Place AI compliance evidence at the lifecycle stage where it is most useful for governance decisions.
Place each evidence artifact at the lifecycle stage where it most directly supports a decision. Intake Pre-launch Deployment Monitoring Retirement Initial purpose, owner, data class, AI capability, and affected-people entry Vendor documentation request for intended-use limits and model/provider chain Bias, robustness, security, and human-oversight test results Launch approval record with accepted risks and required mitigations User instructions explaining limits, escalation, and override authority Metric drift, override rate, complaint, and incident review dashboard Material-change log for model, data, threshold, prompt, or vendor chain Data deletion, access removal, and archived decision record at end of use
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