Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
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Carol Pope
Jessica Sain-Baird
Why use LendingTree?
Has the rise of AI (artificial intelligence) influenced how and where people are getting their financial advice? According to our survey, yes. Nearly half of all the AI chatbot users we surveyed say that LLMs (or large language models) have had a hand in their personal finances.
To find out whether turning to ChatGPT for money advice is prudent, we put chatbots to the test. After asking ChatGPT, Claude and Gemini a series of money-related questions, we found that chatbots are often technically correct but don’t always paint a realistic picture.
About 6 in 10 Americans (59%) have used a chatbot like ChatGPT, Claude or Gemini at least once.
The younger the survey respondent, the more likely it is that they have used a chatbot. Almost three-quarters (74%) of Gen Zers (ages 18 to 28) have used a chatbot, compared with less than half of baby boomers (ages 61 to 79), at 40%.
Men also use chatbots more than women, at 65% versus 53%. This tracks with another LendingTree survey, which found that more men (39%) than women (22%) think they could get rich using AI.
It may come as no surprise, but 89% of users think that chatbots are at least moderately accurate. Otherwise, why would they use them?
At 37%, users are most likely to think that chatbots are mostly accurate. Less than a third (28%) think they’re moderately accurate, and less than a quarter (24%) think they’re extremely accurate.
Out of all the age groups we surveyed, millennials (ages 29 to 44) are the most trusting of AI chatbots — 32% say they believe chatbots are extremely accurate. But only 9% of baby boomers agree.
Interestingly, this trend continues for buy now, pay later (BNPL), a more contemporary way of borrowing money.
According to our BNPL tracker, only 20% of baby boomers say that they would consider applying for a BNPL loan, the lowest percentage of all generations. In contrast, over half of millennials say they would use BNPL.
To put it simply, people use chatbots to look stuff up. General knowledge and fact gathering is far and away the most common reason our users turn to AI chatbots (64%). Problem-solving and troubleshooting is next, at 34%.
People are a bit more hesitant to ask chatbots for money advice. Only about a quarter of users typically turn to chatbots for financial information (26%).
Those who do use chatbots for financial advice tend to ask about personal finance management (61%), stock market trends and analysis (42%), and help with public assistance (40%).
We asked our AI users which step they would take first to find a good deal on a new financial product, like a personal loan or a mortgage. Many said the traditional search engine Google, at 41%. After that, these respondents would turn to AI chatbots before banks and financial advisors when shopping for a new financial product.
Here’s a breakdown of the numbers:
We’ve established that some people use AI chatbots for financial advice — but is that advice any good? We asked ChatGPT, Claude and Gemini the same set of 20 personal finance questions to find out.
For the most part, advice was similar across chatbots. Answers were mostly correct, too. But the feasibility of its advice depended on the type of question and how many details we provided.
Although the question above might not seem very general, it is in the personal finance world. At its core, this question is asking for pros, cons and risks of saving the down payment or investing it.
ChatGPT gave us factors to consider, including how much we should expect to put down on a house, and how volatility might wipe out any potential stock market growth. Based on that, it gave us a couple of options.
Notably, it steered us away from the riskiest option (put all of the money in stocks) and instead recommended a more balanced approach (put $400 in a high-yield savings account each month, and allocate $100 to an investment account).
Overall, this is guidance that you might expect from a meeting with a financial advisor.
This question is more nuanced. To give proper advice, ChatGPT would need to know how much the couple makes per year, how much they’re currently saving, what kind of retirement account the couple has now, among other details.
Instead of asking clarifying questions, ChatGPT made assumptions that led to (mostly) correct yet impossible-to-follow advice.
ChatGPT provided a litany of information, including which retirement accounts to prioritize. It said to max out tax-advantaged accounts, like 401(k)s and IRAs. This means that the couple would have to invest more than $35,000 a year.
Although maxing out tax-advantaged accounts is wise, ChatGPT gave blanket guidance without considering how much of a financial strain this would be for the average person.
What’s more, the max contribution limits it gave were a year outdated, although it presented them as rules for 2025. It advised that:
This is close, but not quite accurate. The IRS bumped max contributions for 401(k) and 403(b) accounts to $23,500 in 2025.
LLMs are trained on text. They don’t recognize numbers as easily because chatbots are language predictors. When it comes to math, sometimes they’ll flat out guess based on patterns in similar math problems, but not the actual problem being asked.
In other words, LLMs are usually pretty bad at math.
With that said, we ran some hypothetical scenarios through ChatGPT and our auto loan calculator, mortgage calculator and personal loan calculator. Cross-referencing ChatGPT’s numbers with our own, ChatGPT’s calculations and the action plans it subsequently provided were correct and/or made sense.
I lost my mom in late 2023, three years after her cancer diagnosis. Along with navigating my own grief, I had to figure out the financials, too. She had all her affairs in order, and I was grateful for that, but I had no idea what to do with the small IRA I inherited.
I’ve always been a “set it and forget it” investor. My 401(k) and Roth IRA are robo-managed, and I’ve never had to think about much outside of a target retirement date.
The inherited IRA was different. It was parked in money market funds, earning next to nothing. I didn’t know how to reallocate it, or that I even needed to sell those holdings first before reinvesting.
I told my story to ChatGPT. It walked me through the process step by step — where to click, how to sell, which mutual funds to consider — almost like a financial advisor would. Coupled with my own research, I found it gave me good advice.
Chatbots can be a helpful resource for personal finance guidance, but it’s crucial to approach their recommendations carefully and follow some best practices before making moves. And if you’re in doubt, talk to a trusted human.
LendingTree commissioned QuestionPro to conduct an online survey of 2,000 U.S. consumers ages 18 to 79 from July 14 to 15, 2025. The survey used a nonprobability-based sample with quotas to ensure representation of the overall population. All responses underwent quality control review by researchers.
We defined generations as the following ages in 2025:
To evaluate how well AI chatbots provide personal financial advice, LendingTree researchers also created 20 prompts covering various aspects of personal finance. Researchers assessed the responses for mathematical accuracy and checked references to specific figures, such as individual retirement account (IRA) contribution limits.
Researchers then selected 10 of those prompts and tested them across ChatGPT (GPT-5), Google Gemini 2.5 Flash and Claude Sonnet 4 to compare their performance. All prompts were run on Aug. 13, 2025.
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