A tailored course, built for your situation
Mastering ISO 42001 for Executive Support Practitioners
Deliver AI governance artefacts with confidence and precision
$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
Executive-level support professional in a consulting or systems integration firm, responsible for preparing and coordinating high-stakes governance, compliance, and risk documentation with minimal oversight.
Who this is not for
Entry-level admins, general office coordinators, or roles without access to confidential governance or client-facing compliance artefacts.
What you walk away with
- Produce AI governance summaries that pass partner review without revision
- Own the drafting and routing of ISO 42001-aligned deliverables independently
- Anticipate escalation paths and prepare artefacts that meet regulator-facing standards
- Build trusted workflows where senior sponsors route sensitive M&A and compliance papers directly to you
- Reduce rework cycles by aligning documentation structure with ISO 42001 clause expectations
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 Scope in AI Governance
Establish a clear boundary for AI system documentation based on organisational context, stakeholder expectations, and regulatory alignment. Focus on identifying which AI processes require formal recording and which can be documented informally.
12 chapters in this module
- Defining organisational context for AI management
- Identifying internal and external stakeholders
- Mapping AI use cases to ISO 42001 requirements
- Establishing documentation boundaries
- Differentiating between core and peripheral AI systems
- Determining scope ownership across teams
- Aligning AI scope with existing governance frameworks
- Documenting scope decisions for audit readiness
- Updating scope during AI lifecycle phases
- Avoiding scope creep in multi-client environments
- Using scope to prioritise high-impact AI systems
- Linking scope to leadership reporting cycles
Module 2. Leadership and Commitment in AI Management
Learn how to reflect leadership engagement in AI governance artefacts, including documented roles, resource allocation, and integration with strategic direction, all aligned with ISO 42001 Clause 5.
12 chapters in this module
- Documenting leadership roles in AI systems
- Recording commitment to AI governance policies
- Assigning accountability for AI oversight
- Linking AI initiatives to business objectives
- Capturing leadership reviews in meeting minutes
- Integrating AI into enterprise risk frameworks
- Demonstrating resource allocation for AI projects
- Tracking leadership communication on AI ethics
- Aligning AI governance with organisational values
- Preparing leadership statements for audits
- Updating commitment records after organisational changes
- Using leadership engagement as audit evidence
Module 3. AI Policy Development and Communication
Create and maintain a formal AI policy that meets ISO 42001 requirements, including content structure, approval workflows, and dissemination to relevant teams and stakeholders.
12 chapters in this module
- Structuring the AI policy document
- Including mandatory elements per ISO 42001
- Drafting policy statements with precision
- Securing executive sign-off on policy
- Version control for policy updates
- Communicating policy changes to stakeholders
- Maintaining policy accessibility across teams
- Linking policy to training and onboarding
- Auditing policy compliance across projects
- Handling policy exceptions and waivers
- Revising policy in response to new regulations
- Archiving outdated policy versions
Module 4. Roles and Responsibilities in AI Governance
Define, assign, and document roles for AI system oversight, including decision rights, escalation paths, and cross-functional coordination, ensuring clear accountability.
12 chapters in this module
- Identifying AI governance roles across departments
- Assigning ownership for AI system lifecycle
- Documenting role responsibilities in RACI format
- Establishing escalation procedures for AI risks
- Integrating AI roles with existing compliance teams
- Clarifying boundaries between AI and data privacy
- Updating role assignments during reorganisations
- Documenting role changes for audit trails
- Training staff on AI role expectations
- Monitoring role effectiveness over time
- Linking roles to access control systems
- Reporting role structure to senior management
Module 5. AI Risk and Opportunity Assessment
Apply ISO 42001 principles to identify, evaluate, and prioritise AI-related risks and opportunities, focusing on ethical, operational, and regulatory dimensions.
12 chapters in this module
- Identifying AI system risks and opportunities
- Categorising risks by impact and likelihood
- Involving stakeholders in risk assessment
- Documenting risk evaluation methodology
- Prioritising risks for treatment planning
- Linking AI risks to enterprise risk registers
- Assessing ethical implications of AI use
- Evaluating reputational and compliance risks
- Updating risk assessments after system changes
- Using risk data to inform leadership decisions
- Aligning risk assessments with audit requirements
- Archiving assessment records for review
Module 6. AI Risk Treatment Planning
Develop actionable plans to address identified AI risks, including mitigation strategies, ownership assignments, and integration with project timelines.
12 chapters in this module
- Selecting risk treatment options
- Assigning risk owners and action items
- Integrating risk treatment into project plans
- Defining risk acceptance criteria
- Documenting treatment decisions formally
- Tracking progress on risk actions
- Reviewing treatment effectiveness regularly
- Updating plans after new risk findings
- Linking treatment to AI system changes
- Reporting treatment status to leadership
- Using templates for consistent risk documentation
- Preparing treatment records for audit
Module 7. AI System Documentation Requirements
Master the creation of comprehensive AI system documentation as required by ISO 42001, including design specifications, training data descriptions, and operational logs.
