A tailored course, built for your situation
Mastering ISO 42001 for Problem Management Leaders
Build authoritative command of AI governance frameworks within complex defense and critical infrastructure environments.
$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.
Feeling like AI governance discussions move too fast to fully grasp the framework behind them?
The situation this course is for
Most practitioners absorb ISO 42001 piecemeal, through audit checklists or vendor questionnaires, without mastering the underlying architecture. This leads to reactive positioning, inconsistent control mapping, and missed opportunities to lead.
Who this is for
Senior Problem Management professional in a defense, critical infrastructure, or regulated technology services organization navigating AI governance for the first time.
Who this is not for
Junior IT staff, general compliance interns, or vendors selling AI tools without governance depth.
What you walk away with
- Internalize ISO 42001 control clauses to the point of fluency
- Map problem management workflows directly to A.1, A.9 governance controls
- Anticipate auditor and regulator focus areas in AI system documentation
- Lead internal discussions with confidence when AI-related problem tickets arise
- Produce clear, precedent-setting artefacts that survive leadership transitions
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 and Its Role in Problem Management
Establish foundational knowledge of the ISO 42001 standard, its structure, and how it aligns with existing problem resolution practices in high-assurance environments.
12 chapters in this module
- What ISO 42001 governs and why it matters for problem resolution
- Comparing ISO 42001 with ISO 27001 and COBIT in practice
- The relationship between AI risk and recurring incident patterns
- How ISO 42001 differs from technical AI safety frameworks
- Core terminology: AI system, lifecycle, governance body, oversight
- Mapping existing problem records to potential AI governance gaps
- The role of documentation in audit readiness under ISO 42001
- Understanding scope definition for AI systems in hybrid environments
- Distinguishing between AI management and AI ethics frameworks
- Case study: AI incident response in a defense contractor setting
- How regulators interpret AI governance maturity
- Foundation for integrating ISO 42001 into daily problem triage
Module 2. Establishing AI Governance Context and Scope
Define the boundaries of AI governance within existing operational structures, focusing on integration with service management and risk frameworks.
12 chapters in this module
- Identifying AI systems within existing service portfolios
- Determining which problem records involve AI components
- Defining organizational context for AI governance adoption
- Scoping AI systems based on impact and autonomy level
- Engaging stakeholders across engineering and compliance
- Documenting governance boundaries for audit clarity
- Integrating AI scope decisions into change advisory boards
- Handling edge cases: machine learning scripts in automation
- Using RACI models to assign AI governance roles
- Aligning AI scope with existing ISO 27001 or SOC 2 domains
- Avoiding overreach while maintaining control integrity
- Template: AI system inventory and classification matrix
Module 3. Leadership and Governance Accountability
Clarify leadership obligations under ISO 42001 and how problem management leaders can shape governance expectations.
12 chapters in this module
- Top management responsibilities under clause 5.1
- Translating executive commitment into operational practices
- Establishing a governance forum for AI system oversight
- Role of the Problem Manager in AI policy escalation
- Documenting governance meeting outcomes and action items
- Ensuring continuity of governance during leadership transitions
- Linking AI governance to existing risk and compliance committees
- Maintaining independence in audit and review processes
- Balancing innovation velocity with control rigor
- Case example: Governance failure in autonomous diagnostics
- Template: Governance meeting minutes and follow-up tracker
- Building credibility as a governance practitioner
Module 4. Planning AI Risk Management
Develop a structured approach to identifying, assessing, and mitigating AI-related risks within problem resolution workflows.
12 chapters in this module
- Identifying AI-specific risk factors in incident patterns
- Using ISO 42001 Annex A controls as risk filters
- Integrating AI risk into existing risk registers
- Assessing likelihood and impact of AI system failures
- Prioritizing risks based on operational criticality
- Documenting risk treatment plans for audit review
- Linking AI risk decisions to existing change management
- Avoiding duplication with existing cybersecurity controls
- Handling model drift and data degradation risks
- Case: Missed risk pattern in predictive maintenance AI
- Template: AI risk assessment worksheet
- Escalation paths for unresolved AI risk items
Module 5. Supporting AI Governance Documentation
Create and maintain the essential documentation required for ISO 42001 compliance within problem management contexts.
12 chapters in this module
- Required documentation under ISO 42001 clause 7.5
- Creating AI governance policy statements
- Maintaining control implementation records
- Version control for AI-related policies and procedures
- Secure storage and access for AI governance documents
- Linking documentation to incident and problem records
- Using documentation to defend control decisions
- Common auditor findings in documentation reviews
- Template: AI governance document index
- Automating documentation updates from ticketing systems
- Handling document retention across jurisdictions
- Integrating with existing document management systems
Module 6. Operational Control of AI Systems
Implement and monitor controls for AI system deployment, monitoring, and decommissioning.
12 chapters in this module
- Applying ISO 42001 controls to AI development pipelines
- Ensuring data quality and provenance for AI systems
- Validating model performance before deployment
- Monitoring AI outputs for drift or degradation
- Establishing feedback loops from problem tickets
- Incident response procedures for AI system failures
- Handling model updates and retraining cycles
- Decommissioning AI components safely and transparently
- Case: AI-driven ticket routing failure analysis
- Template: AI system lifecycle checklist
- Integrating with IT service continuity plans
- Audit evidence for operational control effectiveness
Module 7. Auditing AI Governance Performance
Prepare for and conduct internal audits of AI governance practices, focusing on control adherence and effectiveness.
