A tailored course, built for your situation
Direct sign off authority on ISO 42001 framework decisions
Own the AI governance call with confidence and clarity
$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.
Still escalating AI governance decisions to senior reviewers?
The situation this course is for
Even senior practitioners get stuck waiting for approvals on core framework choices, delaying implementation and diluting ownership.
Who this is for
Senior compliance or governance lead in a regulated enterprise, already fluent in control frameworks and responsible for AI oversight
Who this is not for
Entry-level analysts, consultants without implementation authority, or teams focused on non-certifiable AI ethics frameworks
What you walk away with
- Own end-to-end scoping and approval of ISO 42001 control mappings
- Documented rationale for control exclusions or adaptations that survive auditor scrutiny
- Pre-built templates for SoA, AoA, and compliance evidence packages
- First-mover credibility in internal AI governance forums
- Trusted judgment when balancing innovation speed with compliance rigor
The 12 modules (with all 144 chapters)
Module 1. Foundations of ISO 42001 in enterprise AI governance
Understand how ISO 42001 creates a structured foundation for AI risk management and why certification elevates practitioner authority.
12 chapters in this module
- Why ISO 42001 now matters for AI oversight
- How certification shifts decision rights
- Structure of the standard and core clauses
- AI governance vs AI ethics: where ISO 42001 applies
- Mapping AI use cases to control domains
- Role of the CSA in scoping boundaries
- Control exclusions: when and how
- Linking AI policies to existing frameworks
- Integrating with SOC 2 and ISO 27001
- Vendor AI tools and third party assurance
- Internal vs external certification paths
- Timeline for first certification cycle
Module 2. Establishing governance boundaries and scope
Define the perimeter of AI governance with precision, ensuring control applicability without overreach.
12 chapters in this module
- Identifying AI systems in scope
- Determining materiality thresholds
- Documentation required for scope claims
- Handling shadow AI deployments
- Exclusions based on risk tolerance
- Engaging legal and compliance teams
- Internal audit alignment strategies
- Version control for system inventories
- Data lineage mapping for AI models
- Defining operational boundaries
- Mapping to NIST AI RMF
- Maintaining scope over time
Module 3. Control selection and justification
Choose controls based on organizational context and articulate clear, defensible reasoning.
12 chapters in this module
- Tailoring control objectives
- Baseline controls every organization needs
- High risk AI use case enhancements
- Documenting rationale for omissions
- Cross-referencing with SOC 2
- Evidence collection planning
- Control implementation phasing
- Role-based access to AI systems
- Monitoring automated decisions
- Bias detection and correction protocols
- Human oversight requirements
- External auditor expectations
Module 4. Building the Statement of Applicability
Create a defensible SoA that demonstrates thoughtful application of controls.
12 chapters in this module
- SoA purpose and structure
- Required fields and formatting
- Linking controls to risk assessments
- Justifying exclusions clearly
- Using templates from certified peers
- Review cycle best practices
- Version control and change logs
- Aligning with internal policies
- Third party attestations
- Preparing for external review
- Common auditor questions
- Updating SoA for new AI models
Module 5. Conducting the risk assessment
Run a repeatable, evidence-backed risk assessment process for AI systems.
12 chapters in this module
- Scope definition for AI risk
- Identifying threat sources
- Vulnerability mapping
- Impact rating methodology
- Risk tolerance thresholds
- Documenting assumptions
- Engaging business stakeholders
- Third party model risks
- Data quality risks
- Model drift detection
- Risk register maintenance
- Linking to control selection
Module 6. Developing implementation timelines
Translate framework decisions into actionable, auditable implementation plans.
12 chapters in this module
- Phased rollout strategy
- Milestone definition
- Resource allocation models
- Tracking control deployment
- Integrating with project management
- ServiceNow workflows for compliance
- Automated evidence collection
- Testing control effectiveness
- Internal review checkpoints
- Audit readiness gates
- Post-certification maintenance
- Updating for model refreshes
Module 7. Vendor AI system oversight
Extend ISO 42001 governance to third-party and open-source AI tools.
12 chapters in this module
- Third party due diligence
- Contractual assurance clauses
- Model cards and technical documentation
- API-based AI services
- Open source model risks
- Pre-trained model governance
- Fine-tuning accountability
- Monitoring downstream usage
- Vendor audit rights
- Incident response coordination
- Performance drift tracking
- Exit strategy planning
Module 8. Human oversight and escalation design
Design meaningful human involvement in AI decision loops.
12 chapters in this module
- When to require human review
- Designing override mechanisms
- Training for human reviewers
- Logging oversight actions
- Measuring intervention rates
- Bias escalation paths
- Time-to-intervention benchmarks
- Feedback loop integration
- Documentation for auditors
- Scalability of oversight
- Cost-benefit of review layers
- Automated alerting rules
Module 9. Bias detection and mitigation planning
Institutionalize proactive bias management across AI lifecycle stages.
12 chapters in this module
- Bias definition and scope
- Pre-deployment testing methods
- Demographic data considerations
- Disparate impact analysis
- Ongoing monitoring techniques
- Thresholds for intervention
- Remediation protocols
- Transparency with stakeholders
- Incident reporting structure
- External benchmarking
- Legal and reputational risks
- Public disclosure policies
Module 10. Evidence packaging for audits
Assemble compelling, organized evidence packages that satisfy auditors.
12 chapters in this module
- Audit evidence checklist
- Document retention strategy
- Linking controls to evidence
- Formatting for external review
- Common deficiencies to avoid
- Leveraging automation tools
- Internal pre-audit process
- Responding to findings
- Maintaining evidence over time
- Cross-system traceability
- Version control practices
- Audit trail preservation
Module 11. Maintaining certification over time
Sustain compliance through changes in AI systems and business context.
12 chapters in this module
- Change control process
- Reassessing scope annually
- Updating SoA and AoA
- Ongoing risk reassessment
- Control effectiveness reviews
- New model onboarding
- Deprecation of legacy AI
- Annual internal audit cycle
- Engaging recertification bodies
- Handling control failures
- Continuous improvement cycle
- Knowledge transfer planning
Module 12. Leading ISO 42001 in cross-functional teams
Drive alignment across legal, engineering, compliance and business units.
12 chapters in this module
- Stakeholder identification
- Communication plan design
- Workshop facilitation techniques
- Conflict resolution methods
- Executive update cadence
- Escalation protocols
- Shared documentation platforms
- Cross-team KPIs
- Incentive alignment
- Training rollout strategy
- Feedback integration
- Celebrating certification milestones
How this maps to your situation
- When launching first AI governance initiative
- Before external auditor engagement
- After AI incident or near miss
- During enterprise compliance framework refresh
Before vs. after
Before
Waiting for senior approval on core framework choices and control boundaries
After
Confidently signing off on ISO 42001 scope, controls, and implementation path
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 completion over 12 weeks with implementation milestones.
If nothing changes
Without structured command of ISO 42001, governance decisions remain fragmented, escalation-dependent, and vulnerable to auditor challenge.
How this compares to the alternatives
Unlike generic AI ethics courses or broad compliance webinars, this program delivers specific, certification-grade capability in ISO 42001 with practitioner-tested documentation and decision authority frameworks.
Frequently asked
Who is this course for?
Senior practitioners leading AI governance in regulated environments, especially those preparing for ISO 42001 certification.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this cover SOC 2 or ISO 27001?
It focuses on ISO 42001 but includes cross-walks to SOC 2 and ISO 27001 for integration.
$199 one-time. Approximately 3-4 hours per module, designed for completion over 12 weeks with implementation milestones..
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