A tailored course, built for your situation
Deeper command of the ISO/IEC 42001 AI governance framework
Master the emerging standard shaping responsible AI at global enterprises
$199 one-time
24-hour access provisioning
30-day money-back guarantee
Hand-built implementation playbook
12 modules. 12 chapters per module. 144 chapters total.
12 modules, each with 12 chapters (144 chapters total), text-based, plus downloadable templates and a hand-built implementation playbook delivered alongside course access.
The situation this course is for
Who this is for
Senior technology leader in a global systems integrator managing AI governance, compliance, and enterprise risk frameworks
Who this is not for
Individuals seeking introductory overviews of AI ethics or general risk management principles
What you walk away with
- Name every component of the ISO/IEC 42001 framework and its purpose in AI governance workflows
- Map internal AI controls directly to clause requirements with confidence
- Anticipate auditor expectations based on clause-by-clause implementation logic
- Draft policy updates that align with framework intent without senior review
- Lead cross-functional alignment using the standard as a shared reference model
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO/IEC 42001 and the AI Management System
Establish foundational clarity on the purpose, scope, and structure of the AI management system standard. Understand how it aligns with broader enterprise risk and compliance goals.
12 chapters in this module
- What AI MS solves
- Core principles of ISO/IEC 42001
- Relationship to ISO 9001 and ISO 27001
- Governance vs ethics vs risk
- Boundaries of the management system
- Key terms and definitions
- The role of top management
- Documentation requirements
- Context of the organization
- Understanding stakeholders
- AI system lifecycle stages
- Clause 4.1, 4.4 alignment
Module 2. Leadership Commitment and Policy Formulation
Learn how leadership obligations are codified in the standard and how to draft enforceable AI policies that reflect organizational intent and regulatory readiness.
12 chapters in this module
- Top management responsibilities
- AI policy statement components
- Setting strategic direction
- Resource allocation expectations
- Accountability frameworks
- Policy approval workflows
- Version control standards
- Communication protocols
- Policy exception handling
- Integration with corporate values
- Clause 5.1, 5.3 breakdown
- Policy audit readiness
Module 3. Planning for AI Risk and Opportunity
Master the risk assessment methodology embedded in the standard, including identification, evaluation, and treatment of AI-specific risks and opportunities.
12 chapters in this module
- Risk criteria definition
- Hazard identification techniques
- Bias risk mapping
- Transparency gaps analysis
- Third-party model risks
- Data provenance risks
- Risk treatment options
- Opportunity identification
- Risk register structure
- Escalation thresholds
- Clause 6.1 requirements
- Linking risk to objectives
Module 4. Support Functions: Resources, Competence, and Awareness
Ensure your team meets the standard’s expectations for training, awareness, and internal capability development across AI governance roles.
12 chapters in this module
- Competence requirements
- Training program design
- Awareness campaign tactics
- Internal communication plans
- Documentation standards
- Knowledge retention strategies
- Vendor competence validation
- Audit trail preparation
- Clause 7.1, 7.4 alignment
- Role-based access controls
- Skills gap assessment
- Evidence collection workflows
Module 5. Operational Controls for AI Systems
Implement the standard’s operational requirements across the AI lifecycle, from design and development to deployment and monitoring.
12 chapters in this module
- Lifecycle stage controls
- Design-time assurance
- Development environment security
- Testing for fairness
- Deployment checklists
- Monitoring KPIs
- Incident response planning
- Model versioning rules
- Human oversight mechanisms
- Clause 8.1, 8.4 breakdown
- Change management protocols
- Decommissioning procedures
Module 6. Performance Evaluation and Internal Audits
Conduct internal evaluations that mirror external audit expectations, ensuring continuous compliance and improvement.
12 chapters in this module
- Internal audit planning
- Audit scope definition
- Checklist creation
- Sampling techniques
- Nonconformity classification
- Corrective action workflows
- Management review inputs
- KPI tracking dashboards
- Clause 9.1, 9.3 requirements
- Audit report structure
- Follow-up verification
- Audit evidence standards
Module 7. Management Review and Continuous Improvement
Lead review cycles that drive governance maturity by analyzing performance data and adapting the AI management system.