12 chapters in this module
- Planning internal audits based on ISO 42001 clauses
- Sampling AI-related incident and problem records
- Interviewing stakeholders across AI lifecycle stages
- Evaluating control implementation completeness
- Documenting audit findings and recommendations
- Reporting results to governance forums
- Tracking remediation of audit findings
- Using audit results to refine problem management
- Case: Audit uncovering undocumented AI inference use
- Template: Internal audit work program for AI
- Avoiding common auditor pitfalls
- Building credibility through consistent audit execution
Module 8. Improving AI Governance Maturity
Use feedback and performance data to continuously improve AI governance practices.
12 chapters in this module
- Collecting metrics on AI system incidents and problems
- Analyzing trends in AI-related ticket volume
- Measuring control effectiveness over time
- Using root cause analysis to improve governance
- Benchmarking against ISO 42001 maturity levels
- Identifying opportunities for automation
- Prioritizing governance improvements
- Documenting improvement actions and outcomes
- Case: Reducing AI incident recurrence by 40%
- Template: AI governance improvement backlog
- Linking improvements to business outcomes
- Sustaining momentum in governance enhancement
Module 9. Integrating AI Governance with Service Management
Align AI governance practices with existing ITIL and service management frameworks.
12 chapters in this module
- Mapping AI governance to ITIL problem management
- Integrating AI considerations into change advisory boards
- Using incident records to identify AI control gaps
- Linking known errors to AI system documentation
- Handling AI-related workarounds and resolutions
- Updating service catalogs with AI system metadata
- Training service desk staff on AI reporting
- Case: ServiceNow integration for AI incident tagging
- Template: AI system service model
- Aligning AI governance with continuous improvement
- Avoiding siloed governance and operations
- Measuring service impact of AI governance
Module 10. Vendor and Third-Party AI Governance
Extend governance to AI systems provided or maintained by external parties.
12 chapters in this module
- Assessing vendor AI governance maturity
- Including ISO 42001 requirements in procurement
- Reviewing third-party AI system documentation
- Monitoring vendor compliance with governance rules
- Handling incidents involving third-party AI
- Conducting vendor audits for AI governance
- Managing contract clauses for AI system changes
- Case: Third-party AI failure in access control
- Template: Vendor AI governance assessment form
- Escalation paths for unresolved vendor issues
- Building joint governance forums with vendors
- Ensuring transparency in outsourced AI operations
Module 11. Preparing for External Certification
Navigate the process of achieving ISO 42001 certification with confidence and efficiency.
12 chapters in this module
- Selecting a certification body for ISO 42001
- Preparing for stage 1 and stage 2 audits
- Gathering evidence for AI governance controls
- Conducting internal readiness assessments
- Training teams for audit interactions
- Responding to auditor findings effectively
- Maintaining certification over time
- Case: First-time certification success story
- Template: Certification readiness checklist
- Avoiding common certification pitfalls
- Using certification as a credibility signal
- Communicating certification achievements internally
Module 12. Sustaining AI Governance Leadership
Maintain and grow your influence as a leader in AI governance within your organization.
12 chapters in this module
- Building internal communities of practice
- Mentoring junior staff in AI governance
- Sharing success stories across teams
- Influencing future AI initiatives proactively
- Staying current with ISO 42001 updates
- Contributing to industry governance discussions
- Measuring personal impact on AI governance
- Developing a personal roadmap for mastery
- Case: From problem manager to governance lead
- Template: Personal development plan for governance
- Balancing operational demands with strategic growth
- Leaving a lasting governance legacy
How this maps to your situation
- Problem resolution in defense-contracted services
- AI governance integration into existing compliance frameworks
- Efficiency pressure impacting control rigor
- Cross-functional visibility in regulated environments
Before vs. after
Before
Reacting to AI governance questions with fragmented knowledge and incomplete control mapping
After
Leading with deep, structured command of ISO 42001 and its operational integration into problem management
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: 90 minutes of focused learning, structured to fit within a single Sunday morning.
If nothing changes
Without structured mastery, AI governance remains reactive , exposing operations to audit findings, control gaps, and missed leadership opportunities in evolving regulatory environments.
How this compares to the alternatives
Unlike generic compliance webinars or broad AI ethics courses, this program delivers precise, actionable mastery of ISO 42001 as it applies to real-world problem management in high-assurance environments , with zero consultant fluff and full operational specificity.
Frequently asked
Is this course suitable for someone without direct AI development experience?
Yes. This course is designed for governance, risk, and operations leaders who need to understand and oversee AI systems, not build them.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will I receive a certification upon completion?
This course prepares you for ISO 42001 compliance and audit readiness but does not grant formal certification. It equips you with the knowledge and artefacts to succeed in an external audit.
$199 one-time. 90 minutes of focused learning, structured to fit within a single Sunday morning..
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