AI automation often stays active because it was once funded, rather than because it still creates value. Retirement criteria agreed early let the team stop a use case without treating it as a loss of credibility.
Measure acceptable outcomes
Define adoption, time, quality, cost and error thresholds. Generation counts do not show whether work is completed more effectively.
Include maintenance costs
Add evaluations, prompt corrections, vendor changes, review and incident handling. An inexpensive API may require expensive ongoing care.
Monitor alternatives
Compare an improved manual process, deterministic automation or another product feature. AI should not be assessed only against the old baseline.
Set a decision date
Schedule a review with an owner and predefined evidence. Without a deadline, a weak pilot quietly becomes a permanent service.
Design a responsible exit
Inform users, export useful data, revoke permissions and archive lessons. Retirement is part of the lifecycle, not abandonment.
This framework is an original DigitalNow editorial methodology.