Evidence collection

AI lifecycle evidence & model-specific artifacts Documenting AI risk, bias & impact assessments Model cards & system cards as audit evidence AI monitoring, drift detection & logs Human oversight & human-in-the-loop evidence AI incident management & failure reporting

Evidence collection for ISO/IEC 42001 involves demonstrating that AI governance and controls are not only defined but also consistently implemented and effective across the entire AI lifecycle. Auditors will look for objective evidence that shows how AI-related risks are identified, managed, monitored, and improved over time. Unlike traditional management system standards, ISO 42001 places significant emphasis on system-level and model-level evidence. This means organizations must be able to produce artifacts that link governance decisions to specific AI systems, showing traceability from risk assessment and design through deployment, operation, and incident handling.

AI lifecycle evidence & model-specific artifacts

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