A tailored course, built for your situation
Mastering ISO 42001 for Senior AI-ML Solutions Architects
A tailored course to expand your influence across AI governance domains and global teams
$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
Senior AI-ML Solutions Architects in global systems integrators who are leading AI delivery and ready to scale their governance influence
Who this is not for
Junior data scientists, non-technical compliance staff, or professionals without hands-on AI deployment experience
What you walk away with
- Lead ISO 42001-aligned AI governance initiatives across multiple client engagements
- Standardise AI risk assessment templates used by cross-functional teams
- Serve as the internal reference on AI governance for peers and stakeholders
- Shape AI governance scope for new projects before development begins
- Deliver repeatable governance artefacts that accelerate client onboarding
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 in AI Context
Foundational principles of ISO 42001 and their application to AI systems in enterprise environments.
12 chapters in this module
- What ISO 42001 means for AI practitioners
- Core clauses every AI architect must know
- How ISO 42001 differs from general AI ethics
- Mapping AI lifecycle to ISO requirements
- Global adoption trends in AI governance
- Key terminology every implementer needs
- Interpreting 'AI system' in standard terms
- Scope definition for AI projects
- Alignment with organisational objectives
- Documented information requirements
- Governance vs operational controls
- Integration with existing AI frameworks
Module 2. AI Risk Assessment Design
Designing risk assessments that align with ISO 42001 requirements and real-world AI deployments.
12 chapters in this module
- Identifying AI-specific risk sources
- Stakeholder mapping for AI governance
- Creating risk likelihood matrices
- Impact categorisation for AI outcomes
- Bias and fairness in assessment design
- Transparency risk scoring
- Human oversight thresholds
- Performance degradation risks
- Data lifecycle risks in AI
- Model drift and monitoring risks
- Third-party AI vendor risks
- Risk treatment planning
Module 3. Governance Structure Setup
Building internal governance bodies and accountability structures that meet ISO 42001 standards.
12 chapters in this module
- Defining roles in AI governance
- Establishing oversight committees
- Authority levels for model approval
- Escalation paths for AI incidents
- Cross-regional governance alignment
- Client-facing governance reporting
- Vendor oversight frameworks
- Audit readiness for AI systems
- Incident response coordination
- Documentation ownership
- Change control for AI models
- Continuous monitoring ownership
Module 4. AI System Documentation
Creating comprehensive documentation for AI systems that satisfies ISO 42001 requirements.
12 chapters in this module
- Model card design and content
- System specifications for AI
- Data provenance documentation
- Training data description
- Model development process logs
- Version control for AI systems
- Human oversight procedures
- Performance monitoring dashboards
- Bias assessment records
- Update and retraining logs
- Security configuration records
- Decommissioning procedures
Module 5. Transparency and Explainability
Implementing transparency measures that align with ISO 42001 expectations for AI systems.
12 chapters in this module
- User-facing transparency design
- Explainability by audience type
- Model confidence reporting
- Limitations disclosure
- Human-in-the-loop documentation
- Decision rationale logging
- Error communication protocols
- Performance uncertainty reporting
- Stakeholder communication templates
- Audit trail for AI decisions
- Third-party explainability tools
- Standardised transparency reports
Module 6. Human Oversight Mechanisms
Designing human oversight processes that meet ISO 42001 requirements for AI systems.
12 chapters in this module
- Oversight threshold definition
- Human review triggers
- Intervention authority levels
- Monitoring frequency design
- Escalation protocols
- Training for human reviewers
- Performance feedback loops
- Audit logging for oversight
- Override procedures
- Escalation tracking
- Decision validation checks
- Post-deployment oversight
Module 7. AI System Lifecycle Controls
Implementing controls across the AI system lifecycle in accordance with ISO 42001.
12 chapters in this module
- Project initiation controls
- Data collection standards
- Model development oversight
- Testing and validation protocols
- Deployment approval process
- Monitoring baseline setup
- Retraining triggers
- Performance degradation response
- Model update controls
- Version deprecation
- System decommissioning
- Knowledge transfer process
Module 8. Bias and Fairness Management
Establishing systematic approaches to manage bias and ensure fairness in AI systems.
12 chapters in this module
- Bias detection methods
- Fairness metrics selection
- Demographic data handling
- Disparate impact analysis
- Bias mitigation techniques
- Model retraining for fairness
- Stakeholder feedback collection
- Bias audit design
- Third-party bias assessment
- Ongoing fairness monitoring
- Transparency in bias reporting
- Bias response protocols
Module 9. Security and Robustness
Ensuring AI systems meet security and robustness requirements under ISO 42001.
12 chapters in this module
- Model security design
- Data integrity controls
- Adversarial attack resistance
- Model inversion protection
- Input validation standards
- System availability requirements
- Resilience testing
- Security incident response
- Penetration testing for AI
- Model integrity verification
- Update authenticity checks
- Security audit preparation
Module 10. Third-Party AI Governance
Managing governance for third-party AI systems and vendor-supplied models.
12 chapters in this module
- Vendor due diligence process
- Contractual requirements
- Third-party audit rights
- Model documentation standards
- Performance monitoring of vendors
- Incident response coordination
- Compliance verification
- Change notification requirements
- Data handling oversight
- Subcontractor management
- Exit strategy planning
- Vendor risk reassessment
Module 11. Internal Audit and Review
Conducting internal audits and reviews to ensure ongoing compliance with ISO 42001.
12 chapters in this module
- Audit planning process
- Checklist development
- Evidence collection methods
- Nonconformity tracking
- Corrective action process
- Management review inputs
- Audit scheduling
- Cross-functional audit teams
- Audit reporting structure
- Follow-up verification
- Trend analysis from audits
- Audit readiness culture
Module 12. Continuous Improvement
Establishing processes for continuous improvement of AI governance systems.
12 chapters in this module
- Performance metric tracking
- Stakeholder feedback loops
- Incident root cause analysis
- Regulatory change monitoring
- Technology change adaptation
- Lessons learned process
- Benchmarking against peers
- Improvement initiative prioritisation
- Resource allocation for upgrades
- Governance framework updates
- Change implementation process
- Success measurement framework
How this maps to your situation
- AI governance in client-facing projects
- Internal AI system compliance
- Cross-regional AI deployments
- Vendor-managed AI solutions
Before vs. after
Before
Leading AI projects without a structured governance framework, responding to requests reactively.
After
Shaping AI governance across multiple business lines, proactively guiding new initiatives with ISO 42001 standards.
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 working professionals. Total time: 36 hours over 4-6 weeks.
If nothing changes
Without structured governance skills, even advanced AI systems face compliance delays, stakeholder pushback, and scalability limits in regulated environments.
How this compares to the alternatives
Unlike generic AI ethics courses, this program focuses on ISO 42001 implementation with concrete templates and decision frameworks used by leading global firms.
Frequently asked
Is this course relevant for practitioners outside the EU?
Yes. ISO 42001 is a global standard applicable across regions, industries, and organisational sizes.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does the course include templates?
Yes. Every module includes downloadable templates and worked examples for immediate use.
$199 one-time. Approximately 3 hours per module, designed for working professionals. Total time: 36 hours over 4-6 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