Predetermined Change Control Plan (PCCP)
A pre-specified, pre-authorized description of the kinds of updates an AI-enabled system is allowed to make after deployment, used in United States medical-device regulation to govern models that continue learning after release. The concept generalizes beyond medical devices: any vendor update, authorized in advance or not, should reopen an evaluation report's evidence and review trigger rather than being treated as routine maintenance.
Defined in 3 GAGE programs, which carry 4 distinct definitions of it. The wording above is taught in Certified AI Governance Professional (CAIGP).
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 pre-specified, pre-authorized description of the kinds of updates an AI-enabled system is allowed to make after deployment, used in United States medical-device regulation to govern models that continue learning after release. The concept generalizes beyond medical devices: any vendor update, authorized in advance or not, should reopen an evaluation report's evidence and review trigger rather than being treated as routine maintenance.
The FDA's formal term for a pre-specified description of anticipated future AI/ML model modifications submitted as part of a US device clearance; NMPA's 2025 to 2026 change-control instruments move toward a functionally similar mechanism without using identical terminology or an identical formal submission structure, a distinction this topic treats carefully rather than claiming cross-jurisdictional equivalence.
A plan, submitted as part of an FDA marketing submission and finalized in FDA's December 2024 guidance, that pre-describes future AI model changes and their safety boundaries, letting a manufacturer implement those changes later without an entirely new submission.
An FDA pathway, formalized in final guidance issued in December 2024, allowing a qualifying AI-enabled medical device maker to pre-specify how its model may be updated over time without a full new premarket submission for each update.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The evaluation report: evidence that your trust levels are earned, not hoped · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
- Sector-Specific Economic Analysis: Compliance Cost and Competitive Advantage · AI Economics and Impact Modeling, The AI Lobbyist: Certified AI Policy Strategist
- Health and Pharma: FDA Pathways, CMS Angles, HIPAA-Safe Talking Points · Sector Playbooks, The AI Lobbyist: Certified AI Policy Strategist
- AI in Healthcare and Life Sciences · Sector Rules: Finance to Autonomous Vehicles, Certified China AI Regulatory Professional (CCARP)
Where it shows up at work
A definition is where Predetermined Change Control Plan (PCCP) 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.
Applies GDPR, CCPA and sector rules to training data, inference, automated decisions, lawful basis, individual rights and cross-border transfer.
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.
- Chief Privacy Officer, AI privacy editionneeds it at depth
- AI Regulatory Counselneeds it at depth · 14 open postings this week
- Privacy Analystneeds working knowledge
- Chief Data Officer, data leadership editionneeds working knowledge
- AI Incident Response Leadneeds working knowledge · 1 open posting this week
- AI Compliance Managerneeds working knowledge · 2 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: GDPR; CCPA/CPRA; EU AI Act Article 27.
One interview question about it
Apply a privacy law you know to a model trained on customer records. Where is the legal basis, and where is the risk?
Asked of candidates for privacy law applied to 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.
- Privacy and data protection carries it as work you can show: Privacy assessments and lawful-basis records are your work product.
- Legal and paralegal work carries it as a claim to back up: Privacy and consumer law are usually within reach.
- A law degree (JD, LLB or LLM), no AI work yet carries it as a claim to back up: Privacy and data protection law are usually a course, not yet a file.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.