AI Governance Monitoring: Continuous Auditing for AI Systems
Blog post from NeuralTrust
AI governance monitoring is a continuous, automated process that involves collecting, analyzing, and acting on operational data from AI systems to detect and address policy violations, behavioral drift, data access anomalies, and compliance failures in real time, thus preventing incidents or regulatory breaches. Unlike one-time audits, which only confirm compliance at a specific time, continuous monitoring ensures systems behave correctly throughout their operational lifetime. EU AI Act Article 72 mandates providers of high-risk AI systems to maintain a documented post-market monitoring system that actively collects and analyzes performance data, making this practice a legal requirement. The monitoring process involves a four-layer architecture of collection, detection, alerting, and response, with alert thresholds tailored per system and metric. Tools like NeuralTrust TrustLens and TrustGuard facilitate this process by providing the necessary infrastructure for observability, behavioral detection, and response, ensuring compliance and governance standards are met continuously.
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