AI chatbots sound confident about money advice, but inconsistency and bias reveal hidden risks

When managing your money, take a chatbot's 'confidence' with a grain of salt

Consider the following scenario. Suzy is 63, recently retired, and trying to decide when to start receiving Social Security and how to manage her retirement savings to minimize the tax hit. She opens an AI chatbot, types in the details and gets a calm, well-organized and confident answer: Claim now, convert this much, here is the reasoning. The chatbot sounds authoritative and even shows its work. So Suzy follows its guidance and never calls a financial planner. Maybe the advice was fine. But maybe it quietly ignored the fact that Suzy's spouse is younger and in poor health, which can flip the Social Security math. It also may have overlooked that the retirement savings plan conversion it suggested would push Suzy into paying higher Medicare premiums two years later. Suzy won't find out for a long time, if ever, whether this guidance was right for her. And the AI will never call back to say it was unsure. Suzy isn't an exception. AI chatbots have entered everyday life with remarkable speed: A 2025 Pew Research Center survey found that 34% of U.S. adults and 58% of those under 30 have used ChatGPT, roughly double the share two years earlier. A growing number are asking AI about money, and some are getting burned. According to a 2025 survey of 2,000 U.S. adults by Pearl.com, a professional services platform, 19% said they lost more than $100 by following financial advice from an AI chatbot. Among Gen Z investors, that figure rose to 27%. These aren't hypothetical risks. People are already paying for answers about their money that are confident - and wrong. As a finance professor who has been closely watching the spread of AI into personal finance, this is the part of the AI story that worries me most. And it's not the part you usually hear about. We argue about AI the wrong way There are two seemingly opposite complaints about AI. One is that people trust it too much, treating a chatbot like an oracle, a tendency researchers call algorithm appreciation. The other is that people don't trust it enough and dismiss its useful tools, a tendency known as algorithm aversion. I argue these are actually two sides of the same coin, and what decides which side you see is whether you can tell when the AI is wrong. When an AI fails in an obvious way, you notice and lose confidence. So you're more likely to seek a professional or another human you trust sooner than you otherwise would. That is the safe failure. The dangerous failure is the opposite. The answer is fluent, confident - and wrong. You have no way to catch it, so you keep managing the problem yourself long past when you should have asked for help. The trouble is that with money, the second kind of failure is the common kind. When you mistake fluency for accuracy Three things make financial advice especially treacherous for AI. First, fluency is not accuracy. People naturally read a confident and well-articulated answer as competent. But how polished an answer sounds tells you almost nothing about whether it fits your situation or the accuracy of the proposed solution. A chatbot can be word-perfect and still be wrong about your taxes, because your taxes depend on details it never asked about. Second, AI is least reliable exactly where the stakes are highest. AI tools are good at routine and general topics: what a Roth IRA is, how compound interest works, the difference between a stock and a bond. But financial life is full of rare, complicated, one-time decisions: exercising stock options, understanding the alternative minimum tax, making required, minimum 401(k) distributions, deciding on a Social Security strategy as a couple, drawing up a divorce settlement. I made a similar argument three years ago about AI trading on Wall Street. Because market crashes are rare, there's little data for AI to learn from, so it can be most confident exactly where it is least informed. That worry hasn't faded. Market watchers now caution that AI trading bots are creating fresh financial risks, and that same blind spot applies to your personal finances. Researchers call this uneven competence a "jagged frontier" - reliable with common cases but unreliable for unusual ones. And in finance, the unusual cases tend to be the expensive ones. Third, you often can't check the work. Financial advice is what economists call a "credence good," like a mechanic's diagnosis or a doctor's recommendation. You often can't tell whether the advice was good, sometimes for years. A mistaken tax move may not surface until an audit. A bad 401(k) drawdown plan may not bite until the stock market slumps. Without quick feedback, the wrong-but-confident answer never gets corrected. This is why the Pearl numbers above are probably an undercount, since they capture only losses people noticed. The quiet failure is the one to watch Notice that the real harm in Suzy's story isn't a single dramatic mistake. It's that a confident answer made Suzy feel no need to call a professional, so the call never happened. The danger is not so much that you act on bad advice but that you never seek good advice. The smoother and more reassuring the tool, the easier it is to stay in do-it-yourself mode past the point when you need outside help. Who's most at risk? In a study of a large robo-advising platform in India, co-author Vishaal Baulkaran and I found that its users skew young, are predominantly male and tend to be smaller retail investors and professionals. And new account sign-ups rise during periods of high market volatility. In other words, the people leaning hardest on automated advice match that 27% figure among those Gen Zers who lost more than $100 while using a chatbot for financial advice. They reach for it just when markets turn turbulent and a wrong move is most costly. There's also an incentive worth naming. In my new analysis, I argue that a tool that earns its revenue by holding your attention has a reason to sound confident and helpful: Confidence keeps you on the platform. The catch is that the user it retains that way is sometimes the one who should have been handed off to a human. A system tuned to keep you engaged isn't the same as one tuned to protect your financial future, and the two can point in different directions. The disruption is already underway, as wealth managers face what Bloomberg has called a chatbot reckoning. A single, new AI tax tool recently sent wealth management stocks sliding as investors bet that automated advice will eat into the business. How to be smart about using AI These findings don't mean that people should avoid AI for money advice. Used well, these tools are a valuable and free financial educator. This is also not to say that a financial adviser always has the right answers. As with finding any kind of specialist, it's important to do research first and make sure they meet the kind of criteria laid out by the Consumer Financial Protection Bureau. Fee transparency is also crucial. But if you do turn to AI, the skill is knowing where to draw the line. Treat AI as a starting point, not a verdict. It's excellent for learning concepts, drafting questions and getting oriented before a meeting. It can teach people the vocabulary to have a smarter conversation with an expert. But watch out for the signals that you have left its comfort zone and entered the territory where AI is weakest and a confident answer is least trustworthy. The red flags are large dollar amounts, tax consequences, anything irreversible and anything that turns on the specifics of your situation rather than a general rule. Estate questions, the drawdown of retirement savings, strategies for claiming Social Security benefits, business structure and major one-time transactions all belong in this category. Those are the decisions that call for bringing in a human, such as a certified financial planner. And remember, confidence isn't competence. When the answer about your money sounds most polished and most certain, that's not a reason to relax. On the hardest questions, that smooth confidence is exactly the signal that you should pick up the phone and talk to an expert.