12 chapters in this module
- Identifying required AI documentation
- Describing AI system architecture
- Documenting training data characteristics
- Recording model development processes
- Maintaining operational logs
- Capturing version control information
- Describing deployment environments
- Reporting performance monitoring results
- Updating documentation after changes
- Ensuring documentation readability
- Storing documentation securely
- Preparing documentation for audit
Module 8. AI System Lifecycle Management
Understand and document each phase of the AI system lifecycle, from design to decommissioning, with attention to compliance, ethics, and stakeholder expectations.
12 chapters in this module
- Defining stages in the AI lifecycle
- Documenting design and development phases
- Capturing testing and validation procedures
- Recording deployment and integration steps
- Monitoring operational performance
- Planning for system updates and retraining
- Managing AI system decommissioning
- Documenting lifecycle decisions
- Aligning lifecycle with regulatory requirements
- Reviewing lifecycle periodically
- Updating lifecycle documentation
- Using lifecycle records in audits
Module 9. AI Performance Monitoring and Measurement
Establish metrics and monitoring processes for AI systems to ensure ongoing compliance, accuracy, fairness, and alignment with intended outcomes.
12 chapters in this module
- Defining key performance indicators for AI
- Setting thresholds for model drift
- Monitoring fairness and bias metrics
- Tracking operational reliability
- Collecting user feedback systematically
- Reporting performance to stakeholders
- Using dashboards for real-time monitoring
- Scheduling regular performance reviews
- Responding to performance deviations
- Updating monitoring plans after changes
- Linking monitoring to risk assessments
- Preparing monitoring data for audit
Module 10. AI Incident and Nonconformity Management
Develop processes to identify, record, investigate, and resolve AI-related incidents and nonconformities in line with ISO 42001 requirements.
12 chapters in this module
- Defining AI incident reporting procedures
- Documenting incident details accurately
- Investigating root causes of failures
- Classifying incident severity levels
- Escalating incidents to appropriate teams
- Implementing corrective actions
- Tracking resolution timelines
- Preventing recurrence through process updates
- Reporting incidents to leadership
- Archiving incident records securely
- Using incidents to improve AI governance
- Auditing incident response effectiveness
Module 11. Internal Audit Preparation for ISO 42001
Prepare for internal audits by collecting evidence, reviewing documentation, and conducting pre-audit checks specific to AI management systems.
12 chapters in this module
- Scheduling internal audit cycles
- Identifying audit scope and criteria
- Collecting evidence of compliance
- Reviewing documentation completeness
- Conducting pre-audit gap assessments
- Correcting findings before formal audit
- Coordinating with audit teams
- Documenting audit plans and checklists
- Reporting audit results to leadership
- Tracking corrective actions from audit
- Using audit data for continuous improvement
- Maintaining audit records
Module 12. Continuous Improvement of AI Management
Implement processes to ensure ongoing enhancement of AI governance practices, incorporating feedback, audit findings, and evolving regulations.
12 chapters in this module
- Identifying opportunities for improvement
- Analysing feedback from stakeholders
- Reviewing audit and incident data
- Benchmarking against industry standards
- Planning improvement initiatives
- Implementing changes systematically
- Measuring impact of improvements
- Updating policies and procedures
- Training teams on new practices
- Documenting improvement efforts
- Reporting progress to leadership
- Sustaining improvement over time
How this maps to your situation
- Preparing executive summaries for AI governance reviews
- Coordinating escalation responses for regulator-facing deliverables
- Supporting M&A integration teams with AI system documentation
- Ensuring compliance artefacts meet senior sponsor expectations
Before vs. after
Before
AI governance files require multiple revisions and input from multiple teams before submission.
After
You produce trusted, regulator-ready AI governance papers independently, routinely routed to senior sponsors without revision.
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 hours per module, designed to fit around executive support workflows, total commitment around 36 hours over 6-8 weeks.
If nothing changes
Without structured documentation practices, AI governance artefacts may require repeated review cycles, increasing delays and reducing visibility into high-impact work.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses specifically on ISO 42001 and its application to AI governance in consulting environments, delivering templates and workflows tailored to high-stakes, client-facing work.
Frequently asked
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant for someone in an executive support role?
Yes, this course is designed for practitioners supporting senior leadership, especially when handling confidential, regulator-facing, or client-ready governance documentation.
Will I receive templates I can use immediately?
Yes, each module includes downloadable, customisable templates and real-world examples aligned with ISO 42001 requirements.
$199 one-time. Approximately 3 hours per module, designed to fit around executive support workflows, total commitment around 36 hours over 6-8 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