12 chapters in this module
- Review frequency standards
- Input data collection
- Performance trend analysis
- Stakeholder feedback integration
- System effectiveness review
- Resourcing decisions
- Policy update triggers
- Clause 9.3 implementation
- Improvement backlog prioritization
- Benchmarking against peers
- Maturity model navigation
- Action item tracking
Module 8. Clause-by-Clause Implementation Logic
Walk through each clause of ISO/IEC 42001 with implementation examples, decision trees, and real-world adaptation patterns.
12 chapters in this module
- Clause 4 deep dive
- Clause 5 deep dive
- Clause 6 deep dive
- Clause 7 deep dive
- Clause 8 deep dive
- Clause 9 deep dive
- Clause 10 deep dive
- Mapping to NIST AI RMF
- Mapping to EU AI Act
- Gap analysis methodology
- Implementation roadblock patterns
- Executive summary templates
Module 9. Control Mapping and Framework Integration
Connect ISO/IEC 42001 to existing governance frameworks like NIST, COBIT, and GDPR to avoid duplication and strengthen coherence.
12 chapters in this module
- NIST AI RMF crosswalk
- COBIT the current cycle alignment
- GDPR Article 22 linkage
- SOC 2 Type 2 overlap
- Cloud provider controls
- Enterprise risk framework sync
- Single source of truth design
- Control rationalization
- Duplicate effort elimination
- Unified reporting strategy
- Integration playbook
- Stakeholder alignment tactics
Module 10. Documentation and Artefact Development
Build the exact documents required by the standard, from policy statements to audit trails, with templates and examples.
12 chapters in this module
- AI governance policy template
- Risk register format
- Training records log
- Internal audit report
- Management review minutes
- Control implementation evidence
- Compliance dashboard
- Vendor assessment form
- Model impact assessment
- Change request log
- Incident report structure
- Document retention schedule
Module 11. Preparing for Certification and External Audit
Navigate the certification process with clarity on auditor expectations, evidence readiness, and readiness assessment.
12 chapters in this module
- Certification body selection
- Stage 1 audit prep
- Stage 2 audit prep
- Evidence package assembly
- Auditor Q&A simulation
- Nonconformity response
- Corrective action proof
- Readiness checklist
- Gap closure tracking
- Post-certification maintenance
- Surveillance audit readiness
- Re-certification timeline
Module 12. Sustaining and Scaling the AI Management System
Embed the AI MS into ongoing operations and extend its use across business units and geographies.
12 chapters in this module
- Operating model design
- Center of excellence setup
- Cross-functional governance
- Global rollout strategy
- Local adaptation rules
- Change enablement
- Performance monitoring
- Stakeholder engagement
- Budget justification
- Value communication
- Maturity progression
- Next-generation framework planning
How this maps to your situation
- When drafting AI governance policy for the first time
- Before an internal audit cycle
- During integration with existing compliance frameworks
- When preparing for ISO certification
Before vs. after
Before
Relying on fragmented guidance and external consultants to interpret AI governance standards
After
Owning the ISO/IEC 42001 framework with technical precision and leading implementation independently
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters)
- Downloadable templates and worked examples for every module
- Hand-built implementation playbook delivered alongside course access
- 30-day money-back guarantee
Delivery and format
- Course and learning environment access provisioned within 24 hours of purchase
- Hand-built implementation playbook delivered alongside course access
Format: Text-based modules and chapters in the Art of Service learning environment, plus downloadable templates and worked examples for every chapter, plus the hand-built implementation playbook delivered alongside course access.
Time investment: Approximately 6, 8 hours per module, designed for completion over 6, 8 weeks with steady progress.
How this compares to the alternatives
Unlike generic AI ethics courses or high-level overviews, this program provides clause-level mastery of ISO/IEC 42001 with implementation-grade templates and decision logic used by leading practitioners.
Frequently asked
Is this course aligned with the final published version of ISO/IEC 42001?
Yes, the course is based on the full published standard released in December the current cycle and reflects current global implementation practices.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I use this to prepare for official certification?
Yes, the course includes audit-ready templates, clause-by-clause guidance, and a full implementation playbook used by teams pursuing ISO certification.
$199 one-time. Approximately 6, 8 hours per module, designed for completion over 6, 8 weeks with steady progress..
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.
30-day money-back guarantee·
144 chapters·
Hand-built playbook included·
Account access within 24 hours