Have you been using an AI chatbot to give you quick answers for life’s daily tasks?
You’re not alone in this time-saving measure, but you should be careful with just how much you trust the answers you receive on certain topics.
Take credit cards, for example.
AI chatbots, such as ChatGPT, Claude or Gemini, are 5.7 times more likely to recommend a credit card with an annual fee of $400 or more than they are to recommend a no-annual-fee card, according to research by 5W Public Relations.
Given that Team Clark believes the overwhelming majority of consumers are better off with no-annual-fee cash back credit cards based on their spending habits, that’s a troubling statistic.
The credit card recommendations you get from your chatbot aren’t necessarily bad, but that statistic should have your antenna up for suggestions that don’t look right for your situation.
That awareness could save you money on a premium travel credit card that you may not actually need.
In this article, I’ll explain how your chatbot’s credit card recommendations may be manipulated.
Why AI Chatbot Advice for Credit Cards Can Be Tricky
If you’re new to using a chatbot, you may not be familiar with how it gathers information to answer questions about topics like credit cards.
Here’s a brief explanation of how this often works:
How Chatbots Acquire Information
You submit a question to the chatbot. Maybe something like “Which rewards credit card is best?”
The chatbot deploys a “real-time” web scrape. This basically means it searches all of the internet for the latest credit card offers, annual fees, and sign-up bonuses in real time. I asked Google’s Gemini to define that scraping process. It said, “I do not rely on static internal knowledge. Instead, I deploy search tools to scan high-authority financial aggregate sites (like U.S. News, Yahoo Finance, WalletHub, and CreditCards.com) alongside direct card issuer terms. This ensures rates, fees, and perks are accurate up to the current day.”
The chatbot uses the acquired information to develop a response tailored to your specific prompt. I asked Gemini to tell me about that process, and it told me that it has a “risk mitigation” process that weighs the pros and cons of each card while also applying a “de-biasing” process to try to identify where its source material may have shown bias. Additionally, it accounts for prevailing user opinion by scanning for online chatter about the topic for “real” feedback.
The “bias” that it is attempting to eliminate is what can make the recommendation you receive on a credit card go sideways. And, according to the data provided by 5W, it happens more than we’d hope.
Here’s why it’s an ongoing issue that AI chatbots are battling:
Source Material Can Be Tainted by Financial Motives
The data provided by 5W is pretty eye-opening on the sourcing by AI chatbots in the credit card space:
“Across 4,200 credit card prompts tested between January and April 2026, three publisher domains – The Points Guy, NerdWallet, and Bankrate – were observed to dominate the citation surface, accounting for more than 62% of source attributions inside ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews answers.”
It’s no secret that websites, including Clark.com, that review consumer products like credit cards are often affiliate partners for the products they review.
This means the website, like the ones listed as prominent sources in the study above, may receive compensation from the product it reviews in exchange for driving customers to that product.
And not all of these sites have your best interests at heart.
For example, some may feature a credit card as its “top choice” in a category because the affiliate agreement for that card may be more profitable than a card with similar or potentially superior characteristics.
Bottom line: The sites that AI chatbots cite could be dishing out financially-fueled credit card recommendations. And the chatbot, while trying to filter that bias out, may still be giving you information tainted by it.
What Makes Clark.com Credit Card Content Different?
If this has you wondering how Team Clark handles credit card content differently, see our credit card disclosure:
Clark.com has partnered with CardRatings for our coverage of credit card products. Clark.com and CardRatings may receive a commission from some card issuers may earn compensation when a customer clicks on a link, when an application is approved, or when an account is opened. Any potential commission DOES NOT influence if or where a card will appear in our content. Opinions, reviews, analyses & recommendations are the author’s alone, and have not been reviewed, endorsed or approved by any of the card issuers.
As Team Clark’s lead credit card writer, I can take this a step further: We go to great lengths to separate the “business” side of credit cards from the “content production” side. As such, I’m “in the dark” on much of our affiliate process.
We feel it is important that you get an unbiased review from us on each card regardless of any potential affiliate earnings. And if a non-affiliate card is the best fit for your wallet, that’s what we recommend.
Simply put: Your trust is what we value most.
Non-expert Opinions on Certain Sites Can Be Overweighted
In addition to “expert” sites that review credit cards for a living and the “official” sites of the credit cards in question, AI chatbots also cite the internet’s prevailing opinions on a particular card to develop its answers to your queries.
For example, 38% of travel credit card-related queries analyzed in the 5W study included prevailing citations from one of three Reddit forums.
Reddit happens to have a great credit card subreddit that is a good resource for strategy discussion, but that reliance on one source for prevailing user opinion on specific credit cards is ripe for potential manipulation.
Not unlike the struggle with avoiding “fake reviews” on Google or Yelp! for other product types, relying too much on one forum to develop overall user sentiment for a credit card can be dangerous.
I like to “fact check” my chatbot answers by clicking on the links it sources to provide an answer to see where it’s getting its “opinion” on a topic to see if it’s something that I’d trust myself as a healthy skeptic of internet opinions.
Bottom Line
Chatbots are increasingly useful tools for saving time. And they’re getting better at weeding out bad information by the day.
But you should still be very careful about the financial advice that you receive from one. That includes credit card recommendations.
Outside forces like affiliate marketers with financial incentives and outspoken internet forum users touting their favorite cards may have a disproportionate amount of influence on your chatbot of choice.
And the end result could be a recommendation that doesn’t quite fit.
That’s why Team Clark likes to keep it simple, transparent and relatable when we dish out credit card advice to the average consumer:
Read money expert Clark Howard’s rules for credit card usage to get started, which include starting with a no-annual-fee credit card that pays you an unlimited 2% cash back on all of your spending.
Visit our guide to rewards credit cards to get started on the right card strategy for your spending habits.
Do you use a chatbot for credit card advice? What has your experience been like? We’d love to hear about it in the Clark.com community.
The post Why You Should Be Careful Taking Credit Card Advice from AI appeared first on Clark Howard.