A tailored course, built for your situation
Own the ISO 42001 AI Governance Design End to End
A 12-module program to lead AI governance decisions in your current role
$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 BI and data governance practitioners implementing AI oversight frameworks in global services firms
Who this is not for
Entry-level analysts, project coordinators, or team members without direct input into control design or governance documentation
What you walk away with
- Lead ISO 42001 control mapping without escalation
- Produce audit-ready governance documentation in half the time
- Make confident design decisions on scope boundaries and exclusions
- Own the vendor assessment track within AI governance deployments
- Deliver stakeholder-aligned SoA (Statement of Applicability) drafts on first iteration
The 12 modules (with all 144 chapters)
Module 1. Foundations of ISO 42001 in Data-Centric AI
Ground your governance approach in the actual text of ISO 42001, focusing on clauses relevant to BI and analytics environments. Understand how it maps to existing data practices without overlap.
12 chapters in this module
- What ISO 42001 solves that other standards don’t
- Core terms every practitioner must know
- AI types in scope under Annex A
- Relationship to BI and data warehousing
- How Annex A controls differ from ISO 27001
- When to apply human oversight clauses
- Mapping data lineage to control A.8.1
- Using A.4.2 for AI policy ownership
- Integrating A.5.1 into model documentation
- Control A.6.3 for third-party AI tools
- Defining 'high-risk' AI per A.7.1
- Auditor expectations for clause 4.1
Module 2. Designing the Governance Boundary
Learn how to define what’s in and out of scope with confidence, a key skill for practitioners leading real deployments. Avoid overreach and unnecessary burden.
12 chapters in this module
- Start with data source types
- Exclude non-AI automation cleanly
- Using deployment purpose to set limits
- How model update frequency affects scope
- Documenting boundary rationale
- Handling edge cases like chatbots
- Stakeholder alignment on exclusions
- Preventing scope creep in reviews
- Mapping boundary to control A.4.1
- Boundary artifacts for audit trail
- When to involve legal vs technical teams
- Common boundary mistakes to avoid
Module 3. Stakeholder Roles in AI Governance
Assign clear ownership across functions without overcomplicating. Focus on decisions that matter and avoid committee drift.
12 chapters in this module
- Defining process owner for A.4
- Who owns model validation reports
- Data provider responsibilities
- Vendor oversight lead role
- Legal input timing and scope
- Privacy officer integration points
- Escalation path for disagreements
- Sign-off sequence for documentation
- Maintaining role clarity in matrix orgs
- Updating roles during team changes
- Documenting role decisions
- Avoiding consensus paralysis
Module 4. Control Selection and Justification
Go beyond checkbox compliance. Learn how to justify inclusion or exclusion based on actual risk and architecture.
12 chapters in this module
- Baseline controls all deployments need
- High-risk AI additional controls
- Exclusion criteria per control
- Documenting rationale clearly
- Using architecture diagrams as proof
- When to include A.8.4 monitoring
- Handling model drift detection
- Validating exclusion with evidence
- Cross-linking to existing SOC 2 controls
- Common auditor pushbacks and replies
- Versioning control decisions
- Template for control justification log
Module 5. Building the Statement of Applicability
Create a professional, clear SoA that stands up to internal and external review. Learn what top teams include, and omit.
12 chapters in this module
- SoA structure best practices
- Presenting in-scope controls
- Formatting exclusion statements
- Referencing implementation evidence
- Using clear language for non-experts
- Version control for SoA updates
- Getting sign-off without delays
- Aligning SoA with audit plan
- Common SoA flaws to avoid
- How often to update the SoA
- SoA vs implementation plan
- Template walkthrough
Module 6. Documenting AI System Lifecycle
Map real BI and analytics workflows to ISO 42001 lifecycle requirements. Show compliance through existing processes.
