How does AI accounts payable automation work?
An invoice arrives by email or upload. Document AI extracts supplier, dates, totals, tax and line items, going beyond plain OCR because it understands which field is which. The system then runs a two- or three-way match against the purchase order and goods receipt, proposes the ledger coding, and sends the invoice to the right approver. Clean, matched invoices flow straight through; people see only the exceptions.
AI vs rule-based AP automation: what’s the difference?
| Rule-based automation | AI accounts payable | |
|---|---|---|
| New invoice layout | Needs a new template | Usually read without setup |
| Coding | Fixed rules per supplier | Learns from past coding, asks when unsure |
| Exceptions | Every mismatch to a person | Explains the mismatch and suggests a fix |
| Fraud signals | Exact duplicate checks | Near duplicates, unusual amounts, changed details |
Ask a vendor to show the exception queue, not the happy path, because that is where your team will spend its time. It is one part of wider AI in finance.
How do we check a supplier with AI before paying it?
For Polish suppliers we built and open-sourced krs-mcp, an MCP server that lets Claude, Codex and other assistants look up a company in Poland’s National Court Register by name, KRS number, tax number (NIP) or statistical number (REGON) and read its official extract. A finance assistant can check that the NIP on a new supplier’s invoice belongs to the registered company named on it, and who may sign for it, before the first payment, as described in our krs-mcp write-up. The tools are read-only, so the assistant can verify a supplier but never change anything. The model reads the register; it does not remember a company.