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Invoice processing is a near-perfect AI automation target: high volume, structured output, clear right answers, and painful to do by hand. Modern models read PDFs, scans, and email bodies directly — the work is in the validation and exception design around them, not the extraction itself.
Route every invoice to one place — a dedicated inbox or upload folder — so the pipeline has a single entry point. Chasing invoices across personal inboxes kills automation before it starts.
Define the exact fields you need (vendor, invoice number, date, line items, tax, total, currency) and have the AI return that structure for every document. Reject free-form summaries; you want rows, not prose.
Machine-check what can be machine-checked: line items sum to the total, the vendor exists in your system, the invoice number isn't a duplicate, amounts are within expected ranges for that vendor. Rule failures become exceptions, not silent errors.
Clean invoices flow straight to your accounting system; anything that fails validation lands in a review queue with the document and the AI's reading side by side. Humans handle the exceptions, which is the only part still worth their time.
Pull a random sample of straight-through invoices each month and check them by hand. Extraction accuracy drifts as vendors change formats, and a monthly audit catches it while the fix is still cheap.
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Email a PDF invoice in, structured line items out to your sheet.
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