A tailored course, built for your situation
Mastering ISO 42001 for Service Delivery Leaders in Regulated Sectors
A structured approach to AI governance that scales with compliance rigor and visibility.
$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.
Audit packages requiring last-minute rework across technical and client-facing teams.
The situation this course is for
Service delivery leaders in regulated environments often face disconnects between governance frameworks and client-facing assurance content. This creates recurring rework during review cycles, especially when technical control mapping doesn’t translate clearly into contractual or compliance narratives. The burden falls on delivery managers to reconcile these at the last mile.
Who this is for
Service Delivery Manager in a global IT services firm, accountable for compliant, client-facing technology delivery under regulated frameworks.
Who this is not for
Individuals outside regulated service delivery roles, or those whose work does not intersect with compliance frameworks or client-facing audit narratives.
What you walk away with
- Build client-ready AI governance documentation that aligns with ISO 42001 control objectives
- Reduce rework cycles in assurance packaging by structuring evidence flows upfront
- Enable peer teams to reuse governance artifacts in their own client engagements
- Strengthen credibility in client reviews by demonstrating standardized compliance practices
- Position your delivery work as a reference model within the organization
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and the AI Governance Landscape
Establish foundational knowledge of ISO 42001, its structure, and its role in regulated service delivery environments. Understand how it differentiates from other compliance frameworks and why it matters for client trust.
12 chapters in this module
- What ISO 42001 means for service delivery teams
- Core principles of AI management systems
- How ISO 42001 complements existing compliance obligations
- Key differences from ISO 27001 and SOC 2 frameworks
- The role of documentation in audit readiness
- Client expectations around AI transparency
- Why governance matters in client-facing deliverables
- Mapping ISO 42001 to service delivery workflows
- Understanding the certification process timeline
- Internal vs external audit requirements
- The importance of stakeholder alignment early
- Setting expectations with technical and non-technical teams
Module 2. Scoping AI Management Systems for Client Engagements
Learn how to define the boundaries of AI governance applicability within specific client delivery contexts. Avoid over- or under-scoping through practical criteria.
12 chapters in this module
- Defining the scope of AI use in a contract
- Identifying AI-influenced processes in service delivery
- Documenting scope decisions for auditability
- Engaging legal and compliance teams early
- Balancing completeness with practicality
- Using client SLAs to inform governance boundaries
- Avoiding scope creep in assurance packaging
- Handling AI tools not under direct control
- Scoping legacy integrations with modern AI
- Documenting assumptions and exclusions clearly
- Preparing for auditor scrutiny on scope
- Revisiting scope during engagement changes
Module 3. Establishing Leadership and Governance Accountability
Clarify roles and responsibilities within delivery teams to ensure ownership of AI governance controls without creating bottlenecks.
12 chapters in this module
- Assigning governance roles in delivery teams
- Defining clear ownership for AI controls
- Avoiding duplication with central compliance teams
- Creating lightweight governance steering
- Documenting decision rights for AI changes
- Integrating governance into change management
- Ensuring leadership visibility without bureaucracy
- Handling cross-functional accountability
- Onboarding new team members into governance roles
- Maintaining role clarity during turnover
- Aligning governance with delivery timelines
- Escalating issues without slowing delivery
Module 4. Risk Assessment Specific to AI in Service Delivery
Conduct targeted risk assessments that reflect AI-specific threats in client-facing operations, avoiding generic templates.
12 chapters in this module
- Identifying AI-specific risk sources in delivery
- Mapping risks to client-facing service components
- Using real-world incidents to inform risk scenarios
- Assessing bias, drift, and transparency risks
- Incorporating client feedback into risk logs
- Prioritizing risks based on impact and likelihood
- Documenting rationale for risk treatment
- Involving technical and business stakeholders
- Updating risk assessments during engagements
- Avoiding risk register bloat with pruning
- Linking risks to control objectives
- Demonstrating risk thinking to reviewers
Module 5. Designing AI Control Objectives and Controls
Translate ISO 42001 requirements into actionable, auditable controls that fit within existing service delivery processes.
12 chapters in this module
- Mapping ISO 42001 clauses to control objectives
- Designing controls for transparency and explainability
- Incorporating AI model monitoring requirements
- Ensuring data quality for AI-driven decisions
- Controls for human oversight of AI outputs
- Addressing model lifecycle management
- Building version control for AI components
- Defining acceptable use policies for AI tools
- Creating audit trails for AI decision points
- Ensuring accessibility of AI system documentation
- Linking controls to risk treatment decisions
- Avoiding control duplication across frameworks
Module 6. Developing AI System Documentation for Audits
Produce client-ready documentation that satisfies auditors and strengthens client trust, avoiding last-minute rework.
