A tailored course, built for your situation
Mastering ISO 42001 for Senior Compliance Leaders
Build defensible, high-accuracy AI governance artefacts that stand up to scrutiny
$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.
Who this is for
Senior compliance and governance practitioners in consulting or audit firms leading AI accountability programmes
Who this is not for
Entry-level compliance staff or those without direct responsibility for AI governance framework implementation
What you walk away with
- Produce fully formed ISO 42001 Statements of Applicability with minimal revision cycles
- Apply control mappings that are accurate, well-justified, and audit-ready
- Build quality into first-draft documentation so stakeholder reviews move faster
- Anticipate and address assessor questions proactively in your initial submission
- Develop a repeatable approach to scoping and implementing AI management systems
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and the AI Management System
Establish the foundation of ISO 42001, its structure, and how it aligns with global AI governance expectations. Learn the core principles of an AI MS and its value in delivering quality outcomes.
12 chapters in this module
- What is ISO 42001
- Purpose of an AI Management System
- Relationship to other ISO standards
- Scope and applicability
- Key terminology
- Principles of AI governance
- Why quality matters first
- Linking to organisational objectives
- Understanding the AI lifecycle
- Stakeholder expectations
- Risk-based thinking in AI
- Certification pathways
Module 2. Leadership and Organisational Context
Define leadership responsibilities and determine internal and external issues affecting AI governance. Learn how to set clear direction and commitment from the outset.
12 chapters in this module
- Determining organisational context
- Internal and external factors
- Understanding stakeholder needs
- Defining AI scope boundaries
- Leadership commitment
- Roles and responsibilities
- Policy development
- Resource allocation
- Accountability frameworks
- Performance evaluation
- Communication strategy
- Leadership engagement
Module 3. Planning the AI Management System
Identify risks and opportunities in AI deployment. Develop actionable plans to address them and set measurable objectives for AI governance quality.
12 chapters in this module
- Risk assessment methodology
- Opportunity identification
- AI-specific threats
- Legal and regulatory alignment
- Setting objectives
- Planning for change
- Risk treatment options
- Objective tracking
- Resource planning
- Stakeholder alignment
- Change management
- Quality benchmarks
Module 4. Support and Resource Management
Ensure adequate support for the AI MS including competence, awareness, communication, and documented information control.
12 chapters in this module
- Competence requirements
- Training needs analysis
- Awareness programmes
- Internal communication
- External communication
- Documented information
- Control of documents
- Version management
- Access control
- Retention policies
- Digital asset tracking
- Archiving strategy
Module 5. Operational Control of AI Systems
Implement controls for AI system development, deployment, monitoring, and maintenance to ensure ongoing compliance and quality.
12 chapters in this module
- Development lifecycle
- Data management practices
- Model validation
- Human oversight
- Performance monitoring
- Incident response
- Bias detection
- Transparency measures
- Update protocols
- Performance metrics
- Logging requirements
- Control automation
Module 6. Competence and Human Factors in AI Governance
Understand how human competencies and oversight mechanisms contribute to the accuracy and defensibility of AI governance.
12 chapters in this module
- AI literacy levels
- Training delivery
- Competency assessments
- Human-in-the-loop design
- Oversight structures
- Decision escalation
- Error feedback loops
- User training
- Ethical considerations
- Cross-functional roles
- Responsibility mapping
- Accountability tracing
Module 7. Monitoring, Measurement, and Review
Establish processes to monitor AI system performance, measure effectiveness, and conduct internal audits to maintain high-quality outputs.
12 chapters in this module
- KPIs for AI systems
- Performance dashboards
- Internal audit planning
- Audit execution
- Nonconformity tracking
- Corrective actions
- Management review inputs
- Trend analysis
- Benchmarking
- Audit documentation
- Continuous improvement
- Quality assurance
Module 8. Audit Readiness and Assessor Interaction
Prepare for certification audits with polished, complete documentation and confident articulation of control implementation.
12 chapters in this module
- Audit planning
- Evidence collection
- Documentation hierarchy
- SoA development
- Control justification
- Assessor expectations
- Response protocols
- Interview readiness
- Gap analysis
- Pre-audit review
- Final documentation
- Post-audit follow-up
Module 9. Statement of Applicability Development
Learn how to create a comprehensive, justified, and defensible Statement of Applicability that forms the core of ISO 42001 compliance.
12 chapters in this module
- Understanding the SoA
- Control selection
- Applicability rationale
- Justification writing
- Exclusion criteria
- Risk linkage
- Evidence mapping
- Stakeholder alignment
- Version control
- Review cycles
- Final approval
- SoA maintenance
Module 10. Control Implementation and Mapping
Apply ISO 42001 controls to real-world AI systems with precision and clarity, ensuring defensible mappings and minimal rework.
12 chapters in this module
- Control A.8.1 mapping
- Control A.8.2 alignment
- Control A.8.3 integration
- Control A.8.4 documentation
- Control A.8.5 validation
- Control A.8.6 monitoring
- Control A.8.7 review
- Control A.8.8 update
- Cross-reference matrix
- Implementation evidence
- Gap tracking
- Control rationalisation
Module 11. Continuous Improvement of the AI MS
Embed feedback loops and improvement processes to ensure the AI management system evolves with changing needs and maintains high quality.
12 chapters in this module
- Feedback mechanisms
- Incident learning
- Audit insights
- Stakeholder input
- Performance trends
- System updates
- Policy revisions
- Training refresh
- Benchmark adoption
- Lessons learned
- Improvement planning
- Change implementation
Module 12. Sustaining Compliance and Governance Maturity
Maintain long-term compliance and drive maturity in AI governance practices, ensuring lasting quality and stakeholder trust.
12 chapters in this module
- Certification maintenance
- Surveillance audits
- Re-certification
- Maturity models
- Benchmarking progress
- Leadership reporting
- Knowledge transfer
- Succession planning
- Technology changes
- Regulatory shifts
- Global alignment
- Defensible consistency
How this maps to your situation
- Preparing for first ISO 42001 audit
- Reducing rework in compliance documentation
- Building stakeholder confidence in AI systems
- Leading AI governance in consulting engagements
Before vs. after
Before
Spending cycles revising AI governance documentation, chasing evidence, and preparing for audits
After
Producing polished, accurate ISO 42001 outputs the first time, with less rework and more confidence
What's included with your purchase
- 12 modules with 12 chapters each (144 chapters total)
- 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 3-4 hours per module, recommended over 12 weeks with applied work between modules.
If nothing changes
Continuing with fragmented or reactive AI governance approaches risks increased rework, audit findings, and diminished trust in AI deployments.
How this compares to the alternatives
Unlike generic AI ethics guides or high-level overviews, this course delivers actionable, ISO 42001-specific implementation patterns used in real certification projects.
Frequently asked
Is this course aligned with the latest ISO 42001 standard?
Yes, the course is fully aligned with the published ISO/IEC 42001 standard for AI management systems.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Who is this course designed for?
Senior compliance, governance, and assurance professionals leading AI accountability initiatives, particularly in consulting or audit roles.
$199 one-time. Approximately 3-4 hours per module, recommended over 12 weeks with applied work between modules..
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