language models, the systems at the core of generative AI. Microsoft uses an OpenAI model, which the Microsoft-backed start-up says is “a universal interface for AI to interact with the digital world.”

The AI agent controls a virtual mouse and keyboard, using AI reasoning to navigate a computer just like a human would. “It acts, by clicking, typing, or scrolling, until the task is done,” says Singh.

How does it know exactly what to do? A human gives it instructions in plain English.

This new AI tech offers a promising way to automate any computer task, without needing preprogrammed software or special protocols between apps. Current popular automation methods need to be preprogrammed and work best on tasks with rote steps. In contrast, these AI agents don’t need such programming and can work through various hurdles, such as a screen that looks different than normal or an intrusive pop-up message.

Using vision, this type of AI can take on incredibly complex tasks and navigate any apps or websites that it comes across. For consumers, AI agents could book a hotel, rent a car or buy a product online. At work, uses include data entry, market research and invoice processing, to save time and reduce human error. These examples are just the start of a seemingly endless list of digital tasks, many of which are already emerging.

Microsoft says “irreversible” decisions and “high-risk actions,” such as large financial transactions, will have an alert for human approval. Privacy will be a big concern as AI tools use credit card data and other personal information. There’s also the chance that AI could make mistakes. These issues are well known and safeguards are being put in place.

Note that using this type of generative AI can sometimes be an inefficient way to automate tasks, as it uses a lot of computing power, though it will get more efficient over time. Look for an explosion of AI agents in the coming year or so, using vision to navigate digital chores.

This forecast first appeared in The Kiplinger Letter, which has been running since 1923 and is a collection of concise weekly forecasts on business and economic trends, as well as what to expect from Washington, to help you understand what’s coming up to make the most of your investments and your money. Subscribe to The Kiplinger Letter.

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AI is particularly helpful if you need assistance with basic financial tasks and principles. Keep in mind, though, that for now, it can't match the advice of a human financial adviser.

Still, AI can be an excellent companion as you aim to keep up with the demands of modern society. Take a look at how you can use it.

1. Learn finance basics with AI

AI is not a personal finance expert, but one area where it can excel is in helping you learn the basics. It serves as an interactive companion that excels at explaining fundamental financial topics.

For instance, if you want to learn about budget categories or debt payoff strategies, AI chatbots like ChatGPT and Perplexity can take you through a crash course. You can also ask the chatbots to explain tools like mortgages, refinancing and different types of savings accounts.

But remember, an area where AI can fall short is in providing personalized advice. It can engage in a dialogue, but that isn't quite the same as working with a financial adviser.

A human adviser will ask for your complete financial picture, including your expenses, debts and income sources. If you don't disclose these to an AI — which you should not out of AI privacy concerns — it may not provide the best advice.

2. Manage your budget with AI

You may not have time to track every little expense and whether your budget is balanced, but AI can take the manual work out of budgeting. Companies already exist that use AI to give budgeting advice – and you might already be using it without realizing.

For example, Cleo is an AI chatbot with a sense of humor that can help you navigate your budget shortfalls. Rocket Money, a more traditional financial analysis app, utilizes artificial intelligence to analyze your budget and pinpoint areas for improvement.

The benefit of the best budgeting apps is that they can eliminate the need for manual tracking. They typically let you connect your financial accounts and automatically populate your income and expenses.

This allows you to quickly view a summary of your finances, including areas where you spend the most. Some might even offer suggestions on how to optimize your budget and spend less.

Another way people have used AI to manage budgets is by asking chatbots specific questions. For example, you can ask an AI-powered bot to build a grocery list that fits a certain weekly budget and dietary needs, or ask Perplexity to compare rates at local auto shops or dry cleaners. You should, however, review their responses as the technology is not perfect – yet.

3. Automate your investing with AI

Investing strategies are virtually unlimited, with endless suggestions on how to build a better portfolio and beat the market. And with nerves and emotions tied up in money, investing decisions can be reactionary, with people buying and selling stocks and other investments based on the day's news stories. Letting your emotions guide your investing decisions rarely produces the best outcomes.

