AI Is Fast at Your Books. Here's What It Still Can't Do.
AI can sort through transactions quickly. It can suggest categories, pull details from documents, and help with parts of a month-end close. That can save time.
But speed is not the same as understanding. And a suggestion is not the same as a reviewed, reliable set of books.
I see AI as a useful assistant for routine work. I also believe judgment, context, and control still belong in the process. Here’s what that means for your business.
Where AI can save time
Bookkeeping includes many repeatable steps. A transaction comes in. A receipt is matched. A familiar expense gets a category. A report is prepared for review.
AI tools can help move through that routine work quickly. They can extract information from receipts, group similar transactions, flag items that need attention, and prepare a first pass of reports. For a business with steady, familiar activity, that first pass can be useful.
Recent benchmark results show how quickly these tools are improving. Mercor tested an AI model and licensed accountants on four simplified month-end exercises. The model completed all 20 attempts correctly. Each exercise focused on locating figures in working files, doing calculations, and presenting results. That is an impressive result for a specific, structured task. It is not proof that AI can manage every business’s books or handle every close without review. The full benchmark summary explains what the test included, and what it left out.
A separate accounting benchmark reported a 100% score for transaction classification by one model. That result also belongs to a specific test, not a promise that every transaction will be categorized correctly in your books.
The practical takeaway is simple: AI can be fast and capable at defined tasks. It can help prepare the work. It does not remove the need to check whether the work makes sense for your business.
Why a correct-looking answer may still be wrong
Numbers need context. A payment to a familiar vendor may be routine. A payment to the same vendor for twice the usual amount may need a question. A deposit may look like income, but it could be a transfer between your own accounts, a loan, or a customer payment that has already been recorded.
AI can use the information it sees. It may not know what is missing.
That gap matters because AI can produce information that looks confident but is inaccurate. In a survey of 100 CFOs covered by the Journal of Accountancy, 86% said their finance teams had encountered inaccurate or hallucinated AI-generated data. The survey also found that two-thirds considered human oversight very or extremely important for accuracy. Read the survey coverage.
There is also a difference between a category that is technically plausible and one that is right for your books. A charge might fit a broad expense category. But is it a business expense? Is it a duplicate? Does it need to be split between the business and personal portion? Those questions often require details that are not in the transaction description.
A useful assistant can make the first pass. A thoughtful review catches the parts that do not fit.
Keep control of what an AI tool can change
Some tools only prepare suggestions for a person to review. Others can connect to accounting software and make changes. That difference matters.
A security researcher documented an AI agent connected to QuickBooks in a controlled test. During review, the agent made no changes. But after it received an instruction to fix a duplicate transaction, it made edits without asking for confirmation. The test used a sandbox company with made-up records, not a business’s live books. Still, it shows why access settings deserve attention. Read the test and its limits.
AI tools are beginning to offer different levels of access, including read-only options, permissioned writing, approval steps, and audit logs. The labels and capabilities vary. Before connecting any tool, check what it can actually do in your accounting system.
Three practical settings can help keep the process orderly:
Prefer read-only access. Let an AI tool review and suggest before you allow it to create, edit, or delete transactions. Confirm that “read-only” means it cannot change the ledger. If a tool requires write access, look for a clear approval step before any change reaches your books.
Test in a sandbox. Use sample or duplicate data first. See what the tool suggests, what it changes, and how it handles an unclear transaction. Do not use a live accounting file as your first test.
Review the audit log. Check who or what made changes and when. Look for edits you did not expect. An audit log helps you understand what happened, but it is not a replacement for limiting access in the first place.
These are straightforward steps. They give you a clearer view of what the tool can see and do. They also help keep your books in order as you try new technology.
Where I still want a human in the process
At month-end, someone should review the close before relying on the reports. That review is more than checking whether the software has filled in every category. It means looking for anything that needs a question or a second look.
A human reviewer can notice:
A duplicate payment that should not be counted twice.
An unfamiliar vendor that needs context.
A deposit that may be a transfer, loan, or customer payment.
A category that seems reasonable but does not reflect how the business actually uses the purchase.
A sudden change in an expense, balance, or sales pattern.
A bookkeeper can also ask you a practical question: “What was this for?” That small pause can make the difference between a tidy-looking report and a dependable one.
The person reviewing the books also needs to know what information to verify against receipts, statements, invoices, and other records. The numbers should be traceable to their source. If something cannot be confirmed, it should be set aside for clarification rather than quietly treated as settled.
That is why I think of AI as helping with the typing, sorting, and first pass, not taking responsibility for the final numbers. The technology can support the process. A person still needs to understand the business, resolve uncertainty, and approve the work.
This balance is becoming part of the wider conversation about responsible tax and finance technology. In September 2026, the AICPA and former IRS Commissioner Danny Werfel announced a council on responsible AI in tax administration. The focus is not simply on what AI can do. It is also on how people can use it responsibly.
A calm, practical way to use AI
You do not need to choose between using AI and keeping a person involved. You can use technology to reduce repetitive work while preserving human review where the details matter.
I also keep an eye on how these tools handle your information, what permissions they request, and whether their work can be reviewed. A Financial Cents survey of 486 bookkeeping and accounting professionals found that 95% of firms were using or exploring AI, while only one in five reported measurable return on their investment. Adoption is moving quickly. Good controls and useful results still depend on thoughtful implementation.
At Jenni’s Business Services, we focus on accurate books and clear guidance, not on using technology for its own sake. I help clients keep their records organized, review the details, and understand the next step without feeling overwhelmed. If you would like support with your bookkeeping or tax preparation, I’m here to make the process feel more manageable.
AI is a tool, not a replacement for judgment. The right setup is AI doing the typing and a human doing the thinking.
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