The more accurate the data, the more likely AI is to give accurate responses. Here’s how you can prepare your books for AI use.
Keeping the books current is a good idea for many different reasons. It makes tax season less of a scramble for you and your accountant. If you bring on new crew members or a dedicated bookkeeper, it becomes easier for them to help with the finances. And it’s also what allows you to know your profitability and see how your operation is doing at any point in time.
These days, there’s another reason for operators to keep up with their bookkeeping. If you want to use AI to help with parts of your business, like financial analysis or planning, having accurate and complete data is essential. You might have heard this phrase before: “Artificial intelligence is only as good as the data behind it.”
So, how can you get your books ready to use AI? We’ll start by talking about why good data makes for better AI results. Then we’ll cover four ways you can prep your books for AI use. Finally, we’ll go over four techniques to help you check whether AI got the numbers right.
Key takeaways
If you use AI to analyze your books or answer questions about your finances, its answers are only as reliable as the bookkeeping data it has access to. That’s why it’s important to make sure your books are clean and set up first.
You can prepare your books for AI use by updating your balance sheet, checking that your categories and enterprises match the structure of your operation, tagging your transactions, and reconciling your accounts.
Many of the same steps to prep your books for AI can help you clean up the books for tax time or throughout the year.
Even when you’re confident that your books are clean, remember to check AI’s responses. Confirm the exact dates it pulled data from, compare key numbers to what’s in your bookkeeping system, and break complex requests into smaller steps.
While AI can act as an assistant as you analyze or work through business scenarios, always consult your accountant or other financial professionals you work with for official advice on business decisions and taxes.
Why does good data make for better AI results?
It might sound obvious, but when your records are accurate, the results, responses, or reports you get from an AI chat are also more likely to be accurate. After all, your books and other data you’ve shared are the basis of what AI knows about your operation.
Reminder: Protect your data by using AI with a private account, turning off settings that allow AI tools to train on your chats, and avoid sharing information that’s highly sensitive about your operation. We go through these safety tips in more detail in our first lesson on AI for financial management.
While people can gather context from different interactions in real life or online, then remember these details over time, AI often relies on the information that’s right in front of it: the apps you gave it access to, or facts you’ve told it within a specific chat.
And when it doesn’t actually know something, AI can hallucinate, confidently guessing at an answer instead of clarifying what it needs or asking for more information. (We wrote more about what that means in our glossary of AI terms.)
One way you can minimize the risk of AI giving the wrong answer is making sure the data it works from is correct and as complete as possible. So if you plan to use AI to help with financial tasks, let’s look at a few tips for prepping your books.
Robbie Gianadda, owner of Flat 12 Mushrooms in Western New York, uses AI tools to analyze data from Ambrook and help him with weekly planning.
4 tips to prepare your books for AI use
Before you ask AI to help analyze your numbers, here are a few steps you can take to check that your records are as complete and ready as they could be. You’ll notice that some of these tips can help clean up your books in general, too.
#1: Check your balance sheet
A balance sheet paints the current picture of your business’s assets, liabilities, and equity, so it’s an important part of your bookkeeping foundation. When you’re using AI, the balance sheet can help put your payments, income, or other financial records in context.
Here are some examples of what you might check:
Are all of your assets on the balance sheet, including the new piece of equipment you purchased?
Are your loans represented and up to date?
Do you see all your current assets, like your business checking account?
Is everything labeled and counted correctly?
If you use Ambrook, you can check this by going to Reports and selecting Balance Sheet. Or you can make updates directly in Accounts.
Keep reading: What Is a Balance Sheet?
#2: Clarify categories, enterprises, and projects
For many owners, categories, enterprises, and projects help them represent the structure of their operation and break down exactly where income or expenses are going: That gives them a clean and useful P&L statement.
That helps when you’re using AI too. When your categories and enterprises are clearly defined and match how you think about your business, AI can use that structure to produce results that are more useful for your business.
You can go through the chart of accounts, enterprises, or projects in your bookkeeping system and ask yourself questions like:
Are there similar categories I need to combine, or one large category I might want to split and track as two smaller buckets?
Do I have enterprises set up for every business line I want to know the profitability of?
If these categories and enterprises were created a while ago, do I know what each of them represents and do they still help me answer questions about my business today?
To review or change your categories, enterprises, and projects in Ambrook, go to Settings and find them under Tags.
Learn more: Building a Chart of Accounts That Works for You
#3: Tag transactions regularly
Once you have categories and enterprises set up the way you’d like, it’s a matter of regularly tagging all your transactions to them.
In some cases, if you try to have AI analyze the books without details on how your income or expenses are categorized, at best you might get a surface-level analysis of the numbers. At worst, AI could give you answers or reports on your spending or profitability based on incomplete (and therefore incorrect) data.
Try setting aside time to go through your ledger and tag transactions each week or every few weeks. Or, as part of our year-end bookkeeping checklist, we wrote about how you can lighten that load by automating some of the tagging.
Keep reading: What Is Enterprise Analysis and Why It Matters for Your Operation
#4: Make sure accounts are reconciled
You’ve checked the balance sheet and your categories to make sure your bookkeeping structure is correct. You’ve tagged transactions so your income and expense records are detailed. There’s another thing to review: Are your accounts reconciled through today?
If AI is going to rely on the books to analyze your operation’s financial health, you’ll want to be sure your ledger checks out with what’s on your bank or credit card statements. Go through and regularly reconcile your accounts before you use AI to answer a financial question or analyze the numbers.
