A tailored course, built for your situation
Mastering ISO 42001 for Global ERP Product Leaders
Build AI governance frameworks that scale with enterprise demand and position you as the definitive internal resource.
$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.
AI governance is shifting from discussion to deployment, but without a clear owner, decisions stall and influence spreads thin.
The situation this course is for
Teams are scrambling to define who owns AI risk, compliance, and control mapping. Without a recognized internal leader, ERP product teams face repeated rework, inconsistent client messaging, and diluted authority during audits or vendor reviews.
Who this is for
Global ERP product or client manager at a Big 4 or global systems integrator, responsible for compliance-adjacent delivery and cross-functional alignment on governance frameworks.
Who this is not for
Entry-level consultants, standalone AI engineers without product ownership, or practitioners focused solely on technical implementation without client or control-facing responsibilities.
What you walk away with
- Be the first named when ISO 42001 planning starts
- Produce governance documentation that accelerates client sign-off
- Lead internal workshops with confidence in control structure
- Position yourself as the bridge between engineering and compliance
- Turn abstract AI governance mandates into deployable product roadmaps
The 12 modules (with all 144 chapters)
Module 1. Understanding ISO 42001 and Its Role in Enterprise AI
Establish foundational knowledge of ISO 42001, its structure, and how it differs from prior governance standards. Learn why ERP-integrated AI systems are now in scope and how this creates new ownership roles.
12 chapters in this module
- Defining AI management systems in the context of global ERP
- How ISO 42001 complements existing COBIT and SOC 2 frameworks
- The shift from ethics-first to audit-ready AI governance
- Why multinational clients now demand ISO 42001 alignment
- Mapping ISO 42001 clauses to ERP product lifecycle stages
- Key differences between ISO 42001 and NIST AI RMF
- The role of product managers in governance ownership
- How the firm client expectations are shifting post-the current cycle
- Identifying high-risk AI use cases in ERP workflows
- Integrating ISO 42001 into RFP response documentation
- Common misconceptions about certification readiness
- Setting realistic timelines for framework adoption
Module 2. Positioning Yourself as the Governance Owner
Learn how to claim ownership of AI governance without formal mandate. Develop language and artefacts that position you as the natural leader on ISO 42001 initiatives.
12 chapters in this module
- Using client feedback to justify governance leadership
- Documenting recurring client questions as proof of need
- Creating internal visibility through targeted updates
- Aligning with compliance teams without overstepping
- Framing governance as enablement not restriction
- Building credibility through structured decision logs
- Presenting governance ownership as client risk reduction
- Leveraging cross-functional project roles to expand influence
- Developing a personal narrative around AI accountability
- Tracking engagement patterns that signal leadership gaps
- Positioning early wins as team outcomes not personal gains
- Measuring recognition through referral frequency
Module 3. Scoping AI Systems Within ERP Environments
Learn to identify which AI components in ERP platforms fall under ISO 42001, how to document them, and how to assess their risk profile for governance planning.
12 chapters in this module
- Inventorying AI features in core ERP modules
- Differentiating between embedded and third-party AI
- Assessing autonomy level in decision-support workflows
- Mapping data flows for AI-driven forecasting tools
- Determining system boundaries for audit purposes
- Classifying AI components by risk and impact
- Documenting training data sources and lineage
- Evaluating explainability requirements by use case
- Identifying human-in-the-loop points in automation
- Tracking model update frequency and triggers
- Integrating AI inventory into existing CMDBs
- Maintaining living documentation for client reviews
Module 4. Designing the AI Governance Framework
Build a tailored AI governance structure aligned with ISO 42001 requirements, designed to scale across global clients and ERP configurations.
12 chapters in this module
- Structuring governance committees with clear roles
- Defining decision rights for model deployment
- Creating escalation paths for ethical concerns
- Integrating governance into change management
- Developing approval workflows for high-risk AI
- Establishing model validation standards
- Setting thresholds for human override
- Designing audit trails for AI decision records
- Documenting rationale for model selection
- Building version control into AI components
- Aligning with data protection and privacy teams
- Creating feedback loops from end users
Module 5. Implementing Risk Assessment Processes
Develop repeatable methods for evaluating AI risk in ERP contexts, aligned with ISO 42001 Annex A controls and client-specific risk appetites.
12 chapters in this module
- Adapting ISO 42001 risk categories to ERP use cases
- Scoring models based on financial and operational impact
- Assessing bias potential in procurement and HR modules
- Evaluating reputational risk in client-facing AI
- Creating risk heat maps for executive reporting
- Integrating risk assessments into sprint planning
- Using client industry as a risk modifier
- Benchmarking against peer implementations
- Documenting risk acceptance decisions
- Updating risk profiles after system changes
- Linking risk scores to control requirements
- Communicating risk levels to non-technical stakeholders
Module 6. Developing Transparency and Documentation
Create client-ready documentation that satisfies ISO 42001 requirements and builds trust through clarity and consistency.