12 chapters in this module
- Phases of AI lifecycle per standard
- Aligning model development steps
- Version control integration
- Model validation checkpoints
- Retirement and deprecation process
- Handling model updates
- Data drift monitoring triggers
- Logging for auditability
- Using CI/CD pipelines as evidence
- Mapping to control A.8.2
- Lifecycle documentation structure
- Common gaps in lifecycle records
Module 7. Third-Party AI and Vendor Oversight
Handle SaaS models, APIs, and external tools with rigour. Expand your remit by owning vendor governance.
12 chapters in this module
- Classifying third-party AI usage
- Required vendor documentation
- Assessing vendor ISO 42001 claims
- Contractual clauses to demand
- Onboarding process for AI tools
- Ongoing monitoring approach
- Incident response with vendors
- Exit strategies for non-compliant tools
- Mapping to control A.6.3
- Common vendor red flags
- Evidence collection from vendors
- Vendor exception process
Module 8. Human Oversight and Intervention Design
Implement meaningful oversight that satisfies auditors without slowing delivery.
12 chapters in this module
- Defining oversight triggers
- Setting thresholds for intervention
- Role clarity for human reviewers
- Logging oversight actions
- Training requirements for reviewers
- Escalation paths for edge cases
- Auditor expectations for oversight
- Common missteps in oversight logs
- Balancing automation and control
- Using dashboards for oversight
- Documentation structure
- Testing oversight process
Module 9. Data Governance Integration
Link AI governance to existing data practices so compliance compounds rather than duplicates.
12 chapters in this module
- Aligning data lineage with ISO 42001
- Mapping data quality checks
- PII handling per control A.5.3
- Data retention policies
- Cross-referencing with GDPR
- Data access logging
- Handling synthetic data
- Data drift detection process
- Vendor data handling oversight
- Documenting data decisions
- Common gaps in data evidence
- Template for data governance map
Module 10. Internal Audit and Continuous Review
Design self-sustaining review cycles so governance stays current without manual effort.
12 chapters in this module
- Frequency of internal checks
- Automating evidence collection
- Assigning review owners
- Tracking findings to closure
- Using control dashboards
- Aligning with SOC 2 cycles
- Preparing for external audit
- Common audit findings and fixes
- Updating documentation post-audit
- Maintaining version history
- Audit communication plan
- Template for audit response
Module 11. Change Management for AI Systems
Control evolution of AI systems without freezing progress. Build processes that scale with innovation.
12 chapters in this module
- Change approval workflow
- Impact assessment for updates
- Version control integration
- Re-validation requirements
- Stakeholder notification
- Documentation update process
- Rollback planning
- Emergency change path
- Auditor expectations for changes
- Common change gaps
- Linking to CI/CD
- Change log template
Module 12. Implementation Playbook Integration
Adapt the course templates to your current projects. Ship faster by starting from proven structures.
12 chapters in this module
- Customising control mapping
- Adapting SoA template
- Integrating with existing tools
- Rolling out to team members
- Training junior staff
- Tracking compliance status
- Reporting progress to leadership
- Updating for new regulations
- Lessons from real deployments
- Avoiding rework traps
- Scaling beyond one project
- Your next governance initiative
How this maps to your situation
- When starting a new AI governance project
- During vendor selection for AI tools
- Preparing for internal audit
- Scaling governance across multiple models
Before vs. after
Before
Relying on guidance from others or reacting to audit findings after the fact.
After
Confidently leading the design and documentation of ISO 42001 AI governance for your projects from day one.
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 3-4 hours per module, designed for practitioners shipping real work. Total investment: ~36-48 hours over 12 weeks.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses exclusively on ISO 42001 in data and analytics environments, with templates based on actual deployments in global services firms. No other course offers this level of role-specific detail for BI specialists leading governance.
Frequently asked
Is this course relevant if my organization hasn’t adopted ISO 42001 yet?
Yes. This course prepares you to lead the design phase so your team can move faster once the decision is made. Many participants use it to shape internal discussion and establish ownership.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me advance into a leadership role?
It strengthens your ability to own key governance decisions in your current role, which often leads to expanded responsibilities and recognition.
$199 one-time. Approximately 3-4 hours per module, designed for practitioners shipping real work. Total investment: ~36-48 hours over 12 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