AI can automate your investing strategy with tools like robo advisers. These use algorithms to optimize your portfolio according to your preferences, such as income and time until retirement. They typically charge a management fee, but they are often lower than the fees you would pay to work with a traditional wealth adviser.

While robo advisers utilize algorithms that are sometimes referred to as AI, this is distinct from the technology employed by chatbots like ChatGPT. AI chatbots utilize large language models (LLMs) to generate responses, while robo advisers employ proprietary algorithms that inform investment decisions.

Various robo adviser options are available, including those from fintech companies and traditional financial institutions. Popular examples include Betterment, Schwab Intelligent Portfolios and Vanguard Digital Advisor.

Read more: How AI Can Be Used in Investing

4. Use AI to raise your credit score

Understanding your credit score can be challenging. Credit score factors are often reported monthly, resulting in significant delays before they impact your credit.

This is another case where you may not necessarily know you're using AI, but companies use it to power suggestions for you. Tools like Experian Boost and Credit Karma are designed to understand how credit-scoring models work. They consider each credit score factor, such as payment history and credit utilization, then provide suggestions for how you can improve your credit score.

Similar to robo advisers, these tools don't rely on LLMs when making suggestions. However, they do rely on large amounts of data. For example, Credit Karma uses Intuit data to make AI-powered recommendations to its users.

Credit scoring is complex, and it typically takes time to recover from a rocky credit history. And if you have a significant amount of debt dragging down your credit score, you might benefit from working with a debt counselor.

Nevertheless, AI does a reasonably good job of helping you understand how you can improve your credit score.

5. Do your taxes with AI

Doing your own taxes can theoretically save you money, but it doesn't always work out that way. For instance, if you are self-employed, there may be many items you can deduct — but you may not know what's eligible and so miss out on those savings. Still, not everyone can afford to pay a professional to prepare their taxes.

This is another area where AI can help. First, you can talk to a chatbot for advice, for example by asking ChatGPT for suggestions of what a self-employed person can deduct. You can also ask a bot to explain IRS forms and rules in more digestible language.

In fact, companies like Blue J and TaxGPT have begun popping up to fit this exact use case. Additionally, even H&R Block and TurboTax have launched AI chatbots for users, which are reportedly getting better and better each year.

Aside from chatting with a bot, tax preparation companies have already begun utilizing AI to streamline tax filing. Some companies, like FlyFin, Keeper and Gelt combine AI and CPAs to help you do your taxes.

"AI can now automate a large portion of the tax filing process, even going so far as to create tax forecasting on a client’s behalf based on their last year’s return," Rachel Richards, CPA and head of product at Gelt, says. "Such automation not only saves time but provides both clients and their advisers with improved insight into the future ahead of them, allowing for smarter planning throughout the year."

However, Richards also notes that AI is not enough to handle tax prep on its own, so don't run off and try to use an AI agent to file. This is because taxes are highly personal, influenced by personal goals, investments and life events.

"Human guidance continues to be important for dealing with gray areas and modifying advice to meet each individual's own financial situation," Richards says.

Ultimately, you are responsible for mistakes made in your tax return, so you should check everything yourself or with a tax professional before filing.

6. AI for retirement planning

When planning for retirement, several key factors must be considered, including investment income, Social Security benefits and the rising costs of health care. Balancing all these factors in your retirement can be tricky, but AI can help you start putting together a basic retirement plan.

One way AI can help with retirement planning is by modeling an optimized withdrawal order, says Doug Carey, CFA, at WealthTrace, a retirement planning software company: "Instead of following a static rule-of-thumb where retirees withdraw from taxable accounts first, AI models can run simulations to figure out the best withdrawal order."

While you can pose these questions to bots like ChatGPT and Perplexity (being sure to protect your privacy), as Kiplinger retirement writer Donna Fuscaldo recently reported, companies have begun leveraging AI to help answer retirement questions like withdrawal orders or whether to convert a traditional IRA or 401(k) to a Roth IRA.

