A tailored course, built for your situation
Mandate on ISO 42001 AI Management Systems Design
Build approved AI governance artefacts that senior sponsors route directly to your desk
$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
Data Engineer at a global systems integrator working on regulated data pipelines and emerging AI governance workflows
Who this is not for
This is not for entry-level analysts, policy generalists, or professionals outside data and compliance-critical engineering roles
What you walk away with
- Own end-to-end ISO 42001 AI management system documentation with sign-off authority
- Receive peer-team escalations on AI control gaps before audit cycles begin
- Produce auditor-ready Statements of Applicability without senior review loops
- Design control mappings that survive cross-functional scrutiny
- Become the named drafter on regulator-facing AI governance summaries
The 12 modules (with all 144 chapters)
Module 1. Scope definition for AI management systems
Define scoping boundaries for ISO 42001 compliance using data lineage maps and system inventory inputs.
12 chapters in this module
- Data system boundary identification
- Mapping AI assets to control domains
- Stakeholder input for scope validation
- Version-controlled scope documentation
- Audit trail setup for scope changes
- Integration with existing data governance
- Documenting excluded controls with rationale
- Data owner sign-off workflow
- Scope freeze timing for review cycles
- Regulator-expected scope artifacts
- Cross-functional scope alignment
- Template: Scope statement with exclusions
Module 2. AI risk assessment framework integration
Embed ISO 42001 risk criteria into data pipeline risk registers with traceable outputs.
12 chapters in this module
- Threat modeling for AI pipelines
- Risk criteria from ISO 42001 Annex A
- Data-centric risk scoring inputs
- Integration with enterprise risk tools
- Risk register versioning setup
- Peer validation of risk inputs
- Risk treatment plan drafting
- Escalation paths for high-severity risks
- Risk acceptance documentation
- Audit-ready risk narrative outputs
- Cross-team risk alignment sessions
- Template: AI risk register with controls
Module 3. Control selection and mapping
Map ISO 42001 controls to data engineering workflows with implementation evidence paths.
12 chapters in this module
- Control relevance filtering
- Data pipeline control alignment
- Existing controls gap analysis
- Compensating control documentation
- Control owner assignment workflow
- Implementation evidence requirements
- Control testing frequency rules
- Documentation trail setup
- Mapping to NIST CSF equivalencies
- Integration with SOC 2 controls
- Peer review of control mapping
- Template: Control mapping matrix
Module 4. Statement of Applicability drafting
Produce regulator-ready SoAs with documented rationale for inclusions and exclusions.
12 chapters in this module
- SoA structure per ISO 42001
- Inclusion rationale writing
- Exclusion justification standards
- Data source validation for SoA inputs
- Version control for SoA updates
- Stakeholder review coordination
- Audit trail for rationale changes
- Cross-functional alignment inputs
- Regulator follow-up preparation
- SoA integration with evidence packs
- Final sign-off workflow
- Template: Working SoA document
Module 5. Evidence pack compilation
Assemble audit-ready documentation packs with traceable data access logs and policy references.
12 chapters in this module
- Evidence requirements per control
- Data access logging integration
- Policy document version tracking
- System configuration snapshots
- User permission audits
- Change management logs
- Automated evidence collection
- Manual evidence compilation workflow
- Evidence review timelines
- Gap identification and remediation
- Peer validation of evidence sets
- Template: Evidence pack index
Module 6. Internal audit preparation
Prepare for internal audits with pre-reviewed artefacts and response playbooks.
12 chapters in this module
- Audit timeline mapping
- Pre-audit evidence review
- Stakeholder alignment meetings
- Response assignment workflow
- Audit question tracking
- Follow-up evidence workflows
- Non-conformance documentation
- Remediation plan drafting
- Management response templates
- Audit report input drafting
- Post-audit review coordination
- Template: Audit response tracker
Module 7. External auditor engagement
Lead external auditor interactions with structured artefacts and escalation protocols.
12 chapters in this module
- Auditor briefing package
- Audit scope confirmation
- Evidence access provisioning
- Primary contact workflow
- Escalation path definition
- Technical deep-dive scheduling
- Clarification request response
- Findings validation process
- Management discussion inputs
- Audit report review cycle
- Post-audit action planning
- Template: Auditor engagement playbook
Module 8. AI governance control monitoring
Implement continuous monitoring for AI management system controls using automated alerts.
12 chapters in this module
- Control monitoring scope
- Automated log analysis setup
- Threshold definition for alerts
- False positive handling
- Review frequency standards
- Escalation to engineering teams
- Remediation tracking
- Monthly control health reports
- Stakeholder distribution list
- Integration with ticketing systems
- Audit trail for changes
- Template: Control monitoring dashboard
Module 9. Management review documentation
Generate executive-ready summaries for AI governance performance and improvement plans.
12 chapters in this module
- Review cycle timing
- Performance metric selection
- Incident trend analysis
- Control effectiveness reporting
- Resource gap identification
- Improvement initiative drafting
- Stakeholder input coordination
- Presentation deck structure
- Action item tracking
- Follow-up milestone setting
- Review meeting minutes
- Template: Management review pack
Module 10. Continuous improvement planning
Turn audit findings and monitoring data into prioritized improvement backlogs.
12 chapters in this module
- Finding severity scoring
- Backlog prioritization framework
- Resource availability inputs
- Engineering team alignment
- Timeline estimation
- Stakeholder approval workflow
- Implementation tracking
- Effectiveness validation
- Version control for updates
- Cross-team awareness rollout
- Success metric definition
- Template: Improvement backlog
Module 11. Cross-functional escalation handling
Manage inbound escalations from peer teams on control gaps and compliance questions.
12 chapters in this module
- Escalation intake workflow
- Triage criteria definition
- Initial response protocol
- Subject matter expert coordination
- Documentation requirements
- Timeline management
- Escalation logging
- Resolution validation
- Knowledge base updates
- Trend analysis for recurring issues
- Stakeholder reporting
- Template: Escalation response pack
Module 12. Regulator-facing summary drafting
Produce concise, accurate summaries of AI governance posture for regulatory submissions.
12 chapters in this module
- Regulator audience analysis
- Key message development
- Evidence citation standards
- Risk posture explanation
- Control effectiveness summaries
- Incident response inputs
- Third-party assurance references
- Executive sign-off workflow
- Translation for global regulators
- Version control for submissions
- Follow-up preparation
- Template: Regulator summary document
How this maps to your situation
- When initiating a new AI governance cycle
- During pre-audit evidence collection
- Responding to peer-team escalations
- Preparing for external auditor engagement
Before vs. after
Before
Reliant on cross-functional inputs and senior review for AI governance artefacts
After
Directly owns ISO 42001 AI management system deliverables with stakeholder-initiated escalations
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 for completion within 6 weeks
How this compares to the alternatives
Unlike generic compliance courses, this program delivers role-specific ISO 42001 AI management system artefacts used by global systems integrators in active regulatory cycles.
Frequently asked
Who is this course for?
Data Engineers and compliance-critical technologists leading AI governance system implementation in regulated environments.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does the course cover other frameworks?
Focus is exclusively on ISO 42001 AI management systems with references to SOC 2 and NIST CSF where aligned.
$199 one-time. Approximately 3 hours per module, designed for completion within 6 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