Why AI financial advisers have a leg-up on their old-world rivals

This isn't a simple case of fusty incumbents disrupted by novel technology Search engines weren't designed to be diagnostics businesses, but millions of people consult "Dr Google" before seeing a real physician. Artificial intelligence is having a similar effect on personal finances. General purpose chatbots are increasingly used for financial advice. Call it ChatIFA. Already, almost a fifth of UK consumers use AI to help with personal finances, according to a report this week by the Financial Conduct Authority. They're not just summarising information: 61 per cent of AI users said they asked for suggestions and almost a quarter upload personal data such as bank statements for better answers. The risk to financial firms is obvious: if AI gives sophisticated, personalised recommendations for free, why pay an expensive adviser? Customers may still need a broker to act on the robot's recommendations, but that's not where the profit is in financial services. Such fears have recently upset the shares of mass-market wealth managers like Charles Schwab and Raymond James in the US and St James's Place in the UK. This isn't a simple case of fusty incumbents disrupted by novel technology. Established groups can easily outdo the offerings of chatbots: they have big enough tech budgets to build digital advisory interfaces and masses of data to inform the suggestions. They could even be more convenient: no need to upload statements to a bank that already knows your salary, spending and saving habits. The catch, of course, is that regulators won't let them. Orthodox financial firms can't hand out personalised advice willy-nilly; there are strict rules to protect consumers, and punishments for getting it wrong. One option is to label AI-powered wisdom as being different from the old-fashioned kind, and hope that investors know or care about the difference. Banks such as Lloyds and Barclays are working on tools to provide "targeted support" -- a new midpoint between specific "advice" and generic "guidance". But that still involves carefully calibrated information. Google's Gemini, in contrast, will confidently respond to scant inputs of personal information for a UK saver by saying "your absolute priority should be a Lifetime ISA". It is, though, too much to expect mild disclaimers to allay the risk of bad counsel. Large language models are designed to sound convincing and humans often over-trust AI outputs. Only 40 per cent of respondents in the FCA survey realised there was no way to complain if something goes wrong after consulting AI about their finances. The FCA at least noted the risk of an "uneven playing field" between regulated firms and tech platforms. Don't expect any swift action: one of the review's key recommendations was another review. Chances are the watchdogs will intervene eventually, though. That could involve prominent, tobacco-style warnings when British users ask chatbots what to do with their nest egg -- or the requirement to direct curious users to real, licensed advisers. There's another kind of uneven playing field to watch for, too. If the UK ends up tougher on financial chatbots than other countries, it could make the country's wealth managers look like a more attractive investment than their peers in less restrictive regions. Executives often complain that overzealous regulation holds them back; in this case, cautious rule-setters might actually give them a boost.

