A Production Readiness Review for an AI system
Short answer: A Production Readiness Review checks that an AI system has a boundary, owner, evidence and an exit path before real users depend on it. It is not a promise that a model stays accurate forever.
Gates to pass
| Gate | Minimum evidence |
|---|---|
| purpose/acceptance | use case, metric, stop condition and approver |
| data/security | data flow, permissions, retention and incident path |
| reliability | health signal, capacity, backup/restore and rollback |
| delivery/ownership | inventory, versions, licences, runbook and receiving owner |
Review the architecture and assumptions with Solution Architecture, and separate payload, logs, updates and support in the Trust Center.
The output
The report should mark what is proposed, tested or supported, with limitations, open work, owners and the next review date. A failed gate can correctly lead to another pilot or no-go.
Limitations
One review does not replace monitoring and maintenance after go-live. Evidence from one pilot site does not cover every site.
Read next
Why an AI POC works in a demo but fails in productionWhat to maintain every month after an AI go-liveOpen-source AI is not free: the costs and responsibilities to planContinue with the decision context
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