This lesson develops practical capability in AI Risk, Impact, Policies, Objectives, and Evidence within ISO/IEC 42001 Lead Auditor Training. Activities reflect an organization operating predictive and generative AI with data suppliers, model providers, and affected stakeholders, so requirements, decisions, evidence, findings, and improvement actions remain connected.
The lesson supports the wider objective to audit ISO/IEC 42001 artificial intelligence management systems.
The instructor demonstrates the ai risk, impact, policies, objectives, and evidence workflow, identifies applicable inputs and responsibilities, records checkpoints in AIMS governance audit papers, and contrasts the accepted state with a condition where impact assessment precedes stakeholder identification.
Complete a controlled implementation, audit, analysis, or foundation exercise for AI Risk, Impact, Policies, Objectives, and Evidence. Establish scope and criteria, collect or create evidence, examine “impact assessment precedes stakeholder identification,” reach a supported conclusion, and preserve the result in AIMS governance audit papers.
Separate missing evidence from ineffective practice, and distinguish a documentation issue from a control, process, governance, or competence failure. Use AIMS governance audit papers to trace the earliest divergence. Treat “impact assessment precedes stakeholder identification” as a hypothesis until the response is validated against the relevant requirement and intended outcome.
Learners can apply AI Risk, Impact, Policies, Objectives, and Evidence, explain the reasoning, and defend the result through AIMS governance audit papers.