A tailored course, built for your situation
Mastering ISO 42001 for Service Delivery Leaders in Strategic Programs
Build AI governance practices that produce accurate, defensible outputs from the first draft
$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.
Tired of reworking AI governance documentation after peer feedback?
The situation this course is for
Most practitioners spend 40% of their time revising policies and control mappings because initial drafts lack defensibility or clarity. This delays program timelines and dilutes authority.
Who this is for
Service Delivery Manager in a global systems integrator, managing strategic programs with AI components and governance dependencies
Who this is not for
Individuals seeking introductory AI awareness or non-delivery roles like research, academia, or product marketing
What you walk away with
- Produce AI governance documentation that passes peer review without revision
- Build a repeatable method for accurate control mapping under ISO 42001
- Deliver polished Statements of Applicability with minimal leadership back-and-forth
- Anticipate audit questions with pre-emptive documentation patterns
- Strengthen stakeholder trust by eliminating rework cycles
The 12 modules (with all 144 chapters)
Module 1. Foundations of AI Governance in Delivery-Led Programs
Establish the core principles of AI governance as applied in service delivery contexts, focusing on accountability, transparency, and integration with existing program workflows. This module sets the baseline for producing outputs that are structured, consistent, and aligned with ISO 42001 requirements from the outset.
12 chapters in this module
- Understanding the scope of AI governance in service delivery
- Key roles and responsibilities in AI compliance workflows
- Mapping ISO 42001 to existing delivery lifecycle phases
- Identifying high-risk AI use cases in strategic programs
- Documenting AI system boundaries and data flows
- Establishing governance thresholds for deployment approval
- Integrating ethical review into technical delivery gates
- Defining audit-ready terminology for team use
- Version control practices for AI governance artefacts
- Setting expectations for documentation completeness
- Common pitfalls in early-stage AI governance rollout
- Building stakeholder alignment on governance priorities
Module 2. Control Mapping Under ISO 42001 Clause by Clause
Walk through each control in ISO 42001, translating requirements into actionable implementation steps tailored to service delivery environments. Each chapter provides a worked example to eliminate guesswork and ensure outputs are technically accurate and organizationally relevant.
12 chapters in this module
- Clause 4: Understanding organizational context for AI
- Clause 5: Leadership commitment and governance structure
- Clause 6: Risk assessment methodology for AI systems
- Clause 7: Resource planning for AI compliance activities
- Clause 8: Data quality management in AI pipelines
- Clause 9: Human oversight mechanisms in automated decisions
- Clause 10: Accuracy and reliability validation techniques
- Clause 11: Transparency requirements for model documentation
- Clause 12: Cybersecurity controls for AI infrastructure
- Clause 13: Privacy-preserving design in AI workflows
- Clause 14: Accountability frameworks for AI outcomes
- Clause 15: Continuous monitoring and improvement loops
Module 3. Statement of Applicability: From Template to Approval
Learn how to build a Statement of Applicability that stands up to internal review using real templates and annotation patterns. This module eliminates ambiguity in scoping decisions and ensures every exclusion is justified with evidence, not opinion.
12 chapters in this module
- Structuring the SoA for readability and traceability
- Documenting applicable controls with implementation notes
- Justifying exclusions using risk-based rationale
- Aligning SoA content with delivery team responsibilities
- Using cross-references to existing policies and standards
- Formatting conventions for leadership review
- Versioning and change tracking best practices
- Integrating third-party audit findings into the SoA
- Handling partial implementations with clear status markers
- Automating updates using low-code tools
- Review cycles with legal and compliance stakeholders
- Finalizing the SoA for sign-off and publication
Module 4. AI Risk Assessment: Structured Inputs, Defensible Outputs
Develop a repeatable process for conducting AI risk assessments that feed directly into control selection and documentation. This module emphasizes clarity, consistency, and audit readiness in risk narratives.
12 chapters in this module
- Defining AI system inventory and classification levels
- Assessing societal impact of AI decisions
- Evaluating bias potential in training data
- Scoring model uncertainty and confidence intervals
- Determining human-in-the-loop requirements
- Mapping data sources for provenance and lineage
- Assessing explainability needs by use case
- Integrating security threat modeling outputs
- Documenting risk treatment decisions
- Producing risk register summaries for leadership
- Linking risk findings to control implementation
- Updating risk assessments during model retraining
Module 5. Policy Drafting for Technical Teams
Translate governance requirements into actionable policies that developers and delivery leads can implement without interpretation. Focuses on clarity, specificity, and alignment with technical constraints.
12 chapters in this module
- Writing enforceable policy statements for AI use
- Avoiding vague language in technical governance
- Setting measurable thresholds for model performance
- Defining ownership of AI lifecycle stages
- Integrating policy requirements into sprint planning
- Creating policy exception processes
- Version control for policy documents
- Communicating updates to distributed teams
- Linking policy to code review checklists
- Auditing compliance with policy mandates
- Handling legacy systems under new policy rules
- Documenting policy waivers and sunset dates
Module 6. Evidence Collection for Internal Reviews
Generate audit-ready evidence packages that demonstrate compliance without requiring follow-up requests. This module teaches how to anticipate reviewer needs and package documentation accordingly.
