15 January 2021
8 min
Why AI POCs Fail: 12 Reasons (and Fixes) from Real Teams
POCs prove learning. Production proves reliability, ownership, and integration.
AIProductionDelivery
POCs prove learning. Production proves reliability, ownership, and integration.
Framework
- Decide the delivery mode early (API/batch/edge)
- Add evaluation gates and regression checks
- Define ownership and incident response
Pitfalls
- No decision policy (model score unused)
- No monitoring, no rollback
- No stakeholder alignment on KPI
Portfolio deliverables
- Delivery spec + KPI definition
- Evaluation suite + regression tests
- Monitoring + rollback plan
Good practice
Ship a baseline + monitoring first. Then iterate with evidence.
FAQ
How fast should a baseline be deployed?
Within 1–2 weeks if possible. Iteration beats perfection.
What’s the best first monitoring metric?
Prediction distribution shift + error rate/latency + data quality checks.
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