Kill criterion
A condition defined in advance that, if met, retires an AI use (for example, "if the omission rate exceeds X, we stop"); paired with a re-test date, it lets an organization walk back a bad automation as a planned move rather than an embarrassing reversal.
Defined in 3 GAGE programs, which carry 7 distinct definitions of it. The wording above is taught in AI Literacy & Professional Conduct.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A specific, predetermined, measurable condition that, if not met during a pilot or trial, results in stopping further investment in that technology, agreed upon before the pilot begins so the decision is not made under the influence of sunk cost once results start arriving.
A condition defined in advance that, if met, retires an AI use (for example, "if the omission rate exceeds X, we stop"); paired with a re-test date, it lets an organization walk back a bad automation as a planned move rather than an embarrassing reversal.
A specific, pre-agreed outcome that means "this does not work, we stop," decided before a pilot starts so that sunk cost and emotion cannot talk you into continuing a failing automation. The discipline the McDonald's rollout most visibly lacked.
A pre-agreed, specific condition (for example, "yellow or red on production-readiness for three consecutive weeks") that triggers ending an initiative, set before the pilot starts so the decision is not left to in-the-moment sentiment.
A specific, measurable, pre-committed condition (a number with a time window and a named owner) that mandates ending an initiative. Set before launch, when judgment is still objective, so it will actually fire.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- When NOT to Use AI: Decision Framework and Technical Debt Risk · Practical AI Workflow Design and Prompt Engineering, AI Literacy & Professional Conduct
- Why Transformations Fail, and How Not To · AI Literacy for Decision Makers, Business AI Transformation
- Current-State Process Mining · Diagnose the Organization, Business AI Transformation
- Measuring and Communicating Value · The Economics and the Business Case, Business AI Transformation
- Pilot Strategy and Proof-of-Concept Design: Your Pilot Design Brief · Implementation from Pilot to Scale, Business AI Transformation
- Building Learning Organizations · Measure, Sustain and Evolve, Business AI Transformation
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.