12 chapters in this module
- Identifying evidence requirements for each control
- Organizing documentation by review cycle
- Standardizing file naming and metadata tagging
- Capturing screenshots with context and timestamps
- Documenting decision trails for key choices
- Using automated logs to support claims
- Redacting sensitive information securely
- Compiling evidence packs in standardized formats
- Verifying completeness before submission
- Responding to evidence requests efficiently
- Maintaining evidence for multi-year retention
- Preparing for surprise audit scenarios
Module 7. Narrative Design for Stakeholder Clarity
Craft compelling, jargon-free narratives that make AI governance decisions understandable to non-technical leaders. Ensures outputs are not just correct but communicable.
12 chapters in this module
- Translating technical findings into business terms
- Building logical flow in governance reports
- Using visuals to simplify complex concepts
- Anticipating leadership questions in written form
- Balancing transparency with confidentiality
- Telling the story behind risk decisions
- Framing trade-offs between speed and rigor
- Writing executive summaries that stick
- Adapting tone for different audiences
- Integrating feedback without weakening position
- Maintaining narrative consistency across artefacts
- Archiving narratives for future reference
Module 8. Cross-Functional Alignment Without Delays
Coordinate with legal, compliance, security, and delivery teams efficiently, without getting stuck in alignment loops. This module provides tools to drive decisions forward while maintaining quality.
12 chapters in this module
- Mapping stakeholder influence on governance outcomes
- Setting decision rights for AI control ownership
- Running targeted alignment sessions
- Using collaborative documentation platforms
- Resolving conflicts over control applicability
- Escalation paths for unresolved disagreements
- Building shared understanding of risk appetite
- Synchronizing with procurement on vendor risk
- Integrating DevOps practices into governance
- Tracking inter-team dependencies
- Measuring alignment cycle time
- Reducing rework through early involvement
Module 9. Version Control and Change Management
Maintain governance continuity across revisions, team changes, and system updates. Ensures outputs remain accurate and defensible over time.
12 chapters in this module
- Establishing baseline configurations for AI systems
- Tracking changes to models, data, and infrastructure
- Managing policy updates with change logs
- Using Git for governance documentation
- Automating notifications for version changes
- Conducting impact assessments for updates
- Handling emergency changes with oversight
- Documenting rollback procedures
- Integrating change management with CI/CD
- Auditing version history for compliance
- Archiving deprecated controls
- Ensuring continuity during team transitions
Module 10. Training and Onboarding for Governance Adoption
Equip teams to produce high-quality governance outputs from day one. Focuses on practical onboarding tools that reduce onboarding time and variation.
12 chapters in this module
- Designing role-specific onboarding checklists
- Creating video-free training materials
- Developing decision trees for common scenarios
- Running tabletop exercises for new hires
- Linking training to certification paths
- Assessing knowledge retention post-onboarding
- Updating training materials with lessons learned
- Using peer mentoring in governance adoption
- Measuring time-to-competence for new members
- Integrating governance into delivery onboarding
- Reducing dependency on individual experts
- Scaling training across global teams
Module 11. Continuous Monitoring and Improvement
Implement feedback loops that improve governance quality over time. Focuses on practical metrics and review cycles that drive better outputs without adding burden.
12 chapters in this module
- Defining KPIs for AI governance effectiveness
- Tracking rework rates and revision cycles
- Measuring time from draft to approval
- Auditing consistency across projects
- Gathering feedback from reviewers
- Benchmarking against peer programs
- Running quarterly governance health checks
- Using dashboards for leadership visibility
- Prioritizing improvements based on data
- Automating routine monitoring tasks
- Reporting progress to executive sponsors
- Updating practices based on lessons learned
Module 12. Scaling Governance Across Programs
Replicate success across engagements using standardized templates, reuse patterns, and coordination mechanisms that preserve quality at volume.
12 chapters in this module
- Identifying common patterns across AI programs
- Creating shareable control libraries
- Standardizing documentation templates
- Building internal centers of excellence
- Replicating successful governance models
- Adapting frameworks for regional differences
- Managing governance at program portfolio level
- Using playbooks for rapid deployment
- Tracking maturity across teams
- Sharing lessons learned organization-wide
- Recognizing high-performance teams
- Sustaining quality during growth phases
How this maps to your situation
- Service Delivery Manager in strategic programs
- AI governance integration under ISO 42001
- Cross-functional alignment in global delivery
- High-quality, revision-free documentation
Before vs. after
Before
Producing AI governance documentation that requires multiple rounds of feedback and revision, leading to delays and inconsistent quality.
After
Delivering accurate, defensible, and polished governance outputs the first time, aligned with ISO 42001 and accepted without rework.
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 90 minutes per module, designed for completion over 12 weeks with one module per week.
If nothing changes
Without a structured approach, teams continue producing inconsistent, revision-heavy governance documentation, delaying program timelines and weakening stakeholder trust in delivery leadership.
How this compares to the alternatives
Unlike generic AI ethics primers or high-level compliance overviews, this course delivers structured, field-tested methods for producing high-quality governance documentation that stands up to scrutiny, specifically tailored for service delivery leaders in global firms.
Frequently asked
Is this course technical or strategic?
It’s delivery-oriented: focused on producing accurate, defensible documentation that aligns technical execution with governance requirements.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does it cover other standards besides ISO 42001?
The focus is ISO 42001, with references to COBIT and NIST AI frameworks where they support implementation clarity.
$199 one-time. Approximately 90 minutes per module, designed for completion over 12 weeks with one module per week..
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