Change control
The rule that any material change to scope, timeline, or budget goes through a defined request with an impact assessment rather than being absorbed silently. It is the enforcement arm of the out-of-scope list, converting "can you also handle X" from a favor into a resourced decision.
Defined in 2 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in Certified AI Transformation Professional (CATP).
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.
The rule that any material change to scope, timeline, or budget goes through a defined request with an impact assessment rather than being absorbed silently. It is the enforcement arm of the out-of-scope list, converting "can you also handle X" from a favor into a resourced decision.
The discipline that governs alterations to a model or a control: a request, an impact assessment, a decision, a record, and a trigger for revalidation where the change is material.
The discipline of routing every change to a production AI system through review, testing, and rollback readiness sized to the change's risk. Rests on treating configuration as code: a behavior change is a product change.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The Operating Charter That Protects the Role · Own the AI Transformation Mandate, Certified AI Transformation Professional (CATP)
- Program Management and Execution Discipline · Implementation from Pilot to Scale, Certified AI Transformation Professional (CATP)
- Risk matrices and model governance · Quantitative Risk and Decision Science, Certified Enterprise Governance, Risk and Compliance Professional (CEGP)
Where it shows up at work
A definition is where Change control 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.
Runs stage gates, intake, decision logs and evidence repositories so a pilot cannot reach production without the required approvals.
One lesson on this page teach it as a primary outcome.
Classifies models by tier, sets validation requirements, challenges data, methodology and performance evidence, and reports aggregate exposure.
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 Program Managerneeds it at depth · 11 open postings this week
- Chief Information Officer, technology leadership editionneeds working knowledge
- VP of AI Governance and Ethicsneeds working knowledge
- Model Risk Managerneeds it at depth
- AI Model Validatorneeds it at depth
- Chief Audit Executive, AI audit editionneeds working knowledge
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: PMBOK; SR 11-7; NIST AI RMF MEASURE.
One interview question about it
Run me through delivering an AI program across legal, security, data and the business without governance becoming the bottleneck.
Asked of candidates for governed ai program and portfolio delivery. 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.
- Project and program management carries it as work you can show: Plans, RAID logs and status reports are your artifacts.
- A business, MBA or technology management degree carries it as a claim to back up: Program delivery is familiar in method.
- Model risk, credit risk and quantitative analysis carries it as work you can show: Validation reports and model inventories are your record.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.