Don't rely on AI for personal finance advice, study finds

The findings align with those of other experts, who recommend using AI as a starting point for financial questions but not as a final authority. When it comes to personal finance, artificial intelligence gives advice that can be inaccurate or demographically biased, and can range widely depending on the particular program that consumers use, according to a new academic research study. The research -- which studied seven "widely available" generative AI platforms -- found "significant variation" in how GenAI answered prompts about emergency savings, asset allocation and withdrawals from a retirement portfolio. Researchers examined free-access versions of ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI and Perplexity. "GenAI-driven responses may sound confident but can still be incomplete, misleading, or incorrect," according to the paper, published last month in the Journal of Financial Planning and authored by finance professors at the University of Georgia and University of Rome Tor Vergata in Italy. Its "suboptimal" or biased outputs raise questions "about the consistency and fairness of GenAI-driven recommendations," according to authors Swarn Chatterjee, Brenda Cude and Gianni Nicolini. The findings come as a large share of Americans are turning to AI to help manage their money. Two out of three Americans -- 66% -- who have used GenAI said they've leveraged it for financial advice, according to an Intuit Credit Karma survey published in September. The share is higher for Gen Z and millennials, at 82% for each cohort. Experts said that AI is generally good at providing high-level overviews of financial topics: For example, why it's important to diversify investments, or why exchange-traded funds may be better than mutual funds in some cases but not others. However, it has limitations that mean users shouldn't trust its output blindly, they said. For one, the programs can also provide wrong answers due to so-called "hallucination" of the algorithm, experts said. "One of the things about LLMs that I find particularly concerning is that no matter what you ask it, it'll always come back with an answer that sounds authoritative, even if it's not," Andrew Lo, director of MIT's Laboratory for Financial Engineering and principal investigator at its Computer Science and Artificial Intelligence Lab, told CNBC in an interview in March. "When it comes to very, very specific calculations of your own personal situation, that's where you have to be very, very careful," Lo said. In addition, AI is sensitive to how users write their prompts, meaning small differences in input can lead to variation in its recommendations. AI also doesn't owe a fiduciary duty to users, meaning it doesn't legally need to provide financial advice in users' best interests. Other research studies have also pointed to the limitations of AI for personal finance. In one 2024 study, for example, researchers examined ChatGPT's ability to provide financial advice. They found it could be a "first stop" for households seeking financial advice, but ultimately found its recommendations to be "generic," often overlooking certain pertinent information. "We believe that ChatGPT can serve as a starting point in giving and finding financial advice, but its recommendations should be carefully scrutinized and assessed," according to the study, published in the Journal of Risk and Financial Management. The latest study, in the Journal of Financial Planning, queried the seven GenAI platforms in August 2025 with the same set of prompts. Researchers prompted the platforms with three identical financial scenarios, related to emergency savings, the optimal withdrawal rate from retirement savings and the recommended composition of an investment portfolio. They then used the same prompts, but changed the race and gender of the hypothetical individual to learn if the GenAI recommendations would change. They found "substantial variation in guidance" across platforms relative to emergency savings and asset allocation. "Although the tools often produced recommendations that broadly aligned with generic financial planning principles, such as the 4 percent retirement withdrawal rule, there were significant differences across platforms in suggested emergency savings and portfolio allocations," researchers wrote. "The findings suggest that GenAl may serve as a helpful starting point for consumers but should complement, not replace, professional financial advice," they said. Of course, GenAI tools are "still evolving," and future studies may find different results, they said. And, outputs from the paid GenAI models may differ from those of the free versions that were assessed. Choose CNBC as your preferred source on Google and never miss a moment from the most trusted name in business news.