12 chapters in this module
- Structuring the AI governance manual effectively
- Creating SOC-style narratives for ISO 42001
- Documenting AI system boundaries and interfaces
- Writing clear control descriptions for reviewers
- Including real examples of control execution
- Maintaining version control for documents
- Using standardized templates across engagements
- Integrating technical evidence into narratives
- Ensuring consistency with other compliance docs
- Preparing documents for external auditor review
- Reducing editing cycles before submission
- Archiving documentation for future reference
Module 7. Implementing AI Model Lifecycle Management
Integrate model development, deployment, monitoring, and retirement into governance workflows without slowing delivery.
12 chapters in this module
- Defining AI model lifecycle stages
- Documenting model development practices
- Ensuring reproducibility of training data
- Versioning models and dependencies
- Establishing deployment approval gates
- Monitoring model performance in production
- Detecting concept drift and model decay
- Setting retraining triggers and schedules
- Handling model deprecation and retirement
- Auditing model changes over time
- Integrating lifecycle steps into CI/CD
- Reducing technical debt in model management
Module 8. Operationalizing AI Monitoring and Human Oversight
Implement practical monitoring that ensures AI systems behave as intended and remain under human control.
12 chapters in this module
- Defining key performance indicators for AI
- Setting thresholds for human intervention
- Logging AI decisions for audit review
- Creating dashboards for oversight teams
- Testing human-in-the-loop processes
- Handling false positives and false negatives
- Ensuring response times for AI alerts
- Monitoring for bias and fairness drift
- Reviewing AI decisions during service reviews
- Documenting oversight activities
- Improving processes based on monitoring data
- Scaling oversight across multiple clients
Module 9. Conducting Internal AI Governance Reviews
Run effective internal reviews that identify gaps early and reduce audit surprises.
12 chapters in this module
- Scheduling regular governance check-ins
- Preparing evidence packages in advance
- Using checklists aligned to ISO 42001
- Involving cross-functional reviewers
- Identifying gaps before external audits
- Tracking open items to resolution
- Incorporating peer feedback
- Avoiding review fatigue with focus
- Documenting review outcomes
- Improving processes between cycles
- Benchmarking against industry peers
- Using reviews to strengthen team capability
Module 10. Preparing for External Audits and Client Reviews
Streamline the audit process by aligning documentation, evidence, and narratives to reviewer expectations.
12 chapters in this module
- Understanding auditor expectations for ISO 42001
- Organizing evidence packs for easy access
- Preparing for sample-based auditor requests
- Conducting pre-audit readiness checks
- Running internal mock audits
- Briefing team members on review protocols
- Handling auditor follow-up questions
- Responding to findings professionally
- Using audit feedback for improvement
- Reducing time spent in audit cycles
- Demonstrating compliance maturity
- Turning audits into credibility opportunities
Module 11. Integrating ISO 42001 with Existing Compliance Programs
Leverage synergies with other standards to avoid redundant work and strengthen overall compliance posture.
12 chapters in this module
- Mapping ISO 42001 to ISO 27001 controls
- Integrating with SOC 2 and SOC 3 requirements
- Aligning with NIST AI Risk Management Framework
- Reducing duplication with SOX controls
- Using COBIT for governance alignment
- Harmonizing documentation across frameworks
- Sharing evidence across audits
- Training teams on multi-standard expectations
- Avoiding framework fatigue
- Demonstrating efficiency to clients
- Positioning as a compliance leader
- Future-proofing for emerging regulations
Module 12. Scaling AI Governance Across Delivery Teams
Extend governance practices across teams while maintaining adaptability to client needs.
12 chapters in this module
- Creating reusable governance templates
- Training new delivery managers
- Onboarding client-specific variations
- Maintaining consistency across geographies
- Sharing best practices across projects
- Recognizing and rewarding governance excellence
- Building internal communities of practice
- Gathering feedback for continuous improvement
- Measuring governance maturity over time
- Reducing time to compliance readiness
- Becoming the reference point for peers
- Driving adoption through example
How this maps to your situation
- Service delivery under regulated client contracts
- AI integration into existing service offerings
- Client-facing compliance assurance packaging
- Cross-functional coordination in global teams
Before vs. after
Before
Spending cycles reconciling technical controls with client-facing compliance narratives, often under time pressure.
After
Producing structured, client-ready AI governance documentation that other teams reference and auditors accept.
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 6-8 hours total, designed to be completed in focused Sunday sessions.
If nothing changes
Continuing to rely on ad-hoc governance approaches increases rework, audit findings, and missed opportunities to build credibility with clients and internal stakeholders.
How this compares to the alternatives
Generic AI governance courses focus on principles without delivery context. This course is tailored to service delivery managers who must translate compliance into client-ready outcomes.
Frequently asked
Is this course focused on technical AI development?
No. It's designed for delivery managers who must govern AI systems, not build them. Content focuses on control, documentation, and assurance.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this to non-ISO 42001 clients?
Yes. The structure transfers to other compliance frameworks and strengthens your governance credibility broadly.
$199 one-time. Approximately 6-8 hours total, designed to be completed in focused Sunday sessions..
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