Although these decisions are complex, Carey says AI is great at helping to make them. However, AI is only a starting point when planning for retirement. Remember that it often falls short of working with a human financial adviser when seeking personalized advice.

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• Have a Retirement Question? AI Can Answer That

Artificial intelligence can answer that.

From ChatGPT to Gemini, retirement savers are increasingly turning to AI for help with their financial planning questions. They are asking these large language models (LLMs) all sorts of questions about their finances hoping to get the answers typically provided by financial advisers.

That isn’t going unnoticed from fintechs to traditional financial institutions that are leveraging AI to level the playing field in retirement planning.

They are using AI to help people plan for retirement, sometimes eliminating the need for a wealth adviser. Additionally, they are empowering financial advisers by automating tasks, freeing them up to spend more time with their clients.

“AI is democratizing access to wealth management that is reserved to the 1%,” says Fahad Hassan, CEO and co-founder of Range, the wealth management company. “The beauty in AI and tech is that everyday consumers get chat experiences that they can understand.”

That’s not to say AI is perfect. LLMs like ChatGPT and Gemini have their weaknesses. ChatGPT can run into trouble generating reliable and accurate answers while Gemini has limitations with common sense and real-world experiences.

What’s more, neither can replace the insight and institutional knowledge that humans bring to the table, particularly with financial planning.

“Personal finance elicits lots of emotions, and retirement planning, especially, can be confusing, overwhelming and complex for many. So, the personal, human touch of the adviser will remain integral to a financial planning experience,” says Matt George, head of Product at Edelman Financial Engines. “However, AI does provide the opportunity to make the client experience and the adviser experience better.”

AI’s role in retirement planning

Love it or hate it, AI is becoming part of the retirement planning process. Here’s a look at how some companies are leveraging AI to help you prepare for your golden age.

Boldin

What it does
Geared toward everyday investors and retirement savers, Boldin is a financial software program that uses AI to help you plan, invest and manage your finances.

The company offers a free basic plan that gives you access to retirement calculators and planning tools. For $10 a month, you can use the PlannerPlus service, which lets you input more financial information about yourself and create a more detailed retirement plan. At the top tier is the BoldinAdvisors service, which costs a flat fee of $2,500 and gives you access to a fee-only certified financial planner (CFP). It also offers retirement planning coaching sessions for $250.

How it uses AI
“We’re using an AI agent for support to answer questions when customers are building a financial plan,” says Stephen Chen, founder and CEO of Boldin. “When they are going through it they will have questions about their situation: should I claim Social Security, what are RMDs, and will ask inside the platform.”

Chen says Boldin's AI agent has ingested thousands of previous questions answered by humans and thousands of articles to provide clients with answers to their retirement questions.

How’s it going
In a recent week out of 955 tickets (questions asked by Boldin customers), 57% were handled by an AI agent and 43% were handled by a human agent. Of the questions answered by an AI agent, Boldin said 65% were resolved without the need for human intervention while 35% required the helping hand of a real-life person.

“Every company is thinking about AI right now and how to use it. Some companies are more serious than other companies,” says Chen.

Where it's going
Boldin doesn’t plan to keep its AI at the customer service level. The company is looking at ways to leverage AI to create a more personalized experience for customers, pulling from their financial data provided when they open an account. They are also looking at using AI to provide coaching to clients.

“Helping keep people on track is a big part of the value of a human financial adviser. AI can be good at that and in the future with agents it might help you do things like make a transfer or investment,” says Chen.

Range

What it does
An online financial wealth management firm that melds human advice with technology, including AI to create comprehensive financial plans. Range targets wealthy households, and has three plans ranging from $1,475 semi-annually to $4,975 semi-annually. Users get access to its team of fee-only advisers, tax, investment and retirement planning experts, and several tools and calculators among other wealth management services.

How it's using AI
“We’re trying to supercharge wealth advisers by improving the technology wealth advisers have,” says Hassan. Currently the company is using AI internally, building a comprehensive AI tool for its financial advisers to make better and quicker decisions for its clients.

