Program Overview
ISO/IEC 42001 is the first certifiable AI Management System standard. Train to audit AI policies, impact assessments, dataset governance, model lifecycle controls, and human oversight obligations — and to map findings against the EU AI Act and NIST AI RMF.
Syllabus
Day 1 Schedule
AIMS Foundations & the Regulatory Landscape
Why ISO/IEC 42001 exists, how it sits beside the EU AI Act, NIST AI RMF and the OECD AI Principles.
AI Impact Assessment & AI Risk Management
Walk a single AI use-case through the impact-assessment lifecycle: rights, safety, transparency, environmental footprint.
Dataset Governance & Model Lifecycle Controls
Annex A controls covering data provenance, quality, labelling, model evaluation, deployment gates and post-market monitoring.
Day 2 Schedule
Transparency, Explainability & Human Oversight
Audit the controls that make AI decisions accountable: model cards, system cards, user notices, appeals and redress.
Third-Party AI, GenAI & Supply Chain
Audit the use of foundation models, third-party AI APIs, and embedded vendor AI features inside an AIMS.
Final Knowledge Assessment
Multiple-choice assessment covering every clause area introduced in Specialty: ISO/IEC 42001 Artificial Intelligence Management Systems Lead Auditor. Pass mark 70%.
This terminal assessment unlocks after you enrol. The exam grades clause-level recall; the simulation requires a passing score before drafting the closing NCR.
Closeout: Live Audit & NCR Drafting
Live War Room simulation tied to Specialty: ISO/IEC 42001 Artificial Intelligence Management Systems Lead Auditor. Conduct an AI-driven interview, evidence-gather, then draft a defensible NCR.
This terminal assessment unlocks after you enrol. The exam grades clause-level recall; the simulation requires a passing score before drafting the closing NCR.
Learning Outcomes
- Audit an AI Management System (AIMS) against ISO/IEC 42001
- Conduct AI Impact Assessments and review their integration with corporate risk
- Sample dataset governance and model-lifecycle controls (data, train, evaluate, deploy, monitor)
- Verify human oversight, transparency and explainability controls
- Reconcile AIMS findings with EU AI Act risk tiers and NIST AI RMF functions