AI Dictionary › Regulation
Monitoraggio post-commercializzazione
Post-market monitoring is the ongoing activity of observing and collecting data on the performance of a high-risk AI system after it has been placed on the market or put into service, carried out by the provider to verify that the system continues to meet regulatory requirements in real-world use, which often differs from the controlled test conditions under which it was initially validated.
In practice, the provider collects and analyzes data on the system's actual use, its performance over time, any malfunction reports from users, and changes in the operating context that could alter its behavior, such as a gradual drift between the data the model was trained on and the data it encounters in production. The monitoring plan must be set up proportionally to the system's risks and integrated into the technical documentation.
For companies, post-market monitoring is not a one-off formal requirement but an ongoing operational function requiring observability tools for the system in production, processes for collecting user feedback, and the ability to intervene quickly, with updates, fixes or service suspension, when signs of malfunction or non-compliant behavior emerge.
The principle is borrowed from post-market surveillance already established for medical devices, where it has long been standard practice to monitor a product's performance even after initial approval, based on the awareness that a complex system can behave differently at scale compared to what was observed during development.
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