Somewhere right now, a business owner is spending a Saturday matching bank transactions to receipts by hand. AI can do most of that work in minutes. It can also confidently make mistakes no one notices. The goal isn't to choose between people and AI. It's to give each the work it does best.
Where AI helps most
- Categorizing transactions. AI can suggest how to code routine transactions based on past patterns, leaving people to handle the exceptions.
- Matching reconciliations. Matching bank and card activity to the books is repetitive, rule-based work that automation handles well.
- Reading documents. Pulling data from invoices, receipts, and contracts saves typing and reduces errors from manual entry.
- Explaining changes. AI can flag unusual swings between months and draft a first explanation for a person to confirm.
- Answering questions. Asking plain-language questions about your data, such as "which customers are paying slower than last quarter," gets answers in minutes instead of hours.
- Testing scenarios. Trying different assumptions in a forecast becomes faster, so you can look at more options before deciding.
The guardrails that matter
- A person reviews and owns every output. AI drafts and suggests. Someone accountable approves what goes into the books and the reports.
- Protect sensitive data. Don't paste financial or personal information into consumer AI tools. Use tools with business data agreements, and know where your data goes.
- Keep an audit trail. You should always be able to see what changed, when, and who approved it.
- Check accuracy regularly. Spot-check the AI's work, especially early on and after any process change.
- Start small. Automate one well-understood process, measure the results, then expand.
What should stay with people
Judgment calls belong to people: accounting estimates, unusual transactions, decisions about how to apply accounting rules, and the final sign-off on financial statements. AI can gather information for these decisions, but it shouldn't make them.
How we use it
We use AI to speed up the repetitive parts of the close and to spot issues sooner. Every number we deliver is reviewed by an experienced person who is accountable for it. The result is faster work without giving up control.
We'd automate one boring, well-understood task, check every result for a month, and only then rely on it. And we'd never put financial data into a tool without knowing exactly where that data goes.