A tailored course, built for your situation
Mastering ISO 42001 for Operations Specialists in Global Business Services
A practitioner-led course to command AI governance decisions with precision
$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.
Not another compliance layer, this is about owning the decisions that shape how AI governance lands in operations
The situation this course is for
Most practitioners inherit governance checklists. You’ll define them.
Who this is for
Operations Specialist in a global B2B service environment managing cross-functional compliance and process controls
Who this is not for
This is not for auditors, consultants, or executives seeking high-level overviews. It’s for hands-on owners of implementation.
What you walk away with
- Define the scope of AI governance coverage without escalation
- Choose control implementation methods for ISO 42001 requirements
- Approve documentation formats and evidence collection workflows
- Lead vendor AI compliance assessments end to end
- Ship audit-ready outputs on first submission
The 12 modules (with all 144 chapters)
Module 1. Foundations of ISO 42001 in Operations Contexts
Understand how ISO 42001 applies specifically to business operations, not just technical AI development. Covers terminology, high-level structure, and integration with existing control environments.
12 chapters in this module
- What ISO 42001 means for non-AI developers
- Mapping clauses to operational workflows
- AI system boundary definition
- Governance vs. technical implementation
- Role of operations in AI risk assessment
- Linking ISO 42001 to vendor management
- Integration with existing compliance frameworks
- Audit expectations for operations teams
- Ownership models across functions
- Documentation standards for non-engineers
- Key overlaps with ISO 27001 and SOC 2
- Common misalignments in practice
Module 2. Scoping AI Systems in Business Operations
Learn to define what counts as an AI system in your domain and set clear boundaries for governance coverage.
12 chapters in this module
- Identifying AI-enabled processes
- Vendor-provided AI vs in-house logic
- Determining AI system boundaries
- Documenting decision logic sources
- Exclusion criteria with justification
- Change tracking for scope updates
- Stakeholder alignment on scope
- Version control for scoping artefacts
- Audit trail for boundary decisions
- Handling gray-area tools
- Escalation paths for disputes
- Scope sign-off workflow
Module 3. Assigning Accountability for AI Governance
Establish clear ownership models for AI governance decisions within operations-led workflows.
12 chapters in this module
- Defining RACI for AI controls
- Operational ownership vs technical delivery
- Vendor accountability integration
- Cross-team governance forums
- Escalation thresholds
- Internal audit liaison protocols
- Documentation custodianship
- Change control integration
- Performance metric ownership
- Compliance validation ownership
- Training responsibility assignment
- Review cycle leadership
Module 4. Risk Assessment for Operational AI Use
Conduct proportionate risk assessments tailored to business operations, not R&D environments.
12 chapters in this module
- Operational risk criteria definition
- Impact levels for business processes
- Likelihood assessment methods
- Stakeholder input collection
- Risk register structure
- Acceptable risk thresholds
- Mitigation tracking
- Third-party risk integration
- Risk treatment workflows
- Documentation templates
- Review frequency decisions
- Audit readiness checks
Module 5. Designing Human Oversight Mechanisms
Implement human-in-the-loop requirements that are practical for operations teams.
12 chapters in this module
- Defining oversight points
- Role clarity for interveners
- Intervention logging standards
- Escalation procedures
- Training for human reviewers
- Workload impact assessment
- Automation override protocols
- Review frequency decisions
- Documentation requirements
- Audit evidence collection
- Continuous monitoring integration
- Performance metrics
Module 6. Data Governance for AI in Operations
Apply data quality and provenance controls relevant to business-process AI.
12 chapters in this module
- Data source documentation
- Quality thresholds definition
- Bias detection in operational data
- Data lineage standards
- Retention and archiving rules
- Access control alignment
- Vendor data handling rules
- Data refresh protocols
- Anonymization requirements
- Impact of poor data on AI output
- Monitoring data drift
- Remediation workflows
Module 7. Transparency and Explanation Requirements
Meet ISO 42001 transparency obligations without technical overreach.
12 chapters in this module
- User notification standards
- Purpose specification documentation
- Explanation depth by use case
- Stakeholder communication plans
- Internal transparency protocols
- Vendor transparency demands
- Audit trail requirements
- Change disclosure processes
- Training material obligations
- Language clarity standards
- Feedback mechanisms
- Complaint handling integration
Module 8. Robustness, Accuracy, and Reliability Controls
Implement operational checks for AI performance and reliability.
12 chapters in this module
- Performance baseline setting
- Accuracy monitoring methods
- Failure mode tracking
- Fallback procedure design
- Stress testing protocols
- Version comparison tracking
- User feedback integration
- Error logging standards
- Recovery time objectives
- Service level alignment
- Vendor performance reporting
- Continuous improvement loop
Module 9. Organizational Competency and Training
Ensure team readiness without overburdening staff.
12 chapters in this module
- Role-specific training needs
- Competency assessment methods
- Training frequency decisions
- Vendor staff inclusion
- Certification tracking
- Knowledge retention protocols
- Onboarding integration
- Refresher training cycles
- Performance validation
- Compliance attestations
- Documentation standards
- Audit evidence preparation
Module 10. Monitoring and Maintenance of AI Systems
Establish ongoing oversight that fits operational rhythms.
12 chapters in this module
- Review frequency decisions
- KPI tracking design
- Performance deviation alerts
- Change impact assessments
- Version control protocols
- Decommissioning criteria
- Stakeholder update routines
- Audit trail maintenance
- Incident response integration
- Lessons learned documentation
- Vendor review coordination
- Compliance verification cycle
Module 11. Preparing for Internal and External Audits
Generate audit-ready outputs without last-minute effort.
12 chapters in this module
- Audit scope definition
- Evidence collection workflows
- Documentation structure
- Interview preparation protocols
- Audit response coordination
- Deficiency tracking
- Corrective action workflows
- Management report drafting
- Vendor audit coordination
- Evidence retention rules
- Follow-up timeline
- Continuous improvement integration
Module 12. Continuous Improvement and Governance Evolution
Adapt governance as AI systems and business needs change.
12 chapters in this module
- Feedback collection design
- Lessons learned integration
- Control effectiveness reviews
- Benchmarking against peers
- Process refinement cycles
- Technology change adaptation
- Regulatory update monitoring
- Stakeholder expectation tracking
- Governance maturity assessment
- Resource planning
- Vendor innovation tracking
- Annual review protocol
How this maps to your situation
- AI governance scoping
- Control implementation ownership
- Audit preparation authority
- Vendor assessment leadership
Before vs. after
Before
Reactive compliance, shared ownership, unclear boundaries, delayed approvals
After
Proactive governance, clear scope definition, direct sign-off, audit-ready outputs
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 with real-world application.
If nothing changes
Without clear command of AI governance decisions, operations teams risk duplicated effort, audit findings, and loss of influence over control design.
How this compares to the alternatives
Unlike generic compliance courses, this course focuses on operational ownership of AI governance decisions under ISO 42001, specifically for practitioners who must implement, not just review.
Frequently asked
Is this course technical?
No. It’s designed for operations practitioners who need to own governance decisions, not build AI models.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this to non-AI automation tools?
Yes. The decision frameworks apply to any automated decision-making system.
$199 one-time. Approximately 3 hours per module, designed for completion within 6 weeks with real-world application..
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