Most descriptions of “AI in finance” come from vendors who want to sell you a product, or McKinsey reports that price the opportunity at $2 trillion globally. Neither is a useful guide to what the actual day looks like at a 40-person business that has shipped a finance agent and is running it in production. So here’s what the day looks like for one we deployed late last year.
8:55am
The agent’s overnight batch has already run. Bank feed reconciliation against accounting system: 312 transactions processed, 297 auto-matched, 15 flagged for human review. The flagged set is in a queue waiting for the bookkeeper. None of this is exciting. It used to take her an hour every morning. Now it takes fifteen minutes of clicking through the flagged ones.
9:20am
A customer pays an invoice. The payment notification arrives via email. The agent extracts the invoice number, matches it to the open invoice in the accounting system, marks it paid, generates the receipt, sends the receipt to the customer, and updates the customer’s record in the CRM with the payment date. Total elapsed time: 22 seconds. This used to be a manual job that happened once a day at the end of the day.
9:40am
A purchase invoice comes in from a supplier. The agent reads it, extracts the line items, classifies them against the chart of accounts, checks them against the open purchase order, identifies a discrepancy (the supplier billed for a quantity higher than ordered), and routes it to the operations manager with a draft email to the supplier asking for clarification. The operations manager approves the draft and sends it. Total human time on this transaction: 90 seconds. Without the agent: probably 20 minutes.
11:15am
A staff member submits an expense report. The agent reads the receipts (image OCR), classifies the expenses, checks them against policy (one was over the per-meal limit), produces a summary for the staff member’s approval, then routes the approved version to the bookkeeper with the policy exception flagged. Bookkeeper approves the exception with a one-line note. Done.
12:30pm
Nothing happens. The agent runs no jobs at lunchtime by design, because the team didn’t want urgent flags landing in the middle of meals.
2:00pm
The CFO asks a question in Slack: “How much did we spend with vendor X in Q1?” The agent has been integrated as a Slack bot. It answers in 11 seconds, with a link to the detail. The CFO would previously have asked the bookkeeper, who would have spent five minutes pulling the report. Now the CFO asks the question whenever it occurs to her, instead of saving them up.
3:30pm
A customer queries an invoice line item via email. The agent reads the email, identifies the invoice, finds the line item, drafts a response explaining what was charged and why (referencing the original quote), and queues the response for human review because the customer’s tone suggests they may dispute it. The bookkeeper reads the draft, makes one small wording change, and sends it.
4:45pm
End-of-day processing. Cash position summary auto-generated and posted to the management Slack channel. AR aging report updated. Two customers flagged as 30+ days overdue with draft chase emails ready to send tomorrow morning. The agent doesn’t send these automatically; the bookkeeper reviews them at 9am.
5:00pm
The bookkeeper closes her laptop. She used to leave at 6:30 most nights. Now she leaves at 5. The agent has not replaced her. It has replaced the most repetitive 90 minutes of her day, and the company has used the saved time to give her ownership of the supplier relationship management work that nobody had bandwidth for previously.
The agent is not impressive. It’s a bunch of single-purpose workers stitched together by an orchestrator, each one handling a defined job that used to be done by hand. Together they save the equivalent of about 12 person-hours a week. The team likes it. The CFO trusts it. The bookkeeper protects it.
That’s what the day looks like. Not magic. Not replacement. A reliable, boring, audited improvement to a job that used to be slower and more annoying.