A tailored course, built for your situation
Influence through ISO 42001 implementation
Shape AI governance decisions with confidence and clarity
Who this is for
Senior technical leader driving AI governance and compliance decisions
Who this is not for
Individuals looking for introductory AI or compliance training not tied to ISO 42001 decision-making
What you walk away with
- Lead ISO 42001 scoping discussions with authority
- Influence vendor selection and audit boundaries
- Drive alignment between technical teams and executive stakeholders
- Shape internal AI governance policy before it’s finalized
- Position yourself as the reference point on AI risk and controls
The 12 modules (with all 144 chapters)
- Mapping ISO 42001 clauses to real-world AI systems
- Defining organizational boundaries under Clause 4
- Determining leadership roles in AI governance
- Scoping AI systems under management control
- Establishing internal versus external AI use cases
- Identifying high-risk versus low-risk AI activities
- Documenting AI inventory for compliance
- Setting accountability for AI lifecycle stages
- Aligning with other frameworks like SOC 2
- Integrating with existing risk management processes
- Establishing AI governance policy thresholds
- Building the foundation for internal audits
- Translating controls for engineering teams
- Framing risk for non-technical leaders
- Engaging legal on AI liability boundaries
- Securing buy-in from product leadership
- Running cross-functional alignment workshops
- Managing differing interpretations of AI risk
- Documenting stakeholder input for audits
- Building trust through transparency
- Creating feedback loops across teams
- Handling resistance to change
- Prioritizing actions based on input
- Establishing ongoing governance forums
- Defining risk criteria under ISO 42001 Clause 6
- Classifying AI system impact levels
- Assessing bias and fairness risks
- Evaluating transparency and explainability
- Mapping data provenance and quality
- Identifying model monitoring needs
- Scoring risk severity and likelihood
- Prioritizing remediation efforts
- Documenting risk treatment plans
- Integrating with incident response frameworks
- Validating risk assessment outputs
- Updating assessments over time
- Structuring policy for readability and action
- Writing clear roles and responsibilities
- Defining approval workflows
- Setting thresholds for model deployment
- Documenting data governance expectations
- Establishing model monitoring standards
- Creating audit trails for decisions
- Aligning with ethical AI principles
- Incorporating third-party risk rules
- Versioning and maintaining policy
- Training teams on policy adoption
- Measuring policy effectiveness
- Mapping controls to ISO 42001 Annex A
- Implementing human oversight requirements
- Ensuring accuracy and reliability
- Managing data quality processes
- Setting model validation protocols
- Controlling access to AI systems
- Documenting model updates and changes
- Tracking model performance over time
- Enforcing secure development practices
- Auditing control effectiveness
- Updating controls based on feedback
- Scaling controls across teams
- Planning audit scope and objectives
- Selecting audit team members
- Developing audit checklists
- Interviewing process owners
- Reviewing documentation and logs
- Evaluating control design and operation
- Identifying gaps and root causes
- Reporting findings clearly
- Prioritizing corrective actions
- Tracking closure of findings
- Preparing for external audits
- Improving audit processes
- Assessing vendor AI maturity
- Evaluating third-party model risks
- Defining contractual obligations
- Conducting vendor audits
- Monitoring ongoing compliance
- Managing open-source AI components
- Tracking external model updates
- Establishing incident reporting with vendors
- Enforcing data protection clauses
- Creating exit strategies for bad actors
- Building vendor scorecards
- Negotiating right-to-audit terms
- Collecting performance metrics
- Analyzing audit findings trends
- Reviewing incident reports
- Soliciting team feedback
- Updating risk assessments regularly
- Revising policies based on experience
- Improving training effectiveness
- Scaling best practices
- Benchmarking against peers
- Reporting progress to leadership
- Celebrating improvements
- Planning future enhancements
- Understanding auditor expectations
- Organizing documentation efficiently
- Preparing process narratives
- Demonstrating control effectiveness
- Responding to findings professionally
- Negotiating scope and timelines
- Providing timely evidence
- Clarifying interpretation differences
- Avoiding over-sharing
- Maintaining audit independence
- Following up on recommendations
- Building long-term auditor relationships
- Identifying governance champions
- Adapting policies to local needs
- Standardizing core controls
- Creating shared tooling
- Training regional leads
- Establishing centralized oversight
- Managing decentralized execution
- Aligning KPIs across units
- Sharing lessons learned
- Avoiding duplication
- Measuring consistency
- Supporting innovation within bounds
- Mapping common controls across standards
- Avoiding redundant audits
- Aligning control owners
- Sharing documentation efficiently
- Coordinating audit schedules
- Harmonizing risk language
- Creating unified reporting
- Educating teams on overlaps
- Reducing compliance overhead
- Strengthening defense-in-depth
- Optimizing resource use
- Demonstrating enterprise-wide maturity
- Building personal credibility
- Sharing wins strategically
- Mentoring emerging leaders
- Publishing internal thought leadership
- Speaking at cross-functional forums
- Influencing strategic roadmaps
- Shaping executive understanding
- Staying current on developments
- Joining industry groups
- Contributing to standards evolution
- Maintaining visibility
- Leaving a governance legacy
How this maps to your situation
- Preparing for first ISO 42001 audit
- Scaling AI governance across product teams
- Responding to executive demand for oversight
- Reducing compliance rework across frameworks
Before vs. after
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 2-3 hours per week over 12 weeks.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses specifically on how to wield influence within the ISO 42001 implementation process, giving you tools to shape outcomes, not just understand them.
Frequently asked
Within 24 hours your account in the learning environment is provisioned and the tailored implementation playbook is delivered alongside it.