Choose a workflow with an accountable owner
Start with a measurable operational problem and a team that owns the result. Establish the current cost, delay, and error rate. Agree what success would change for that team before choosing a model or building a demonstration.
Budget for operations
Production work includes permissions, evaluation, monitoring, exception handling, and changes to the process around the system. Estimate the human effort that remains after automation. A pilot can look inexpensive when the team running it absorbs that work informally.
Expand on evidence
Roll out to a bounded group, compare outcomes, and inspect failures before widening access. Keep a rollback route and a named decision-maker. Scale the workflow that works, rather than assuming every AI use case should inherit the same architecture.