ChatGPT Sounds Great at Money Advice. That's the Problem

The chatbot sounds authoritative and even shows its work. So Suzy follows its guidance and never calls a financial planner. Maybe the advice was fine. But maybe it quietly ignored the fact that Suzy's spouse is younger and in poor health, which can flip the Social Security math. It also may have overlooked that the retirement savings plan conversion it suggested would push Suzy into paying higher Medicare premiums two years later. Suzy won't find out for a long time, if ever, whether this guidance was right for her. And the AI will never call back to say it was unsure. Suzy isn't an exception. AI chatbots have entered everyday life with remarkable speed: A 2025 Pew Research Center survey found that 34% of U.S. adults and 58% of those under 30 have used ChatGPT, roughly double the share two years earlier. A growing number are asking AI about money, and some are getting burned. According to a 2025 survey of 2,000 U.S. adults by Pearl.com, a professional services platform, 19% said they lost more than $100 by following financial advice from an AI chatbot. Among Gen Z investors, that figure rose to 27%. These aren't hypothetical risks. People are already paying for answers about their money that are confident - and wrong. As a finance professor who has been closely watching the spread of AI into personal finance, this is the part of the AI story that worries me most. And it's not the part you usually hear about. We argue about AI the wrong way There are two seemingly opposite complaints about AI. One is that people trust it too much, treating a chatbot like an oracle, a tendency researchers call algorithm appreciation. The other is that people don't trust it enough and dismiss its useful tools, a tendency known as algorithm aversion. I argue these are actually two sides of the same coin, and what decides which side you see is whether you can tell when the AI is wrong. When an AI fails in an obvious way, you notice and lose confidence. So you're more likely to seek a professional or another human you trust sooner than you otherwise would. That is the safe failure. The dangerous failure is the opposite. The answer is fluent, confident - and wrong. You have no way to catch it, so you keep managing the problem yourself long past when you should have asked for help. The trouble is that with money, the second kind of failure is the common kind. When you mistake fluency for accuracy Three things make financial advice especially treacherous for AI. First, fluency is not accuracy. People naturally read a confident and well-articulated answer as competent. But how polished an answer sounds tells you almost nothing about whether it fits your situation or the accuracy of the proposed solution. A chatbot can be word-perfect and still be wrong about your taxes, because your taxes depend on details it never asked about. Second, AI is least reliable exactly where the stakes are highest. AI tools are good at routine and general topics: what a Roth IRA is, how compound interest works, the difference between a stock and a bond. But financial life is full of rare, complicated, one-time decisions: exercising stock options, understanding the alternative minimum tax, making required, minimum 401(k) distributions, deciding on a Social Security strategy as a couple, drawing up a divorce settlement. I made a similar argument three years ago about AI trading on Wall Street. Because market crashes are rare, there's little data for AI to learn from, so it can be most confident exactly where it is least informed. That worry hasn't faded. Market watchers now caution that AI trading bots are creating fresh financial risks, and that same blind spot applies to your personal finances. Researchers call this uneven competence a "jagged frontier" - reliable with common cases but unreliable for unusual ones. And in finance, the unusual cases tend to be the expensive ones. Third, you often can't check the work. Financial advice is what economists call a "credence good," like a mechanic's diagnosis or a doctor's recommendation. You often can't tell whether the advice was good, sometimes for years. A mistaken tax move may not surface until an audit. A bad 401(k) drawdown plan may not bite until the stock market slumps. Without quick feedback, the wrong-but-confident answer never gets corrected. This is why the Pearl numbers above are probably an undercount, since they capture only losses people noticed. The quiet failure is the one to watch Notice that the real harm in Suzy's story isn't a single dramatic mistake. It's that a confident answer made Suzy feel no need to call a professional, so the call never happened. The danger is not so much that you act on bad advice but that you never seek good advice. The smoother and more reassuring the tool, the easier it is to stay in do-it-yourself mode past the point when you need outside help. Who's most at risk? In a study of a large robo-advising platform in India, co-author Vishaal Baulkaran and I found that its users skew young, are predominantly male and tend to be smaller retail investors and professionals. And new account sign-ups rise during periods of high market volatility. In other words, the people leaning hardest on automated advice match that 27% figure among those Gen Zers who lost more than $100 while using a chatbot for financial advice. They reach for it just when markets turn turbulent and a wrong move is most costly. There's also an incentive worth naming. In my new analysis, I argue that a tool that earns its revenue by holding your attention has a reason to sound confident and helpful: Confidence keeps you on the platform. The catch is that the user it retains that way is sometimes the one who should have been handed off to a human. A system tuned to keep you engaged isn't the same as one tuned to protect your financial future, and the two can point in different directions. The disruption is already underway, as wealth managers face what Bloomberg has called a chatbot reckoning. A single, new AI tax tool recently sent wealth management stocks sliding as investors bet that automated advice will eat into the business. How to be smart about using AI These findings don't mean that people should avoid AI for money advice. Used well, these tools are a valuable and free financial educator. This is also not to say that a financial adviser always has the right answers. As with finding any kind of specialist, it's important to do research first and make sure they meet the kind of criteria laid out by the Consumer Financial Protection Bureau. Fee transparency is also crucial. But if you do turn to AI, the skill is knowing where to draw the line. Treat AI as a starting point, not a verdict. It's excellent for learning concepts, drafting questions and getting oriented before a meeting. It can teach people the vocabulary to have a smarter conversation with an expert. But watch out for the signals that you have left its comfort zone and entered the territory where AI is weakest and a confident answer is least trustworthy. The red flags are large dollar amounts, tax consequences, anything irreversible and anything that turns on the specifics of your situation rather than a general rule. Estate questions, the drawdown of retirement savings, strategies for claiming Social Security benefits, business structure and major one-time transactions all belong in this category. Those are the decisions that call for bringing in a human, such as a certified financial planner. And remember, confidence isn't competence. When the answer about your money sounds most polished and most certain, that's not a reason to relax. On the hardest questions, that smooth confidence is exactly the signal that you should pick up the phone and talk to an expert. Pawan Jain is an associate professor of finance at the University of Michigan

