A tailored course, built for your situation
Mastering ISO 42001 for Senior Service Delivery Leaders
A structured path to owning AI governance scope within your current role
$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 evidence that slips through cycles
The situation this course is for
Service delivery leaders face mounting pressure to produce clean, cross-vendor audit artifacts on demand, yet lack standardized playbooks to automate evidence collection and validation across complex partner ecosystems.
Who this is for
Senior service delivery managers in global IT services firms managing multi-vendor delivery and compliance requirements under regulator scrutiny
Who this is not for
Individual contributors focused only on internal IT operations, or executives seeking high-level governance overviews without hands-on deliverables
What you walk away with
- Own the full lifecycle of AI governance evidence from policy intent to signed-off packages
- Reduce time spent on audit preparation by automating vendor attestation workflows
- Gain standing invitations to governance design sessions due to proven deliverable quality
- Produce standardized SoAs that pass regulator review the first time
- Lead AI governance scope expansion without requiring a role change
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 and Its Role in Service Delivery
Establish a clear foundation in ISO 42001 principles and how they apply specifically to service delivery frameworks in global IT organizations.
12 chapters in this module
- Defining AI management systems in real-world delivery contexts
- Mapping ISO 42001 clauses to service delivery control points
- Differentiating AI governance from traditional IT service compliance
- Aligning AI transparency requirements with SLAs and contracts
- Recognizing audit triggers specific to vendor-integrated workflows
- Identifying where AI governance intersects with change management
- Leveraging ISO 42001 to strengthen client-facing service narratives
- Documenting decision rights in multi-vendor AI implementations
- Using the standard to clarify ownership across delivery phases
- Integrating AI risk registers into existing service review cycles
- Benchmarking current practices against ISO 42001 readiness levels
- Structuring initial gap assessments for leadership review
Module 2. Scoping AI Governance Across Vendor Ecosystems
Learn how to define and control the boundaries of AI governance when delivery spans multiple vendors and subcontractors.
12 chapters in this module
- Defining scope boundaries in hybrid delivery models
- Classifying AI system components owned by third parties
- Documenting vendor participation in AI lifecycle stages
- Establishing clear demarcation lines for audit accountability
- Negotiating governance rights in master service agreements
- Mapping vendor workflows to required control evidence
- Identifying critical handoff points for AI model updates
- Enforcing version control standards across partner teams
- Creating governance escalation paths for non-compliant vendors
- Building audit trails that survive vendor transitions
- Standardizing definitions of 'AI system' across contracts
- Validating vendor attestation formats against ISO 42001
Module 3. Building Risk-Based AI Control Frameworks
Develop risk-informed control architectures tailored to dynamic service delivery environments.
12 chapters in this module
- Assessing AI risk exposure in managed service offerings
- Prioritizing controls based on client impact severity
- Linking control design to contractual service obligations
- Documenting rationale for control exclusions or adaptations
- Integrating AI risk criteria into vendor onboarding
- Creating repeatable templates for control implementation
- Validating control effectiveness through simulation
- Establishing thresholds for automated control alerts
- Mapping controls to ISO 42001 clause 8.3 requirements
- Maintaining control consistency across delivery regions
- Updating control frameworks in response to AI model drift
- Using control health dashboards in leadership reporting
Module 4. Designing Evidence Collection Workflows
Implement systematic processes for gathering and validating audit-ready evidence across distributed teams.
12 chapters in this module
- Identifying minimum evidence sets per ISO 42001 clause
- Assigning evidence ownership in shared delivery models
- Scheduling evidence collection aligned with review cycles
- Creating standardized formats for vendor-submitted artifacts
- Validating completeness of third-party documentation
- Using checklists to eliminate evidence gaps
- Building automated reminders for pending evidence items
- Integrating evidence tracking with service delivery tools
- Establishing version control for evidence documents
- Documenting evidence review decisions and rationale
- Preparing evidence bundles for internal pre-audits
- Streamlining evidence handover to compliance teams
Module 5. Managing Change in AI Systems and Controls
Establish protocols for managing AI system changes while maintaining governance integrity.
12 chapters in this module
- Defining what constitutes an AI system change
- Implementing change control gates for AI models
- Assessing impact of data source modifications
- Evaluating AI performance degradation triggers
- Updating documentation after model retraining
- Notifying stakeholders of AI behavior changes
- Revalidating controls after configuration updates
- Maintaining audit trails for AI decision logic
- Handling emergency changes without bypassing governance
- Integrating AI change logs into service reports
- Aligning change cycles with client notification requirements
- Documenting rollback procedures for AI components
Module 6. Operationalizing AI Transparency Requirements
Turn abstract transparency principles into operational deliverables across service engagements.
