What is Postmarket Performance Evaluation?
Postmarket performance evaluation is the ongoing monitoring and assessment of an AI system’s behavior, outputs, and risk controls after it has been deployed. It is significant because many regulatory frameworks require organizations to detect degradation, bias, safety issues, or cybersecurity problems once the system is in real-world use.
In Depth
In practice, postmarket performance evaluation means collecting and reviewing operational data to confirm that the AI system continues to perform as intended under actual conditions. This can include drift monitoring, incident tracking, complaint analysis, logging review, and periodic reassessment of accuracy, safety, fairness, and robustness against changing user behavior or data distributions.
For compliance teams, the key value is proving that governance does not stop at launch. The requirement is especially important in regulated sectors such as healthcare and finance, and it appears explicitly in lifecycle oversight expectations under the EU AI Act for certain high-risk systems, in medical device regulation practice, and in broader management frameworks such as ISO/IEC 42001, NIST AI RMF, and DORA-aligned operational resilience programs where model performance can affect service continuity and harm detection.
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