What a controlled 30-day AI pilot should prove
A good pilot proves that one workflow can be controlled, reviewed, and evidenced without slowing the team into paralysis. It does not need to prove every future use case in the first month.
Choose one workflow and one clear boundary
A pilot should focus on a workflow that already matters. That usually means a document-heavy or approval-sensitive path where the lack of reviewability is already visible. The scope should be narrow enough that the team can decide what worked and what did not inside 30 days.
Prove the control path works in practice
- Inputs are checked before AI action.
- Approval triggers behave consistently when the boundary is crossed.
- Failures are explicit and safe instead of hidden.
- Teams can explain what happened without reverse-engineering logs.
Prove the evidence is usable later
Pilot evidence should be reviewable by a buyer, risk lead, or auditor. If the output cannot support a later conversation about policy, approval, or document handling, the pilot has not proven enough.
Do not try to prove scale before control
The first pilot is not where teams should prove every model, every department, or every future route. The job is to prove that one governed path is real, reviewable, and worth expanding.
Related docs
Where to go next
A good pilot earns trust by proving one controlled path clearly, with evidence that the workflow can be reviewed later if someone asks what happened.