\n<\/p>\n
Alexsl | Istock Unreleased | Getty Images<\/p>\n<\/div>\n<\/div>\n<\/div>\n
When it comes to personal finance<\/a>, artificial intelligence gives advice<\/a> 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. <\/p>\n The research \u2014 which studied seven \u201cwidely available\u201d generative AI platforms \u2014 found \u201csignificant variation\u201d in how GenAI answered prompts about emergency savings, asset allocation and withdrawals from a retirement portfolio. <\/p>\n Researchers examined free-access versions of ChatGPT, Claude, Copilot, DeepSeek, Gemini, Meta AI and Perplexity. <\/p>\n \u201cGenAI-driven responses may sound confident but can still be incomplete, misleading, or incorrect,\u201d according to the paper<\/a>, 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.<\/p>\n Its \u201csuboptimal\u201d or biased outputs raise questions \u201cabout the consistency and fairness of GenAI-driven recommendations,\u201d according to authors Swarn Chatterjee, Brenda Cude and Gianni Nicolini.<\/p>\n<\/div>\n The findings come as a large share of Americans are turning to AI to help manage their money. <\/p>\n Two out of three Americans \u2014 66% \u2014 who have used GenAI said they\u2019ve leveraged it for financial advice, according to an Intuit Credit Karma survey<\/a> published in September. The share is higher for Gen Z and millennials, at 82% for each cohort.<\/p>\n Experts said that AI is generally good at providing high-level overviews of financial topics: For example, why it\u2019s important to diversify investments, or why exchange-traded funds may be better than mutual funds in some cases but not others. <\/p>\n However, it has limitations that mean users shouldn\u2019t trust its output blindly, they said. <\/p>\n For one, the programs can also provide wrong answers due to so-called \u201challucination\u201d of the algorithm, experts said. <\/p>\n \u201cOne of the things about LLMs that I find particularly concerning is that no matter what you ask it, it\u2019ll always come back with an answer that sounds authoritative, even if it\u2019s not,\u201d Andrew Lo, director of MIT\u2019s Laboratory for Financial Engineering and principal investigator at its Computer Science and Artificial Intelligence Lab, told CNBC in an interview in March. <\/p>\n \u201cWhen it comes to very, very specific calculations of your own personal situation, that\u2019s where you have to be very, very careful,\u201d Lo said.<\/p>\n<\/div>\n