Post-market monitoring
Under the EU AI Act (Regulation (EU) 2024/1689), Article 72, the obligation on providers of high-risk AI systems to actively and continuously collect and review real-world performance data across a system's operational life. The organizational counterpart of the personal frontier hour: a standing duty to keep looking.
Defined in 2 GAGE programs, which carry 5 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.
Under the EU AI Act (Regulation (EU) 2024/1689), Article 72, the obligation on providers of high-risk AI systems to actively and continuously collect and review real-world performance data across a system's operational life. The organizational counterpart of the personal frontier hour: a standing duty to keep looking.
the ongoing obligation under Article 72 of the EU AI Act (Regulation (EU) 2024/1689) for providers of high-risk AI systems to keep collecting and analyzing evidence about a deployed system's real-world performance throughout its lifecycle, rather than certifying it once and stopping.
The ongoing, documented collection and analysis of a deployed system's performance across its lifetime. Required for high-risk AI systems under EU AI Act Article 72 (Regulation (EU) 2024/1689) and expected by the NIST AI RMF Manage function. A drift monitoring plan is its operational core.
The system a provider must have in place under Article 72 to monitor a high-risk AI system's performance after it is on the market, collecting field data and feeding problems back into the risk-management system. It is Annex IV slot 9 and the mechanism that keeps the file true over time.
The EU AI Act term for a provider's ongoing watch over how a system behaves once it is in use; the automatically generated logs required by Article 12 are part of what makes this monitoring possible.
Where it is taught
The exact lessons this term appears in. The first module of every program is free with a free account.
- The board inspection: the seven-seat AI board audits the estate end to end · The Estate Audit, Certified AI Data Governance Professional (CADGP)
- Model drift: detecting the quiet degradation nobody reports · Evaluation and Trust, Certified AI Governance Professional (CAIGP)
- The conformity file: assembling the evidence for the system you shipped in Module 3 · The EU AI Act: The Executive Map, Certified AI Governance Professional (CAIGP)
- The agent audit trail: logging actions so you can reconstruct any decision it made · Agents Under Command, Certified AI Governance Professional (CAIGP)
- The weekly frontier hour: a sustainable practice for staying current for a career · Staying Current: The Frontier Discipline, Certified AI Governance Professional (CAIGP)
Where it shows up at work
A definition is where Post-market monitoring 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.
Collects, labels and preserves the evidence that a control operated, a decision was made, and a claim can be defended to an auditor or regulator.
2 lessons on this page teach it as a primary outcome.
Scopes an AI audit, sets criteria, samples, interviews, tests, writes findings with condition, criteria, cause, effect and recommendation, and tracks remediation.
2 lessons on this page teach it as a primary outcome.
Sets performance metrics, thresholds and review triggers after launch, and treats a model change, a vendor update or new data as a reason to re-check.
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 Audit Executive, AI audit editionneeds it at depth
- AI Auditorneeds it at depth · 9 open postings this week
- Senior AI Compliance Analystneeds working knowledge
- AI Compliance Specialistneeds working knowledge · 1 open posting this week
- AI Program Managerneeds it at depth · 11 open postings this week
- Security Compliance Managerneeds it at depth · 4 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: EU AI Act Articles 11 and 12; ISO/IEC 42001 Clause 7.5; Global Internal Audit Standards; ISO/IEC 42001 Clause 9.2.
One interview question about it
What evidence would you have ready before an auditor asks about an AI system, and how do you produce it as a byproduct of the work?
Asked of candidates for evidence collection and audit-ready documentation. 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.
- Compliance and regulatory affairs carries it as work you can show: Audit-ready documentation is what you produce.
- Internal audit and IT audit carries it as work you can show: Evidence evaluation is the profession.
- Project and program management carries it as a claim to back up: Decision logs and repositories are familiar.
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.