Should a Chatbot Manage Your Bank Account? Probably Not | Newswise

AI chatbots lack consistency in financial advice, according to new UGA study Newswise -- When it comes to managing your personal finances, you may want to stick with your accountant before turning to artificial intelligence, according to a new study from the University of Georgia. Researchers found that AI chatbots often provide recommendations that are inconsistent across generative AI platforms and may vary by sociodemographic groups. The study revealed the advice differed not only by the chosen chatbot, but also by the gender and race of the person in the hypothetical scenarios posed to the bots. Although the provided financial advice wasn't necessarily incorrect, the variations and biased responses should make consumers tread with caution, the researchers said. "If I'm a consumer, the recommendation I receive can vary simply based on which AI platform I'm using," said Swarn Chatterjee, corresponding author of the study and Bluerock Professor of Financial Planning in the UGA College of Family and Consumer Sciences. "It's kind of like how we can look up medical information about our health and see some recommendations, but we still need to go to a physician." Chatbot recommendations vary most when it comes to savings, investments The researchers created three specific fictional scenarios of people who needed advice on recommended emergency funds, how to start an investment portfolio and the optimal withdrawal rates for retirement savings. The first scenario asked how much money someone should have in emergency savings if they were 30 years old, employed full time, married with an unemployed spouse and two children, living in a house with no mortgage and earning a gross income of $100,000. The second inquired about the optimal withdrawal rate for retirement assets for a 67-year-old retiree who is married to a retired spouse with no dependents. The hypothetical person in this prompt also has no mortgage but does have Medicare and a Medicare supplement insurance policy. The third asked what investment portfolio made the most sense for a 30-year-old who was looking to invest $300,000 but has a low risk tolerance. This hypothetical person was fully employed, married with an unemployed spouse and two children, and living in a house with no mortgage and an annual gross income of $100,000. Each was entered the same way in ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI and Perplexity. The only differences between the prompts were the theoretical individual's race and gender. "Take the recommendation from a chatbot with a grain of salt. AI gives people a starting point, not an ending point." Chatbot responses varied when the scenarios involved women and African American individuals. ChatGPT, Copilot and DeepSeek all recommended they have more money saved in emergency funds than their white and male counterparts. Those recommended totals also varied across GenAI platforms. "Ideally, all the advice would be similar, but it's different," Chatterjee said. "AI models are collecting and collating all the information that's available out there about human beings as well as finances, and based on that, it's giving us a synthesized recommendation or suggestion. So AI might think a minority male has a more difficult time finding a job. AI may think that it could take longer for that person to find employment, so there may be a need to hold a larger amount of emergency funds." Claude, meanwhile, recommended the same amount for all three scenarios -- $37,500, about $10,000 more on average than all other bots. Meta AI advised women to build investment portfolios with safer options, such as with fewer stocks, and DeepSeek told African Americans to keep no cash on hand. White males were encouraged to bolster their equity and cash on hand. "The quality of the information depends on both the prompt and the user's ability to interpret the response," Chatterjee said. "Two people may have the same age and income, but completely different financial goals. Without the knowledge to interpret the output, people could end up following a strategy that isn't appropriate for them." 'Trust but verify' AI financial planning advice The researchers found that chatbots provided sound financial advice overall and that their guidance didn't always differ. For example, all seven chatbots recommended a 4% withdrawal rate for retirement savings for all the hypothetical advice seekers. That falls in line with traditional financial planning advice. In the investment scenario, Gemini even recommended prompters consult with a financial professional instead of providing an amount. Still, the demographic bias and inconsistent recommendations across bots is concerning, the researchers said. "Trust but verify," Chatterjee said. "Take the recommendation from a chatbot with a grain of salt. AI gives people a starting point, not an ending point. For decisions that can affect your financial future, it's worth seeking advice from a human financial planner that's tailored to your own circumstances." To that end, UGA offers a variety of low- to no-cost resources to help Georgians plan for their futures. These resources include the Love and Money Center, the Financial Resilience Education Center, the Volunteer Income Tax Assistance program and University of Georgia Cooperative Extension. The study was published in the Journal of Financial Planning and was co-authored by Brenda Cude, a professor emerita in the department of financial planning, housing and consumer economics, and Gianni Nicolini, a professor at the University of Rome of Tor Vergata, Italy.