12 chapters in this module
- Documenting AI system purpose and intended use cases
- Creating client-facing AI disclosure statements
- Recording data provenance for model training sources
- Publishing model update histories in service portals
- Maintaining logs of AI decision explanations
- Implementing human oversight mechanisms
- Designing fallback procedures for AI failures
- Tracking AI performance against defined metrics
- Providing accessible AI system documentation
- Establishing channels for client AI inquiries
- Responding to requests for AI decision rationale
- Updating transparency artifacts with each release
Module 7. Conducting Internal AI Governance Reviews
Lead rigorous internal assessments that prepare teams for external validation.
12 chapters in this module
- Scheduling recurring governance review cycles
- Preparing review checklists based on ISO 42001
- Gathering evidence ahead of formal audit windows
- Interviewing team members on control execution
- Assessing vendor compliance with AI requirements
- Identifying control gaps in joint delivery workflows
- Documenting findings with specific improvement actions
- Prioritizing remediation based on risk exposure
- Tracking closure of governance action items
- Reporting governance health to leadership
- Using review data to improve future delivery
- Benchmarking performance across service lines
Module 8. Preparing for External AI Audits
Execute flawless external audit cycles with confidence in evidence quality and completeness.
12 chapters in this module
- Understanding auditor expectations for ISO 42001
- Scheduling pre-audit readiness assessments
- Compiling complete statement of applicability documents
- Validating vendor attestations before submission
- Rehearsing team responses to common audit questions
- Organizing evidence repositories for quick access
- Preparing executive summaries of AI governance
- Coordinating responses across delivery stakeholders
- Addressing auditor findings with corrective plans
- Maintaining composure during regulator inquiries
- Documenting audit outcomes and follow-up actions
- Updating internal practices based on audit feedback
Module 9. Sustaining AI Governance Through Leadership Cycles
Ensure governance maturity persists through personnel and leadership changes.
12 chapters in this module
- Documenting governance decisions in organizational memory
- Creating onboarding materials for new team members
- Standardizing governance practices across regions
- Institutionalizing playbooks beyond individual owners
- Transferring vendor relationship knowledge
- Maintaining continuity during leadership transitions
- Archiving critical decisions and rationale
- Updating governance artifacts with organizational changes
- Preserving lessons learned from past audits
- Ensuring new hires understand control expectations
- Building redundancy into evidence collection roles
- Establishing cross-functional governance forums
Module 10. Scaling AI Governance Across Service Lines
Extend proven governance models to new service offerings and business units.
12 chapters in this module
- Identifying governance transfer opportunities
- Adapting playbooks for different service types
- Standardizing evidence requirements across offerings
- Training delivery teams on governance expectations
- Measuring governance maturity across units
- Sharing best practices between service lines
- Aligning governance metrics with business goals
- Securing buy-in from service leadership
- Recognizing teams for governance excellence
- Driving continuous improvement through feedback
- Expanding scope based on client demand signals
- Positioning governance as a delivery differentiator
Module 11. Optimizing AI Governance with Automation
Integrate technical solutions to reduce manual effort in governance execution.
12 chapters in this module
- Identifying automation candidates in evidence collection
- Integrating API calls for real-time data access
- Using workflow tools for vendor attestations
- Automating control monitoring with dashboards
- Implementing document generation for SoAs
- Setting up alert systems for control failures
- Leveraging version control for policy tracking
- Connecting governance tools to service platforms
- Validating automated outputs for audit readiness
- Maintaining human oversight in automated flows
- Documenting automation architecture for auditors
- Measuring time savings from automation gains
Module 12. Leading AI Governance Evolution in Services
Position yourself as the central force in advancing AI governance maturity within your organization.
12 chapters in this module
- Tracking emerging AI governance standards and trends
- Influencing service design with governance insights
- Proposing enhancements based on operational experience
- Sharing lessons with peer organizations
- Contributing to industry working groups
- Mentoring junior team members in governance practice
- Recognizing governance as career development
- Balancing innovation with compliance requirements
- Communicating governance value to clients
- Shaping future delivery models with governance input
- Measuring long-term impact of governance improvements
- Establishing lasting credibility as a governance leader
How this maps to your situation
- Q3 audit preparation cycle
- Vendor compliance tracking
- Cross-regional service delivery
- AI system lifecycle management
Before vs. after
Before
Spending cycles chasing evidence from vendors and scrambling before audits
After
Owning a repeatable process that delivers clean audit packages with minimal effort
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 9 hours total, designed for completion in 30-minute increments across two weeks.
If nothing changes
Without structured governance, organizations face increased scrutiny, client distrust, and operational fragility during audits and service escalations.
How this compares to the alternatives
Unlike generic compliance courses, this program delivers role-specific workflows, vendor-integrated evidence templates, and real-world audit preparation tactics tailored to senior service delivery leaders in global IT services.
Frequently asked
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is prior knowledge of ISO 42001 required?
No , the course is designed for practitioners new to the standard, with a clear ramp from fundamentals to advanced implementation.
Will this help with regulator-facing audits?
Yes , every module builds toward producing clean, defensible artifacts that pass external review cycles.
$199 one-time. Approximately 9 hours total, designed for completion in 30-minute increments across two 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