The useful outcome
Write a bounded pilot plan with a baseline, test set, human checks, stop rule, and decision date.
Good first-project signals
This approach is a good fit when…
- One repeated task has a clear input and reviewable output
- The existing result can be measured
- The team can keep a manual fallback during the test
State the question the pilot must answer
Use a testable question such as: “Can assisted drafting reduce preparation time without increasing corrections?” Name the users, input types, output, and excluded cases. Avoid goals like “see what AI can do,” which provide no decision rule.
Record the baseline and test set
Measure the current process before introducing the tool. Build a representative set with common cases, incomplete inputs, edge cases, and situations that should be escalated. Keep the set stable enough to compare changes between versions.
Define review, access, and fallback
Assign who approves output, what evidence they check, where feedback is recorded, and what happens when the tool fails. Limit access to the minimum data and actions needed for the test. Keep the old process available throughout the pilot.
Set a decision date and stop rule
Choose when the team will review results and who can approve expansion. Pause for harmful output, unacceptable error patterns, privacy or security concerns, excessive review effort, or failures that cannot be detected reliably.
- Expand only after the measured result meets the threshold
- Revise when the problem appears fixable within the pilot
- Stop when risk or total effort outweighs the value
Use it with your team
Pilot charter
Keep this to one page and approve it before launch.
- Business question and current baseline
- Included users, inputs, and volume
- Explicit exclusions
- Human review and escalation owner
- Success measures and thresholds
- Stop conditions and manual fallback
- Start date, review date, and decision owner
Measure what matters
What to track
- End-to-end time including human review
- Material error and correction rates by case type
- Completed outcomes—not just model output quality
Common traps
What to avoid
- Changing scope or success criteria halfway through
- Testing only polished, easy examples
- Rolling out because the demo felt impressive
Want a second set of eyes?
Turn the guide into a practical next move.
Have a pilot idea but need help making it measurable and safe? We can help you define the scope, checks, and first decision.