A tailored course, built for your situation
Deeper command of the ISO 42001 control framework
Master the structure, controls, and implementation logic of ISO 42001 with precision
$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.
Surface-level familiarity with ISO 42001 leaves practitioners exposed during audits and cross-functional reviews
The situation this course is for
Many analysts can cite ISO 42001 controls but struggle when asked to justify exclusions, map evidence, or defend design choices under pressure. This creates dependency on external consultants and slows internal adoption.
Who this is for
Senior analyst or practitioner leading AI governance implementation in a regulated technical environment
Who this is not for
Entry-level compliance staff, vendors selling ISO 42001 tooling, or executives seeking board-level summaries
What you walk away with
- Confidently interpret each of the 14 clauses of ISO 42001 with reference-backed reasoning
- Map AI system components to required controls with precision
- Build audit-ready statements of applicability (SoA) that hold up under internal scrutiny
- Lead cross-functional teams through control implementation without deferring to consultants
- Anticipate and resolve common implementation breakdowns before they delay projects
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and the AI management system
Understand the purpose, scope, and high-level structure of ISO 42001 as it applies to AI systems in operational environments.
12 chapters in this module
- What ISO 42001 governs
- How it differs from ISO 27001
- AI system lifecycle stages
- Boundaries of applicability
- Clause structure overview
- Relationship to NIST AI RMF
- Integration with SOC 2
- Organizational context mapping
- Roles in AI governance
- Documentation expectations
- Audit preparation mindset
- First steps in implementation
Module 2. Clause 4: Understanding organizational context
Learn how to define the internal and external factors that shape AI governance requirements for your organization.
12 chapters in this module
- Identifying interested parties
- AI system user groups
- Regulatory touchpoints
- Internal policy alignment
- Technology stack dependencies
- Vendor relationships
- Risk appetite definition
- Stakeholder influence mapping
- Data sovereignty constraints
- AI use case classification
- Governance maturity baseline
- Context documentation template
Module 3. Clause 5: Leadership and accountability
Establish clear ownership of AI governance across leadership and define accountability mechanisms.
12 chapters in this module
- Top management responsibilities
- AI governance policy drafting
- Leadership communication plan
- Accountability frameworks
- Role of the Principal Analyst
- Delegation of authority
- Oversight cadence design
- Escalation paths
- Resource allocation planning
- Internal audit sponsorship
- Policy dissemination strategy
- Leadership sign-off workflow
Module 4. Clause 6: Planning AI management system
Develop a structured approach to identifying risks and opportunities in AI system deployment.
12 chapters in this module
- Risk identification methodology
- Opportunity mapping
- AI-specific threats
- Bias and fairness planning
- Transparency requirements
- Human oversight planning
- Performance thresholds
- Incident response planning
- Third-party risk integration
- Change management process
- Risk treatment options
- Risk register template
Module 5. Clause 7: Support and resource allocation
Ensure the AI management system has the personnel, data, and infrastructure needed to function effectively.
12 chapters in this module
- Competency requirements
- Training needs analysis
- Data quality standards
- Infrastructure readiness
- Documentation control
- Internal communication plan
- Knowledge retention strategy
- Vendor documentation standards
- Tooling integration
- Version control practices
- Resource tracking dashboard
- Support process documentation
Module 6. Clause 8: Operation of AI management system
Implement controls to ensure AI systems operate as intended and remain within defined boundaries.
12 chapters in this module
- Change approval process
- Model validation steps
- Performance monitoring
- Human oversight mechanisms
- Incident logging
- Data drift detection
- Security controls integration
- Access control mapping
- Output review process
- Bias detection triggers
- Retraining workflow
- Decommissioning protocol
Module 7. Clause 9: Performance evaluation
Establish methods to monitor, measure, and evaluate the effectiveness of the AI management system.
12 chapters in this module
- Key performance indicators
- Audit schedule design
- Internal review cadence
- Effectiveness metrics
- Stakeholder feedback loop
- Compliance monitoring
- Control testing methods
- Gap analysis technique
- Benchmarking approach
- Reporting format
- Management review inputs
- Continuous improvement cycle
Module 8. Clause 10: Improvement and adaptation
Create a feedback-driven process to refine the AI management system over time.
12 chapters in this module
- Nonconformity tracking
- Root cause analysis
- Corrective action process
- Lessons learned log
- System updates procedure
- Feedback from users
- Incident review steps
- Policy update workflow
- Version control for controls
- Change communication plan
- Lessons dissemination
- Improvement roadmap
Module 9. Control mapping and evidence assembly
Translate ISO 42001 requirements into specific, auditable evidence across technical and procedural domains.
12 chapters in this module
- Control-to-process mapping
- Evidence sourcing strategy
- Document retention standards
- Interview preparation
- Audit trail requirements
- Policy linkage method
- Control ownership assignment
- Cross-system dependencies
- Automation of evidence
- Internal validation steps
- Gap justification writing
- Evidence package assembly
Module 10. Statement of Applicability (SoA) development
Build a defensible, well-documented SoA that clearly articulates which controls apply and why.
12 chapters in this module
- SoA purpose and audience
- Mandatory inclusions
- Exclusion justification
- Tailoring explanation
- Risk-based rationale
- Cross-reference method
- Version control for SoA
- Internal review steps
- Approval workflow
- Integration with SOC 2
- Third-party review prep
- Living document approach
Module 11. Internal audit preparation and execution
Prepare for and lead internal audits of the AI management system with confidence and precision.
12 chapters in this module
- Audit planning
- Checklist development
- Sampling methodology
- Interview techniques
- Evidence review process
- Finding categorization
- Report drafting
- Management response
- Follow-up process
- Audit schedule integration
- Cross-functional coordination
- Audit closure steps
Module 12. Certification readiness and external audit
Prepare for external certification audits with a fully documented and defensible AI management system.
12 chapters in this module
- Certification body selection
- Pre-certification review
- Stage 1 audit prep
- Document submission
- Interview preparation
- Finding response strategy
- Corrective action submission
- Stage 2 audit readiness
- Surveillance audit prep
- Maintaining certification
- Scope expansion
- Continuous compliance
How this maps to your situation
- Leading an AI governance initiative
- Preparing for internal audit
- Building a statement of applicability
- Responding to cross-functional challenges
Before vs. after
Before
Reliant on consultants for ISO 42001 interpretation, inconsistent control mapping, reactive audit preparation
After
Owns the ISO 42001 framework end to end, leads implementation confidently, produces audit-ready artefacts 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 3 hours per module, designed to be completed at your pace over 4-6 weeks.
If nothing changes
Continuing without deep command of ISO 42001 increases dependency on external experts, slows project velocity, and creates exposure during audits or compliance reviews.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses exclusively on ISO 42001 with concrete, role-specific implementation steps. Compared to vendor-led training, it's independent, deeper, and built for practitioners who lead real-world deployments.
Frequently asked
Who is this course for?
Senior analysts, governance leads, and technical practitioners responsible for implementing or auditing AI management systems under ISO 42001.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this aligned with NIST or other frameworks?
Yes, the course includes mapping guidance to NIST AI RMF, SOC 2, and COBIT for integrated governance.
$199 one-time. Approximately 3 hours per module, designed to be completed at your pace over 4-6 weeks..
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