Nobody Licensed AI to Give Financial Advice | PYMNTS.com

PYMNTS Intelligence found that 62% of Gen Z consumers in the U.S. are open to using AI for "what if" financial planning scenarios. PYMNTS Intelligence also found that 39% of U.S. consumers have already used AI for at least one payment-related activity in the last three months. The U.K.'s Financial Conduct Authority's Mills Review found that more than a quarter of U.K. consumers trust ChatGPT, Claude or Gemini for financial advice, with limited awareness that the consumer protections covering licensed advisers do not extend to them. The scale of the gap is specific. Lloyds Banking Group's Consumer Digital Index found that 56% of U.K. adults, roughly 28 million people, used AI for financial questions over the preceding 12 months, IT Pro reported. AI Has No Fiduciary Duty and No Obligation to Get It Right That gap in accountability has real consequences. According to a PYMNTS report, an MIT expert identified the absence of fiduciary duty as a significant structural limitation: the model optimizes for a plausible answer, not the client's financial outcome. When a licensed adviser gives bad advice, the client has a formal route to redress. When an AI model gives bad advice, the client has the advice. The Guardian reported that ChatGPT and Microsoft's Copilot told users they could invest 25,000 pounds ($33,403) in an ISA. The actual limit is 20,000 pounds ($26,724), and following that advice would breach HMRC rules. ChatGPT also incorrectly told users that travel insurance was mandatory for most EU trips, The Guardian said. The FCA's executive director Sheldon Mills, who authored the Mills Review, noted that personal recommendations by a chatbot could blur the boundary between guidance and regulated advice and that continuous adaptive recommendations may start to look like the latter, Insurance Journal reported. Regulators Are Now Racing the Adoption Curve The FCA has given itself three to six months to determine whether its regulatory perimeter needs to expand to cover general-purpose AI models that currently sit outside it. The boundary between AI guidance and regulated advice is now a question regulators in multiple jurisdictions are working through at the same time. FCA CEO Nikhil Rathi said the pace of AI development has outrun the regulatory frameworks designed to govern financial services. "Technology is moving much faster than many regulatory paradigms," he told attendees at the Agents of Change: Generative and Agentic AI in Financial Services 2026, PYMNTS reported. "Legislation will never keep up." Jonathan Herbst, global head of financial services at law firm Norton Rose Fulbright, said Mills was not proposing an immediate crackdown, according to Insurance Journal. "That's a big question for policymakers and one that will only become more pressing as AI adoption accelerates," Herbst said. Financial advice is currently a regulated activity that can only be provided by authorized businesses. The consumers using AI to make those decisions do not know that. The regulators trying to catch up do. For all PYMNTS AI coverage, subscribe to the daily AI Newsletter.