A few months ago I did something I should have done years earlier. I uploaded several months of credit card statements into an AI assistant and asked it to tell me whether I was using the right card for the way I actually spend money. That was when I decided to use AI to find the best credit card for my specific situation, rather than relying on comparison sites with obvious affiliate agendas.
The answer was no. Not even close.
This post walks through exactly how I used AI to find the best credit card for my spending habits, what the process looked like, and what I switched to as a result.
Why I decided to use AI to find the best credit card
I had been using the same credit card for years out of inertia. Not because I had researched it and decided it was the best option, but because it was the card I signed up for a long time ago and never revisited.
The honest truth is that comparing credit cards manually is genuinely tedious. Every card has a different rewards structure, different spending categories, different annual fees, different sign-on bonuses with different conditions attached. Most comparison websites are heavily influenced by affiliate commissions, meaning the cards ranked highest are not necessarily the best cards for your specific situation, they are the ones paying the highest referral fee.
Using AI to find the best credit card for my spending felt like a way to cut through that noise with my actual numbers rather than someone else’s incentives.
What I actually did
I downloaded several months of credit card and bank statements as PDFs. Most banks let you do this directly from your account dashboard under statements or transaction history.
Then I opened Claude and pasted in the transaction data with a clear prompt. I asked it to categorize every transaction into spending categories, calculate what percentage of my total spending fell into each category, and then use that breakdown to evaluate which credit card rewards structure would have earned me the most back over that same period.
That last part is the key step most people skip. It is not enough to know what you spend. You need to know what your spending pattern is worth to different card reward structures, and that calculation across dozens of card options is exactly where AI earns its keep. This is the core of how you can use AI to find the best credit card without relying on biased comparison websites.
What the AI found about my spending
The categorization step produced a clear picture I had never actually looked at before. My spending broke down roughly like this across the months I analyzed: a significant portion on software and SaaS subscriptions for my side projects, a meaningful amount on food and dining, some on travel and transport, and the rest scattered across general purchases.
The card I had been using rewarded general purchases at a flat rate with no category bonuses. That structure makes sense if your spending is genuinely random and spread evenly. Mine was not. I had clear concentrations in specific categories, which meant a card with category multipliers would have outperformed my flat-rate card significantly over the same period.
How to use AI to find the best credit card for your spending pattern
Once I had my spending breakdown, I asked the AI to model the rewards I would have earned using several different card structures across the same transaction history. I gave it the rewards rates and category bonuses for the cards I was considering, and it calculated the effective cash back or points value for each one based on my actual numbers.
This is something you could technically do in a spreadsheet, but the AI handled it faster and flagged things I would not have thought to check myself. It pointed out that one card I was considering had a higher rewards rate on dining but a higher annual fee that would have taken 14 months of my actual dining spending to break even on. That kind of context changes the decision significantly and is the sort of calculation that gets buried in fine print if you are comparing manually.
What I switched to and why
Based on the analysis, I switched to a card with stronger category bonuses on the spending areas where I actually concentrate most of my money. The AI estimated that over a 12 month period at my current spending patterns, the new card would earn meaningfully more back than my old one, enough to cover the annual fee comfortably and still come out ahead.
I am not going to name the specific card here because card terms, sign-on bonuses, and rewards structures change frequently enough that whatever I switched to may not be the right answer for you by the time you read this. The point of this post is the process, not the product recommendation.
How to do this yourself
If you want to use AI to find the best credit card for your own spending, here is the prompt structure that worked for me:
“Here are my transactions from the last three months. Please categorize every transaction into spending categories and calculate the percentage breakdown of my total spending. Then, based on this breakdown, evaluate which of these credit card reward structures would have earned me the most value: [list the cards and their reward rates you want to compare]. Factor in any annual fees when calculating net value.”
The more specific you are about which cards you want compared, the more useful the output. Going in with a vague “what is the best credit card” question produces generic advice. Going in with your actual spending data and a defined shortlist of cards to compare produces something genuinely actionable.
One important caveat
Before you use AI to find the best credit card for your situation, there are a few things worth knowing. AI assistants do not have real-time access to current card offers, current sign-on bonus terms, or your actual credit score eligibility. The analysis is only as current as the card information you provide. Always verify the current terms directly with the card issuer before applying, since promotional rates and annual fees change regularly.
Also, do not paste full card numbers, Social Security numbers, or sensitive account credentials into any AI chat tool. Transaction descriptions and amounts are fine. Sensitive identifying information is not.
The honest result
This was one of the more useful things I have done with AI this year, not because it was complicated but because it replaced a decision I had been avoiding for years with a clear, data-driven answer in under an hour. Using AI to find the best credit card for your spending is genuinely straightforward once you have your statements downloaded and a clear prompt ready.
The card I had been using was not bad. It just was not optimized for how I actually spend money. That gap, multiplied over years, adds up to a real amount of money left on the table. If you have been putting off the decision to use AI to find the best credit card for your spending, this process is the lowest friction way I have found to finally do it properly.
Have you used AI to evaluate your credit card setup? I would love to hear what you found in the comments below.