Kill criterion
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.
Defined in 3 GAGE programs, which carry 7 distinct definitions of it. The wording above is taught in Engineering Judgment and Professional Formation.
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 module of every program is free with a free account.
- When NOT to Use AI: Decision Framework and Technical Debt Risk · Practical AI Workflow Design and Prompt Engineering, Certified AI Practitioner: Workplace Foundations
- Why Transformations Fail, and How Not To · AI Literacy for Decision Makers, Certified AI Transformation Professional (CATP)
- Current-State Process Mining · Diagnose the Organization, Certified AI Transformation Professional (CATP)
- Measuring and Communicating Value · The Economics and the Business Case, Certified AI Transformation Professional (CATP)
- Pilot Strategy and Proof-of-Concept Design: Your Pilot Design Brief · Implementation from Pilot to Scale, Certified AI Transformation Professional (CATP)
- Building Learning Organizations · Measure, Sustain and Evolve, Certified AI Transformation Professional (CATP)
- Neuromorphic computing and new sensing · Frontier and Future Horizons, Engineering Judgment and Professional Formation
Where it shows up at work
A definition is where Kill criterion starts. The lessons above teach it inside the competencies below, which are what job descriptions ask for and what the GAGE credential records. Every link here is drawn from the same careers map that builds a role's readiness check.
Builds an honest value model: baseline, measured change, cost, risk, and the projects that should be stopped.
2 lessons on this page teach it as a primary outcome.
Knows the rules on automated employment decisions, bias audits and notices, and treats hiring AI as the highest-risk use case it is.
One lesson on this page teach it as a primary outcome.
Briefs a model like a good manager: context, constraints, examples, verification, and knows when to stop delegating.
One lesson on this page teach it as a primary outcome.
Roles that hire for it
Each role page shows the full competency set, what the seat decides, and a readiness check against your own evidence.
- AI Adoption and Enablement Leadneeds working knowledge
- Chief AI Officerneeds it at depth
- AI Program Managerneeds working knowledge · 11 open postings this week
- Operations Manager, AI-readyneeds working knowledge
- AI Regulatory Counselneeds working knowledge · 14 open postings this week
- Ethical AI Specialistneeds working knowledge · 5 open postings this week
How job descriptions say it
Postings rarely use the textbook word. These are the phrases the careers map reads as asking for the competencies above.
Where the frameworks place it: NYC Local Law 144; EEOC guidance; EU AI Act Annex III employment.
One interview question about it
How would you measure the return on an AI deployment honestly, including the costs people prefer to leave out?
Asked of candidates for roi and value measurement for ai. Answering it in your own words is exactly how a GAGE topic is passed, and the credential records the pass where an employer can check it.
If you come from another field
Some backgrounds already carry this competency, and the readiness check gives credit for it.
- A business, MBA or technology management degree carries it as a claim to back up: Value and return measurement are a course you passed.
- Human resources and people operations carries it as a claim to back up: Fair-hiring review and disparate-impact awareness are HR discipline.
- A computer science or software engineering degree carries it as work you can show: Prompting and tool workflows are already in your daily work.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.