How to Choose an AI Bookkeeper
Judge an AI bookkeeper by four things: how it handles invoices it cannot read (it should ask, not guess), whether you pay per completed invoice or per month regardless, what it does with your data, and whether a human can review its work. Demos always look perfect — real supplier invoices do not.
The market for AI bookkeeping tools is crowded and the marketing sounds identical: "automated," "AI-powered," "seamless." The differences that matter only show up on real invoices — the smudged photo, the supplier with no VAT number, the duplicate you did not catch. This guide gives you a concrete way to evaluate any AI bookkeeper in an afternoon, using your own invoices, before you commit.
Before you start
A batch of 15–20 real supplier invoices from the last month (mix of clean PDFs, photos, and at least one awkward one), and a short list of 2–3 AI bookkeeping services to test.
Steps
- 1
Send the same test batch to every candidate
Forward your 15–20 real invoices to each AI bookkeeper you are evaluating — the exact same set. This is the only fair comparison. A polished demo on the vendor's chosen invoices tells you nothing about how it performs on your suppliers, your formats, your edge cases.
💡 Include at least one handwritten delivery note and one invoice in a foreign language. These separate the tools that ask from the tools that guess.
- 2
Check field-level accuracy, not just "it processed"
"Processed" is meaningless. Open each result and check every field: supplier name spelled correctly, date in the right format, invoice number with no dropped characters, amount matching the PDF to the cent, VAT rate correct for that supplier. One wrong VAT rate across 200 invoices is a real problem.
- 3
Watch what happens on the awkward invoice
The most important invoice in your test batch is the awkward one — the smudged photo, the two-in-one PDF, the supplier with an unusual VAT rate. Does the tool ask you, or does it silently pick a value and move on? An AI bookkeeper that never asks is either perfect (unlikely) or guessing (likely). You want the one that asks.
- 4
Understand the pricing model — per invoice or per month
Two models dominate: per-invoice (you pay for each completed invoice, like Nika at {price}) or per-month (flat fee regardless of volume). Per-invoice means you pay only for work done and the provider has incentive to finish. Per-month means you pay the same whether 5 or 500 invoices are processed — check what "processed" actually means in that model.
💡 Ask what happens to invoices the tool cannot complete. If you still pay for them under a monthly plan, the incentive is misaligned.
- 5
Ask where your data goes and who can see it
Your supplier invoices contain supplier names, bank details, pricing — sensitive business data. Ask: where is the data stored, is it used to train the AI on other customers' data, can a human at the provider see it, and what happens to the data if you leave. A provider that cannot answer these clearly is a risk.
- 6
Check whether a human can review and override
The AI bookkeeper should output to a place where you or your accountant can review, edit, and override any field. A black box that files directly to your final records with no review path is dangerous — one systematic error (a misread supplier name) propagates before anyone notices. Review-then-file is the safe pattern.
- 7
Test the "asked me" queue in practice
After the test batch, look at the queue of items the tool flagged for your attention. Is it a manageable list of genuine ambiguities, or noise? A good AI bookkeeper asks few, sharp questions; a bad one floods you or asks nothing at all. This queue is what you will live with daily — make sure it is usable.
Common mistakes
- Choosing based on a demo on the vendor's perfect sample invoices. Always test on your own.
- Picking the tool that "never asks" because it seems smarter — it is likely guessing.
- Ignoring data handling until after you have uploaded a year of supplier invoices.
- Forgetting to check what happens when you want to leave — data export and deletion matter.
- Evaluating accuracy as yes/no instead of field-by-field. A wrong VAT rate is a quiet, compounding error.
Verdict
Choose an AI bookkeeper the way you would hire a person: test it on real work, check the awkward cases, and look at how it behaves when unsure. Nika asks before guessing, charges per completed invoice from {price}, and lets you review every field before it lands in your books.
Questions
What is the single most important thing to test?
The awkward invoice — the smudged photo, the unusual format, the edge case. How a tool handles what it cannot read tells you more than how it handles what it can. You want one that asks, not guesses.
Should I choose per-invoice or monthly pricing?
Per-invoice pricing (like Nika at {price} per completed invoice) aligns cost with work done and means you never pay for unfinished invoices. Monthly pricing can be fine at high volume, but check whether you pay the same for invoices the tool fails to complete.