01

Choose a bounded unit of work

“Automate operations” is too broad to test. “Create an owned callback task from an eligible website inquiry” has a start, an end, and an observable result.

  • Name the trigger and completion condition.
  • Identify the person who owns exceptions.
  • Exclude unrelated systems and sensitive decisions from the first pilot.
02

Check whether the rule is stable

Automation magnifies an unclear process. If two staff members disagree about what should happen, document the policy before encoding it.

  • List the normal cases and recurring exceptions.
  • Check whether an existing-tool feature already solves the problem.
  • Use AI interpretation only where a simpler rule is not enough.
03

Set a baseline you can actually collect

Use an observable operating measure such as manual steps, time waiting for assignment, or unresolved requests. Treat revenue forecasts as assumptions, not pilot results.

  • Record the current process consistently.
  • Choose a review period appropriate to the volume.
  • Include errors, rework, and support time in the review.
04

Define the stop conditions

A first pilot should have a manual fallback. Decide who can pause it and what evidence would make the team change or abandon the design.

  • Restrict permissions and test with safe examples.
  • Keep consequential messages or record changes behind approval where appropriate.
  • Document rollback and ownership before expanding.

THE TAKEAWAY

A useful first pilot has a repeatable trigger, stable rules, sufficient evidence, a named owner, and a manageable failure path.

These are planning recommendations, not a guarantee of results, legal advice, or certification of an implementation.