High-Risk AI Drift Detection and Compliance Monitoring (September 2026)

For high-risk AI systems under the EU AI Act, the passage argues that Article 61 requires continuous post-market monitoring rather than reliance on pre-deployment testing, with providers expected to track real-world performance, data drift, concept drift, prediction drift, and potential fairness impacts throughout a system’s lifecycle. It describes Annex IV documentation as requiring performance logs, drift and anomaly records, serious-incident reports, and periodic summaries linked to pre-deployment risk controls, while Articles 61 and 72 require serious incidents to be reported to national authorities within 15 days of awareness. The passage emphasizes that audit-ready monitoring should record threshold breaches, model versions, assigned owners, human-review dispositions, and approved threshold changes, and should connect alerts to documented enforcement or justified decisions not to act. It contrasts policy and governance tools such as Credo AI and IBM watsonx.governance with Openlayer, asserting that the former primarily support documentation or platform-specific monitoring while Openlayer can automatically create audit records and suspend inference when material violations occur.

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