“We took input from advisers at Goldman Sachs and JPMorgan who are used to working with high net wealth clients. We wanted it to be insanely comprehensive,” says Hassan.

How’s it going
Range says the use of AI speeds up thoughtful, hyper-contextualized and hyper-personalized responses for clients. The company leverages its previous conversations with clients, financial data, adviser input and AI, to provide client advice that is 30% faster.

Where it's going
Range is currently reserved for high-net-worth individuals, but it won’t be like that forever. Hassan has a vision of leveraging its AI model to provide retirement advice to the masses, not just wealthy individuals. That could mean a free version of Range to more affordable ones depending on the customer’s income and assets.

Stay tuned, Hassan says Range could be making a move on that front this summer. “The goal is to democratize wealth management,” he says.

Edelman Financial Engines

What it does
A Registered Investment Advisor or RIA firm for over 35 years, Edelman Financial Engines offers investors and retirement savers an array of financial management services including retirement planning with real humans. The fee-only financial adviser has over 1.3 million customers around the country and manages $290 billion for its clients.

How it uses AI
“We are mostly leveraging AI on the backend of our operations to help improve the client experience,” says Matt George. “Today we are looking at AI as a tool to help our advisers be more effective and efficient.”

Let’s say you want to know how much your monthly retirement income will change if you retire three years earlier than you had initially planned. With Edelman’s technology and an assist from AI on the back end, clients can see the impact in real time.

How’s it going
Edelman Financial Engines is using AI to help advisers with time consuming administrative tasks, freeing them up to spend more time focusing on the client relationship.

George says AI has been effective in rapidly summarizing meeting notes into client’s files and helping advisers prepare for upcoming meetings.

“We will continue to leverage AI to gather more and more accurate inputs to continuously improve our advice without putting an additional burden on our clients,” says George, noting AI can be used to help inform its advisers when it’s time to revisit and/or refine a financial plan.

Where it's going
Edelman Financial Engines has Silicon Valley roots and has leveraged technology to develop digital planning and investment tools, but for now its focused primarily on leveraging AI internally to improve operations, client experience, adviser experience and to help its employees better manage their day-to-day responsibilities.

“We are taking a holistic and thoughtful approach to how we evaluate and implement AI at Edelman Financial Engines with our client’s best interest in mind,” says George.

The robots won’t take over anytime soon

While AI holds a lot of promise for the future of retirement planning, all of these industry players agree there will always be a need for human hand holding.

Sure AI can tell you how a stock is performing or how much you’ll earn if you delay collecting Social Security, but it can’t walk you off the ledge if the Dow Jones Industrial drops 1,000 points or stop you from collecting Social Security benefits early out of a fear the system will become insolvent.

But humans can.

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Despite this widespread adoption, many individuals still prefer traditional methods for financial decision-making. A recent survey by the FINRA Investor Education Foundation of over 1,000 U.S. adults found that 63% consult financial professionals and 56% rely on advice from friends and family. Only a modest 5% turn directly to AI tools. Interestingly, about 25% use financial apps that often incorporate AI features like automated budgeting and portfolio suggestions, perhaps without realizing the extent of AI's involvement.​

In contrast, professional investors are rapidly embracing AI. A global survey conducted by Mercer found that 91% of investment management firms are either using AI or planning to do so. Some of the categories for this powerful technology include stock selection, asset allocation and risk assessment.​

Looking ahead, it’s hard to imagine a future where AI doesn't play a central role in how we invest, whether you’re managing billions or just starting your 401(k). The technology is evolving fast, and so is its potential impact.

So, what exactly can AI do in the investing world? Where is it making the biggest difference? And just as important — what are the risks? Let’s take a closer look.

Can I use AI to predict the stock market?

The late Jim Simons made his name as a brilliant mathematician and codebreaker before turning his attention to the financial world. In 1978, he launched Monemetrics, which would later become Renaissance Technologies — a firm now legendary in quantitative investing circles. By 1988, Simons had introduced the Medallion Fund, a vehicle that would go on to reshape how many viewed market analysis and trading.

