What I’m working on is the opposite of that. I want to free humans from boring, repetitive finance work so they can use their time for higher-value and more creative things.
While building an “AI CFO” for small businesses (LayerNext), I’ve learned a few things that changed how I see bookkeeping:
Most of bookkeeping is repetitive and under-optimized. Everyone says “90% of the work is repetitive,” but we still hire bookkeepers and bookkeeping firms. Most small businesses I talk to pay around $300–$800 per month just for bookkeeping. Even after paying that, I really doubt every single transaction is recorded in the most tax-optimized way. There are hundreds of transactions, constant government tax rule changes, and limited time.
Current automation is stuck at rules you manually define. Tools like QuickBooks can categorize transactions based on rules you create. That’s it. As soon as something new comes up, you still need a human to either, create a new rule, or manually enter and categorize it.
And even when you hire a human bookkeeper, you still end up doing half the work anyway: sending receipts, answering clarification emails, chasing missing information.
Invoice and expense capture can be 100% automated, even with edge cases In practice, invoice and expense capture is the easy part. With decent models, you can get 100% accurate capture from receipts, PDFs, emails, etc. Edge cases are solvable with better parsing and validation, not more humans.
Reconciliation is the hard part, but reasoning models are getting very good. This is where things get tricky: - multiple invoices paid in a single payment - partial payments - refunds, chargebacks, etc.
For example, imagine a consulting company issuing several invoices to the same customer and receiving one lump-sum payment. We’ve had success using deep research like reasoning to match payments to invoices and handle those cases automatically.
AI can sometimes care more about details than a human. One moment that surprised me.We had a credit card transaction with no receipt.
The question was whether it should be classified as “office expense” or “meals and entertainment” (in Canada these have different tax treatments). When I checked trace of the agent, it looked up the vendor online to understand what they actually sell, checked CRA tax rules and then picked the GL account that maximized the tax benefit for the company.
I’m not sure many manual bookkeepers consistently do that level of research when they’re trying to reconcile 500+ transactions and half the receipts are missing.
My goal is to build a fully automated financial assistant that can close the books without a CPA or bookkeeper, with ~99% accuracy across all transactions, and with the explicit goal of maximizing tax benefits within the rules.
Other outcome is accurate rea-time books can generate good insights to grow the business.
So I don’t see a good reason why small businesses should pay hundreds of dollars per month for humans to do mechanical work that machines can now do, often more consistently and with better attention to tax details.
Curious how others see this, especially CPAs and engineers who have built accounting tools. Is there a fundamental reason we need humans in the loop for the majority of small business bookkeeping, or is it mostly inertia and habit?