Build a pilot that answers a real question.

Name the outcome

Start with the work you want to improve. A useful pilot might prepare a better review pack, coordinate a specific handoff or connect an equipment alert to an inspection process.

Avoid defining success only as the presence of an AI agent. The important question is whether the resulting workflow helps the people responsible for it.

Choose a representative boundary

Limit the systems, users, data sources and actions in the first version. The boundary should be small enough to test and real enough to reveal the operating constraints.

Agree the review criteria

• Is the information relevant and grounded in approved sources?
• Is the next step appropriate to the task and the agent's authority?
• Does the work reach the right person with enough context?
• Are errors and missing information visible?
• Can the team resume the existing process when needed?

Test exceptions early

Use cases where a source is unavailable, the request is incomplete or a connected system returns something unexpected. Those cases often reveal requirements that a polished demonstration will miss.

Review with the people doing the work

Ask operators and reviewers what they trusted, what they corrected and where the process still caused friction. Use those observations alongside the agreed evaluation criteria.

Decide what happens next

A pilot can justify expansion, identify a narrower useful scope or show that more integration work is needed. Each is a useful result if it is based on evidence. Production readiness comes from making that decision explicitly, with clear operational ownership.