12 chapters in this module
- Writing AI system statements for client audits
- Creating model cards for internal and external use
- Developing user guides that explain AI behavior
- Documenting data quality assurance processes
- Producing version comparison reports
- Maintaining accessible records of training data
- Creating incident response playbooks
- Standardizing disclosure language across engagements
- Building executive summaries from technical details
- Archiving documentation for multi-year retention
- Using templates to ensure consistency
- Aligning documentation with SOC 2 Type II reports
Module 7. Integrating Human Oversight Mechanisms
Design effective human oversight processes that meet ISO 42001 requirements while remaining practical in high-volume ERP environments.
12 chapters in this module
- Defining appropriate levels of human review
- Designing alerts for high-risk AI decisions
- Setting thresholds for mandatory human approval
- Training staff on AI decision monitoring
- Creating escalation paths for uncertain cases
- Documenting human override actions
- Measuring oversight effectiveness over time
- Balancing automation speed with control needs
- Integrating oversight into existing workflows
- Using simulation to test oversight design
- Reporting oversight metrics to leadership
- Updating oversight rules based on performance
Module 8. Managing Data Quality for AI Systems
Implement data quality controls that support reliable AI performance in ERP systems and satisfy ISO 42001 data governance requirements.
12 chapters in this module
- Defining data quality metrics for AI inputs
- Monitoring data drift in production systems
- Validating data lineage across integrations
- Handling missing or corrupted data points
- Assessing bias in training data sets
- Creating data refresh protocols
- Documenting data preprocessing steps
- Establishing data ownership roles
- Auditing data access and modification
- Integrating data quality into CI/CD pipelines
- Reporting data health to stakeholders
- Responding to data quality incidents
Module 9. Ensuring System Robustness and Reliability
Build resilience into AI components within ERP systems to meet ISO 42001 performance and safety expectations.
12 chapters in this module
- Testing AI components under edge conditions
- Designing fallback procedures for model failure
- Monitoring system performance in real time
- Setting performance baselines for AI modules
- Creating automated recovery workflows
- Evaluating model degradation over time
- Stress testing AI decision throughput
- Validating results against known outcomes
- Integrating redundancy for critical functions
- Documenting system limitations clearly
- Updating models based on performance data
- Communicating reliability to end users
Module 10. Aligning with Global Compliance Requirements
Integrate ISO 42001 with other regulatory frameworks and client mandates to create a unified compliance posture.
12 chapters in this module
- Mapping ISO 42001 to GDPR requirements
- Aligning with NIS2 directives for critical infrastructure
- Integrating with SOX controls for financial AI
- Meeting DORA resilience expectations
- Connecting to sector-specific regulations
- Harmonizing with client-specific governance rules
- Documenting compliance across jurisdictions
- Preparing for cross-border data flows
- Addressing auditor questions proactively
- Updating compliance posture after legal changes
- Creating compliance dashboards for leadership
- Reducing duplication across frameworks
Module 11. Conducting Internal Audits and Readiness Reviews
Prepare for ISO 42001 certification by conducting thorough internal audits and readiness assessments.
12 chapters in this module
- Scheduling audit cycles aligned with client needs
- Selecting qualified internal auditors
- Developing audit checklists from ISO 42001 clauses
- Reviewing documentation completeness
- Testing control effectiveness
- Interviewing system owners and users
- Identifying gaps in implementation
- Prioritizing remediation efforts
- Documenting audit findings clearly
- Tracking corrective actions to closure
- Preparing for external certification
- Using audit results to improve processes
Module 12. Sustaining and Improving the Governance System
Establish continuous improvement processes to keep AI governance effective and relevant as technology and regulations evolve.
12 chapters in this module
- Setting up regular governance review meetings
- Collecting feedback from users and clients
- Monitoring changes in AI technology trends
- Updating policies after incidents
- Reassessing risk profiles periodically
- Incorporating lessons from audits
- Training new staff on governance expectations
- Measuring governance maturity over time
- Benchmarking against industry leaders
- Publishing annual governance reports
- Evolving the framework with ERP upgrades
- Recognizing team contributions to governance
How this maps to your situation
- ERP product leadership in global firms
- AI governance implementation at scale
- Compliance integration into product delivery
- Cross-functional influence without direct authority
Before vs. after
Before
AI governance feels fragmented, with ownership unclear and client demands evolving faster than internal alignment.
After
You lead coherent, client-ready governance frameworks that position you as the natural point person for ISO 42001 initiatives.
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: 90 minutes of focused reading and implementation planning, best completed in three 30-minute sessions.
If nothing changes
Without clear ownership, AI governance decisions will default to ad hoc responses, creating rework, inconsistent client messaging, and missed opportunities to position yourself as the expert.
How this compares to the alternatives
Unlike generic AI ethics courses, this program delivers actionable structure for ISO 42001 compliance within ERP systems , designed specifically for product leaders who need to translate standards into client-ready solutions.
Frequently asked
Is this course technical or strategic?
It's designed for product and client leaders , strategic with concrete implementation tools, not technical deep dives.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help with client acquisition?
Yes , by positioning you as the go-to resource for ISO 42001, you enhance client trust and differentiate the firm's offering.
$199 one-time. 90 minutes of focused reading and implementation planning, best completed in three 30-minute 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