THE PLAN MUST CONNECT TO THE REAL SYSTEM
A post-market monitoring plan should be tied to the high-risk AI system, version, intended purpose, deployment conditions and provider responsibilities rather than existing as a generic policy document.
High-risk AI governance does not end when the system enters the market or service. Post-market monitoring must connect real-world performance signals to evidence, accountable review, corrective action, incident pathways and revalidation when the system or its risk state changes.
Use the current consolidated Regulation as the controlling source. Article 72 addresses providers' post-market monitoring system and plan for high-risk AI systems, while related incident, corrective-action and other duties are governed by their applicable provisions.
Start with the actual system, role, use case and evidence boundary. The same regulation can produce different obligations for different actors and systems.
A post-market monitoring plan should be tied to the high-risk AI system, version, intended purpose, deployment conditions and provider responsibilities rather than existing as a generic policy document.
Performance data, complaints, incidents, drift indicators, user feedback and other monitoring inputs should retain source, time, context and relationship to the system state so they can support a defensible conclusion.
A dashboard is not governance if nobody has defined what signal requires investigation, restriction, corrective action, escalation, reporting or revalidation—and who has authority to act.
Model updates, configuration changes, new uses, changed data, incidents and corrective actions can alter the evidence supporting the previous system state. Preserve the old baseline and establish the new one.
The goal is not merely to reach an answer. It is to preserve what facts, evidence, scope and limitations supported that answer at that time.
Record system identity, version, intended purpose, expected performance, deployment context, known risks and the evidence supporting market-entry or service-entry state.
Identify what data will be collected, where it originates, how often it is reviewed, who owns it and what conditions require investigation or escalation.
Connect monitoring signals to investigations, decisions, incidents, corrective actions and reporting pathways with identified authority and preserved chronology.
When the system or evidence changes materially, determine whether the prior risk, conformity or readiness position still stands and preserve the basis for the new state.
Choose the smallest operating tier that fits the portfolio today. Upgrade when system count, team size or governance scope actually requires it.
Keep a living system-level evidence record with obligations, gaps, versions and revalidation state.
START EVIDENCE PASSPORT →Coordinate evidence, owners, documentation, incidents and team compliance work in one governed workspace.
START COMPLIANCE WORKSPACE →Operate broader high-risk, GPAI, FRIA, post-market and material-change governance across a growing portfolio.
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START INSTITUTION →Use the free classifier to establish the system, intended purpose, possible actor role, EU exposure and unresolved facts. When continuing evidence infrastructure is needed, paid access begins at $19 per month. Independent human readiness review remains a separate service.
For high-risk AI systems, Article 72 establishes a post-market monitoring framework under which providers collect, document and analyse relevant data about system performance throughout the system lifetime, subject to the current legal text and applicable route.
Article 72 requires the post-market monitoring system to be based on a plan, and the plan forms part of the technical documentation referred to in Annex IV. The precise requirements should be checked against the current consolidated Regulation and applicable implementing material.
The relevant data depends on the system and risks, but operational evidence can include performance signals, incidents, complaints, user or deployer feedback, drift, changes, interventions and other information needed to evaluate continuing compliance and risk.
No. Monitoring is the continuing collection and analysis function. Serious-incident reporting is a separate consequential pathway that can be triggered by qualifying events. The records should connect when a monitoring signal becomes an incident or reporting issue.
Article 72 describes monitoring throughout the lifetime of the high-risk AI system. The concrete monitoring design should reflect the system, intended purpose, risks and applicable legal requirements.
No. TA-14 can structure monitoring evidence, provenance, chronology, gaps, authority, corrective action and revalidation state. The provider and other competent actors retain their legal responsibilities.
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