What you will learn
Acceptance criteria, Cost of errors, Sensitivity analysis, Scope boundaries, Decision gates.
Engineering the capability
A pilot should resolve a specific uncertainty: whether a solution improves an important workflow under real constraints. Define the audience, tasks, duration, data, and stop conditions. Agree which outcomes require human review and which actions remain outside scope.
Estimate value using transparent assumptions. Include reviewer time, failed attempts, infrastructure, support, and integration maintenance. A reduction in drafting time is not necessarily a reduction in total handling time. Show a range of outcomes rather than presenting a single optimistic number as fact.
Separate hard acceptance gates from goals. Permission isolation may be non-negotiable, while response latency has a target and an escalation path. Establish the decision process before the demo so stakeholders do not substitute enthusiasm for evidence.
Worked case
A team handles 1,000 tickets per week. Drafting assistance saves two minutes on 40% of cases but adds one minute of review to those cases. Gross net time saved in this simplified model is 400 minutes, before rework and operating effort. If acceptance falls to 20%, that becomes 200 minutes. State these assumptions and validate them in the pilot.
Put it into practice
Continue with the next lab: build a pilot scorecard and sensitivity table. Build the artifact, record the failure cases, and explain the tradeoff before moving on.