Finance and accounting teams spend a large share of their time on work that is necessary but repetitive: reading invoices, matching transactions, chasing missing receipts, answering the same questions from colleagues, and preparing recurring reports. That makes finance a strong candidate for AI.

It is also a function where errors are costly and accountability matters. The right approach uses AI to prepare, check, and explain, while people approve and remain responsible. Here is how.

1. Invoice and receipt processing

AI can read invoices and receipts in different layouts, extract supplier, amounts, tax, dates, and line items, and prepare entries for review. It can also flag likely duplicates or invoices that do not match a purchase order.

  • Make it work: start with your most common suppliers and formats, and measure extraction accuracy on real documents.
  • Control: a person approves entries before posting, especially above set amounts.

2. Expense review

AI can check expense claims against your policy, such as missing receipts, unusual amounts, or categories that do not match the description, and highlight items for the reviewer instead of the reviewer checking every line.

3. Reconciliation support

Matching bank transactions to invoices and payments is often slow when descriptions are inconsistent. AI can suggest likely matches and explain why, leaving the accountant to confirm or correct them.

4. Answering internal finance questions

"How do I submit an expense?", "When is the reporting deadline?", "Which cost center should I use?" An assistant grounded in your finance policies and procedures can answer colleagues quickly, with links to the official documents.

5. Reporting and commentary

AI can draft the narrative for monthly reports, explaining the main changes against budget or last month, based on figures produced by your accounting system.

  • Control: numbers must come directly from your systems, never typed freely by AI, and the finance lead reviews conclusions before they are shared.

6. Supplier and customer communication

AI can draft routine messages such as payment reminders, requests for missing documents, or replies to common supplier questions, for a person to review and send.

Controls that matter in finance

  • Segregation of duties. AI should not both prepare and approve the same transaction. Keep human approval for payments and postings.
  • Audit trail. Record what the AI extracted, suggested, and changed, and who approved it.
  • Thresholds. Require extra review for high amounts, new suppliers, or unusual patterns.
  • Accuracy testing. Keep a set of real documents with known correct values and test against it when anything changes.
  • Data protection. Financial and personal data is sensitive. Know where it is processed and stored, and limit access.
  • Professional judgment. Tax treatment, accounting policies, and regulatory reporting remain decisions for qualified people.

Example: supplier invoices

A small finance team could start by using AI to extract data from invoices sent by its 20 most frequent suppliers. Each extracted invoice appears in a review queue, with mismatches against purchase orders highlighted. The accountant approves or corrects each one before it is posted. After a few weeks, the team can compare time spent and correction rates with the manual process. This is an illustrative example; the right starting point depends on your volume and systems.

The bottom line

AI can remove much of the manual effort in finance, but only within a framework of approvals, records, and testing. Let AI prepare and highlight; let people approve and decide.

If you want to explore AI for your finance processes with the right controls in place, see our AI agents and knowledge assistant service or email us.