Scenario A
Start with high-value docs: invoices, delivery notes, QC sheets, not the whole paper mountain.
Document AI needs field-level accuracy targets and exception desks. OCR without a review loop pours errors into business systems after launch.
Scenario B
Critical fields like amount, tax ID, lot need confidence thresholds and forced review.
Scenario C
When templates vary, standardize capture and layout before chasing models.
| Decision lens | Common trap or cost | Safer cut |
|---|---|---|
| Field policy | Force review on critical | Lower risk |
| Scope | High-value docs first | Do not boil ocean |
| Write path | Idempotent rollback | Stop dirty data |
Design human review into the system, not as after-the-fact rescue Put scenarios into the contract annex—better for acceptance than module names alone.
What accuracy to go live?
By field: higher for critical ones; allow machine-pass on non-critical with human on critical.
Handwriting?
Possible in limited cases with higher review rates and writing standards.
Privacy and compliance?
Encrypt images, minimize access, define retention.
Pair with RPA?
OCR structures; RPA or API posts; keep human gates on critical steps.