What set Medallion apart was its early and aggressive use of complex algorithms, machine learning and artificial intelligence to sift through enormous volumes of data. Rather than relying on traditional valuation metrics, Simons and his team focused on uncovering subtle, short-term inefficiencies in the market — patterns that might escape human detection. This tech-driven approach allowed the fund to adapt rapidly to market shifts and execute trades with exceptional speed and accuracy.

The performance was nothing short of historic. Between 1988 and 2018, Medallion produced an average gross annual return of about 66%, and roughly 39% after fees — returns that place it at the top of hedge fund performance rankings.

The fund’s success sparked a wave of interest in quant strategies, where portfolios began to be built not just by MBAs and CFAs, but by data scientists, AI specialists and physicists. Yet this is not to imply that AI is somehow a silver bullet for predicting markets.

“While it can help with very short-term predictions, it’s less effective beyond this,” said Arjun Bali, who is a staff data scientist at Rocket Mortgage. “Markets tend to self-correct over time, especially in liquid asset classes. As information gets priced in, the edge from predictive models goes down, making it hard for AI to consistently exploit patterns beyond the near-term. Then there are the structural breaks, policy shifts and COVID-like unpredictable events that can render historical patterns irrelevant.”

So while AI might be able to identify certain patterns and market inefficiencies, it can’t predict the future. This was demonstrated handily as Kiplinger's senior investing editor Karee Venema tried out AI vs the stock market.

How will AI impact investing?

One of the clearest validations of AI’s growing role in the financial world is the flood of new apps designed to help retail investors harness AI for stock picking, portfolio optimization and market analysis.

These tools promise to bring institutional-level insights to the fingertips of everyday investors. Here are some examples:

• WallStreetZen: A stock research platform whose Zen Ratings AI model evaluates over 115 factors to assign ratings from A (Strong Buy) to F (Strong Sell). “Our system is trained on the things that pointed to outperformance since 2003,” said Steve Reitmeister, WallStreetZen’s editor-in-chief. “This helps eliminate the bias to what is working now with greater focus on what works over the long haul.”
  There is a free version with limited features and a premium plan for $19.50 per month, which provides access to comprehensive stock ratings, forecasts from top-performing analysts and detailed explanations for stock price movements.
• Magnifi: This service leverages AI to help optimize portfolios. It is done by using a chat interface. Magnifi is integrated with services from firms like Fidelity, Robinhood, and Schwab. There is a free plan and a premium option for $14 per month or $132 per year.
• Danelfin: An AI-powered stock-ratings engine that can help improve the odds of beating the market over the next three months. “We distill thousands of noisy market signals into an objective, explainable probability score and daily idea lists, so you spend less time hunting for alpha and more time acting on it,” said Tomas Diago, founder and CEO. The service has a PLUS plan for $25 per month and a Pro version for $70 per month.

The risks of using AI in investing

There are certainly plenty of risks with using AI in investing.

"LLMs are getting better rapidly, but math is not their strong suit," says Nick Holeman, director of financial planning at Betterment. "That is highly problematic in a field like finance that is heavily reliant on math."

Data bias is another concern, as AI models depend on the quality of their training data. Inaccurate or biased data can lead to flawed investment decisions. Moreover, as AI systems incorporate alternative data sources — such as credit card transactions and social media activity — issues of data privacy and governance in AI become increasingly significant.​

Cybersecurity is also a critical consideration. The integration of AI into trading platforms and financial systems raises the potential for breaches, particularly in fintech firms handling sensitive information.​

Despite these challenges, AI continues to evolve rapidly, introducing innovations like AI agents. While caution is advisable, AI is poised to play a significant role in shaping future investment decisions.

Learn more about AI

• AI vs the Stock Market
• How AI Will Impact Our Lives in 2025 and Beyond
• How to Protect Your Privacy While Using AI
• What Are AI Agents and What Can They Do for You?
• Major AI Companies You Should Know
• What Is AI Investing?
• How AI Will Impact Your Workplace Retirement Plan