AI policyAI Acceptable Use Policy
An AI acceptable use policy defines approved, restricted, and prohibited uses of AI services, models, data, accounts, and generated content.
AI assuranceAI Audit Evidence Integrity
AI audit evidence integrity is the ability to show that logs, model artifacts, data extracts, test results, approvals, and screenshots are authentic, complete, attributable, and unchanged.
AI assuranceAI Audit Finding Follow-Up
AI audit finding follow-up verifies that corrective actions address the root cause, operate as intended, and reduce the stated risk before a finding is closed.
AI change assuranceAI Change Evidence Package
An AI change evidence package assembles the artifacts needed to understand, approve, reproduce, and later audit a model, data, prompt, configuration, or integration change.
AI engineering assuranceAI Configuration Reproducibility
AI configuration reproducibility means an authorized team can recreate the relevant model build or runtime behavior from recorded code, data references, parameters, dependencies, prompts, and infrastructure settings.
AI assuranceAI Control Design Effectiveness
AI control design effectiveness asks whether a control, as documented and configured, is capable of preventing, detecting, or correcting the risk it was selected to address.