How does governed AI move from pilot to operations?
A pilot becomes an operating service only after the workload, evidence, authority, failure modes, acceptance thresholds, infrastructure, recovery, and service owner are explicit. Production readiness is not “the demo worked.” It is repeatable performance on representative cases inside a controlled release boundary, with a safe way to stop and recover.
Reviewed 12 October 2026 · Readiness is workload-specific and must be rechecked after material change.
Promote evidence—not enthusiasm.
Each gate needs a named owner, observable evidence, and an explicit pass, experiment, hold, reframe, or stop decision.
Signals that the system is not ready.
The demo used hand-picked cases.
A persuasive example does not establish representative performance, known failure rates, or acceptable behaviour under pressure.
No one owns the exceptions.
If the system fails, stalls, or encounters missing authority, a named person and a safe route must exist.
The AI can act beyond its evidence.
Consequential tools and writes need explicit permissions, validation, approval gates, logs, and rollback.
Material changes bypass evaluation.
New models, prompts, sources, tools, users, infrastructure, or policies can change the risk and must trigger retesting.
Turn the successful demo into an acceptance record.
Define representative cases, thresholds, authority, recovery, service ownership, and the narrow first release.