In Ambrook, you can start the reconciliation process by going to Ledger and finding the Reconcile button.
Keep reading: What Is a Bank Reconciliation, and How Does It Work?
In Montana's Gallatin Valley, Ella uses AI suggestions and automations in Ambrook to help tag KB Building & Supply's transactions.
4 techniques to evaluate AI’s responses
Let’s say you’ve now cleaned up your books and asked AI to answer a question about your financial records. How can you check that it’s reading the data correctly?
Here are a few ways you can try to poke holes in AI’s responses and evaluate their accuracy against your own bookkeeping data.
#1: Ask for the data it used
When in doubt with AI, ask it to be specific about the sources it relied on. If it’s giving you a number that seems off, for example, you can first try confirming the exact time period it pulled data from.
You might phrase your prompt like this:
Give me the dates of each transaction you pulled to get this number.
List the invoices you reviewed to generate this report. What’s the exact date they were each created?
Show me the transactions you used to calculate this number, including their dates and descriptions.
This helps you assess whether AI looked at the right numbers, or answered your question using the wrong data.
#2: Compare line items with a source you trust
Another way to evaluate an AI response is by comparing specific parts of it to a known source you trust. Let’s say, for example, you asked AI to build you a financial health report that summarizes your accounts receivable, accounts payable, and monthly cash flow.
Pick a few numbers in the report that you could corroborate with your bookkeeping system. For instance:
In the report, AI states you spent $2,403 on materials and $839 on fuel this month. Does that match what you see in your P&L in Ambrook?
AI reports your expenses for the month totaled $10,359. Does that match what’s in your Analytics in Ambrook for this month?
AI says your largest open bill right now is $950. When you look through the unpaid bills listed in Ambrook, does that match?
Choosing a verifiable figure you can compare with your books makes it easier to pinpoint errors when they show up.
#3: Break complex requests into smaller steps
You can also try giving AI “checkpoints,” by breaking up your request or question into smaller pieces.
Let’s say you’re asking AI to comb through your ledger and check for miscategorized transactions. Instead of having it start on the full year right away, maybe you run the AI chat like this:
Start by asking AI to check your ledger for January 2026.
When it responds, review the transactions it flagged and confirm in your bookkeeping system whether they were actually miscategorized.
If it got some transactions wrong, explain why it was incorrect and what it should look for instead next time.
Ask AI to check your ledger for February 2026.
Repeat steps 2-4 for each month after that.
There are two benefits to this type of approach. First, it makes it easier to catch any of AI’s mistakes early on, without having to review a huge amount of information yourself. And second, since you get the chance to give AI feedback after each checkpoint, it can learn from your corrections and get more accurate as you go through the chat.
#4: Have AI spell it out for you
If something isn’t looking right in AI’s response but you can’t quite figure out where it went wrong, try asking it to show its work outright.
For example, you might prompt:
Walk me through your exact steps to get to this number. Which transactions did you use, and what was the calculation you did?
Where do you see that $45 fuel expense? What’s the description and date of the transaction?
In a similar way to #3, this can help you identify the steps or checkpoints where AI went wrong, so you can give it feedback to improve for next time. Keep in mind, however, that AI’s explanation of its steps might not always be a perfectly reliable record of what it actually did, so focus on concrete details you can check, like specific transactions and dates.
See more examples: Farm Financial Planning with AI: Examples from Two Working Ranchers
Prepare Your Books with Ambrook
Taking time to check your balance sheet, organize your categories and enterprises, tag all your transactions, and reconcile accounts gives AI more accurate and complete data to work with.
Ambrook makes it easier to keep your books clean, with automations that tag recurring transactions, built-in support for reconciliations, and reports by enterprise, location, or project. That way, your numbers are ready if you’re experimenting with AI.
Want to see how it works? Try Ambrook free for 30 days.
Resources to Dive Deeper
Review our tips on using AI safely.
Follow this year-end bookkeeping checklist for more tips on cleaning up your financial data.
Learn how Ambrook’s account managers use AI for bookkeeping.
FAQs
Can AI do accounting?
AI can help with accounting tasks, like cleaning up your categories or finding reconciling items. You’ll need to make sure the data you’re giving it to work with (your books or other context you share) is accurate. Even then, keep in mind that AI can make mistakes, so you and financial professionals you trust should always review its responses.
Do my books need to be clean to use AI?
The cleaner your books, the more accurate AI’s answers are likely to be. Untagged transactions, missing accounts, or unclear transfers could lead to incorrect numbers, because AI might not be able to read or interpret your records correctly in those cases.
How do I get my books ready for AI financial analysis?
Try to make sure your records are as complete as possible: You have your categories and enterprises set up, for example, and all or most of your transactions are tagged. Also, double-check that the books are accurate: Reconcile your accounts and make sure your balance sheet looks up to date.
Why is AI giving me a different number than my bookkeeping software?
That might be a sign that AI miscalculated something, or there’s a mismatch between what you expected AI to analyze and what it actually looked at. Try asking it to explain the exact steps it took, confirm which time period it pulled data from, or pick out specific line items and compare them to what’s in your ledger.
Can AI replace my accountant’s review?
No. While AI can answer questions about your books or check for errors in your ledger, it doesn’t have the expertise or the same context on your operation that your accountant does. Always rely on financial professionals, not AI, for official advice on topics like business decisions or taxes.
This resource is provided for general informational purposes only. It does not constitute professional tax, legal, financial or accounting advice. Consult a qualified professional about your specific situation.
