Procure-to-pay and order-to-cash are high-volume, document-heavy and full of exceptions: ideal ground for AI, and also where fraud and payment errors live.
Accounts payable
- Capture and coding: extract header and line data from invoices in any format; suggest GL codes, cost centers and tax codes.
- Matching: two- and three-way match against POs and receipts; explain why an exception happened.
- Duplicate and fraud detection: near-duplicate invoices, changed bank details, unusual vendors.
- Supplier queries: draft answers to "where is my payment?" from the ERP status.
Accounts receivable
- Cash application: match remittances to open items, even with messy references.
- Collections: prioritize accounts by risk and value; draft reminders and summarize disputes.
- Credit: summarize customer financials and payment history for a credit decision (made by a person).
Procurement finance
- Spend analytics: classify spend into a clean taxonomy; find tail spend and off-contract buying.
- Contract terms: extract payment terms, price escalators and rebates; compare against invoices.
Controls to keep
- Bank-detail changes always go through out-of-band verification, whatever the AI says.
- Payment approval limits stay with people (or with agents only under explicit, logged limits).
- Segregation of duties: the same agent should not create a vendor, approve an invoice and release payment.
- Sample AI-coded invoices every month and track the error rate.
Measures
Cost and time per invoice, touchless rate, duplicate payments recovered, days sales outstanding, cash applied automatically, dispute cycle time.