AI operations
The work after an AI pilot: operating it in the real world
Production readiness depends on ownership, evaluation, escalation and change—not simply deploying the model.
Define who owns the workflow, who can change prompts or knowledge sources and what evidence is reviewed before a release. Establish evaluation examples that represent normal work, edge cases and unacceptable outcomes.
Build the operating loop
Monitor quality, latency, cost and the frequency of human intervention. Create an escalation path for users and a safe way to pause or fall back when the system behaves unexpectedly.
Keep records of material changes and review whether the workflow still solves the original problem. Production AI is an operating capability with ongoing decisions, not a pilot that happened to remain switched on.
Further reading: Australian Government responsible AI guidance ↗
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