Invoice automation often starts with OCR, but OCR alone does not solve the finance problem. Accounts payable still needs to know whether the vendor is approved, the purchase order matches, tax is reasonable, the total is within threshold, and the right manager has approved the spend.
A useful design treats the invoice as a workflow item, not as a document conversion task.
Minimum workflow
- Monitor a finance inbox and collect PDF or image attachments.
- Extract vendor, invoice number, dates, line items, tax, currency, purchase order, and total into a fixed JSON schema.
- Validate the schema against vendor master data, duplicate invoice history, PO balance, and approval thresholds.
- Route exceptions to a finance reviewer with the source document beside the extracted fields.
- Send clean invoices to approval, then post to ERP or create an ERP-ready payload.
Where AI helps most
AI is valuable for messy layouts, multilingual invoices, email context, missing-field detection, and summarizing why a document needs review. Deterministic rules should still handle totals, duplicate checks, threshold routing, and required approvals.
Controls to add from day one
Store the original file, extracted data, validation result, approver, timestamps, and final ERP reference. Keep confidence scores visible, but do not rely on confidence alone. A low-risk small invoice and a high-value invoice should not use the same automation path.
Success metrics
Measure manual keystrokes removed, invoice cycle time, exception rate, duplicate detection, approval delay, and percentage of invoices posted without rework. If the process only extracts data but still needs the same manual chasing, the automation is incomplete.