A tailored course, built for your situation
Mastering ISO 42001 for AI Governance Practitioners
Build trusted AI systems with documented, regulator-ready controls
$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 practitioner in product, engineering, or governance roles leading AI system design or compliance assurance, with delivery experience in scalable platforms
Who this is not for
Junior analysts, non-technical stakeholders, or those without hands-on experience in system implementation or control validation
What you walk away with
- Produce regulator-facing AI governance packages aligned with ISO 42001 requirements
- Lead internal control validation exercises for AI systems with confidence
- Receive peer-team escalations on sensitive AI design decisions before deployment
- Respond effectively to auditor follow-ups with documented rationale and evidence
- Build reusable AI SoA templates that accelerate future audits and reviews
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 Scope and AI Governance Boundaries
Define the applicability of ISO 42001 to AI systems, identify core control areas, and distinguish between AI-specific and general information security obligations.
12 chapters in this module
- What ISO 42001 covers
- AI systems in scope
- Control domains overview
- Governance vs technical controls
- Organizational context mapping
- Stakeholder identification
- Risk appetite alignment
- Exclusion justification rules
- Boundary documentation
- Control linkage strategy
- Third-party considerations
- Version control basics
Module 2. AI Risk Assessment Frameworks Under ISO 42001
Develop structured approaches to identifying and prioritizing AI-specific risks, including bias, transparency, and unintended consequences.
12 chapters in this module
- AI risk taxonomy
- Hazard identification
- Impact scoring
- Likelihood assessment
- Risk register setup
- Control mapping logic
- Scenario modeling
- Escalation thresholds
- Peer validation steps
- Documentation standards
- Review cycles
- Update triggers
Module 3. Control Design for AI Transparency and Explainability
Implement specific controls that ensure AI decisions can be explained and justified, meeting both technical and regulatory expectations.
12 chapters in this module
- Explainability requirements
- Model documentation
- Decision tracing
- User notification design
- Output justification
- Data provenance tracking
- Version history
- Audit trail structure
- Human oversight points
- Feedback loops
- Error handling
- Incident escalation
Module 4. Data Governance and AI Model Inputs
Ensure the integrity and compliance of training and inference data used by AI systems, with formal controls over sourcing, labeling, and usage.
12 chapters in this module
- Data provenance
- Labeling standards
- Bias testing
- Data quality checks
- Usage rights
- Retention rules
- Anonymization methods
- Consent verification
- Third-party data
- Data lineage
- Access logging
- Audit sampling
Module 5. Human Oversight and AI Decision Boundaries
Define where human review is required in AI-driven workflows and how to implement effective intervention points.
12 chapters in this module
- Oversight thresholds
- Intervention triggers
- Review process design
- Escalation paths
- Role clarity
- Training for reviewers
- Response timelines
- Documentation needs
- Feedback incorporation
- Performance monitoring
- Error logging
- Process improvement
Module 6. AI Model Development Lifecycle Controls
Apply ISO 42001 principles across the full AI model lifecycle, from ideation to deprecation.
12 chapters in this module
- Lifecycle phases
- Gate review points
- Version control
- Testing protocols
- Model validation
- Documentation requirements
- Approval workflows
- Change management
- Decommissioning plan
- Lessons learned
- Knowledge transfer
- Archival rules
Module 7. Third-Party AI Vendor Management
Assess and monitor external AI providers to ensure compliance with internal governance standards and ISO 42001 expectations.
12 chapters in this module
- Vendor selection
- Due diligence steps
- Contract clauses
- Security assessments
- Performance monitoring
- Compliance verification
- Audit rights
- Incident response
- Exit planning
- Oversight frequency
- Risk tiering
- Escalation procedures
Module 8. Internal Audit and AI Compliance Testing
Conduct effective internal reviews of AI systems to verify control effectiveness and readiness for external audit.
12 chapters in this module
- Audit planning
- Control testing
- Evidence collection
- Sampling strategy
- Gap identification
- Reporting format
- Remediation tracking
- Follow-up timing
- Stakeholder comms
- Tool selection
- Documentation review
- Findings escalation
Module 9. Preparing Regulator-Facing AI Review Packages
Assemble complete, defensible submissions for regulatory review, including statements of conformity and supporting evidence.
12 chapters in this module
- Regulatory expectations
- SoA structure
- Control mapping
- Evidence bundles
- Executive summary
- Risk acceptance
- Exemption justifications
- Review timelines
- Submission formats
- Coordination needs
- Follow-up prep
- Status tracking
Module 10. Responding to Auditor Follow-Ups on AI Controls
Effectively address questions and requests from auditors with timely, complete, and technically sound responses.
12 chapters in this module
- Query triage
- Ownership assignment
- Evidence retrieval
- Technical validation
- Drafting responses
- Review cycles
- Escalation paths
- Timeline management
- Stakeholder input
- Version control
- Final approval
- Submission process
Module 11. Building Reusable AI Governance Artefacts
Develop templates, playbooks, and checklists that accelerate future AI compliance efforts across teams.
12 chapters in this module
- Template design
- Checklist standardization
- Playbook structure
- Version control
- Ownership rules
- Access controls
- Maintenance process
- Feedback integration
- Cross-team adoption
- Training materials
- Onboarding use
- Improvement cycles
Module 12. Sustaining AI Governance Beyond Initial Certification
Ensure long-term compliance and adaptability of AI governance practices as systems evolve and regulations change.
12 chapters in this module
- Change monitoring
- Control updates
- Staff training
- Policy refreshes
- Audit prep rhythm
- Incident learning
- Benchmarking
- Stakeholder updates
- Technology shifts
- Regulatory scanning
- Lessons integration
- Continuous improvement
How this maps to your situation
- Starting first AI governance project
- Responding to internal audit request
- Preparing for external certification
- Scaling governance across teams
Before vs. after
Before
AI governance tasks are ad hoc, reactive, and require extensive coordination to produce compliant outputs.
After
You lead AI governance efforts with standardized artefacts, receive peer escalations proactively, and deliver regulator-ready packages on demand.
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 hours per week over 4 weeks to complete all modules and apply templates to your context.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses exclusively on ISO 42001 implementation for AI systems, with structured workflows and real-world artefacts used by practitioners in product and governance roles.
Frequently asked
Is this course technical or governance-focused?
It's designed for practitioners who bridge both areas , covering control implementation with enough technical depth to be credible, while focusing on documentation, review, and compliance outcomes.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I use the templates for multiple AI projects?
Yes , the course includes reusable, adaptable templates designed to scale across projects and teams.
$199 one-time. Approximately 3 hours per week over 4 weeks to complete all modules and apply templates to your context..
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