A tailored course, built for your situation
Mastering ISO 42001 for Global Compensation and Benefits Leaders
Turn AI governance into strategic influence within your current scope
$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.
Most compensation leaders are being asked to weigh in on AI tools but lack the formal governance framework to assert influence confidently.
The situation this course is for
Without a recognized standard, input on AI-driven compensation platforms is often overruled or deferred. Influence defaults to IT or compliance teams with louder frameworks.
Who this is for
Senior HR and compensation leaders with global scope, expected to govern AI use in people programs but not yet anchored in formal standards.
Who this is not for
Individual contributors without decision influence, AI ethicists without governance roles, or compliance auditors focused solely on technical controls.
What you walk away with
- Lead AI governance discussions with authority grounded in ISO 42001 requirements
- Own the design of AI assurance controls for compensation systems
- Document a defensible, repeatable framework for AI oversight in people analytics
- Influence vendor selection and procurement criteria for AI-enabled HR platforms
- Align ethical AI use with global compensation policy and equity principles
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and the AI Governance Landscape
Establish foundational knowledge of ISO 42001 and its relevance to enterprise risk and people systems. Understand how governance extends beyond IT into HR technology decisions.
12 chapters in this module
- What ISO 42001 solves
- AI risks in compensation systems
- Governance vs ethics debate
- The role of HR leadership
- Scope boundaries in practice
- Mapping to existing policies
- Regulatory drivers global
- Stakeholder expectations
- Assurance maturity levels
- Integration with HRIS
- Vendor governance entry points
- First internal alignment steps
Module 2. Understanding the AI Management System Framework
Break down the core components of an AI Management System (AIMS) and how it applies to compensation governance. Identify where your current authority intersects with framework requirements.
12 chapters in this module
- AIMS core principles
- Leadership commitment criteria
- Policy documentation standards
- Risk assessment entry points
- HR-specific AI risks
- Equity and fairness controls
- Transparency obligations
- Human oversight layers
- Lifecycle oversight
- Decision logging
- Bias monitoring
- Review frequency planning
Module 3. Leadership Commitment and Organizational Context
Define how senior HR leaders establish tone and accountability. Learn to frame AI governance as a people strategy imperative, not just a compliance task.
12 chapters in this module
- Executive sponsorship
- Scope definition process
- Stakeholder mapping
- HR leadership accountability
- Risk appetite setting
- Compensation policy alignment
- Global reporting lines
- Cross-border data use
- Ethics committee integration
- Budget linkage
- Mandate documentation
- Internal endorsement
Module 4. AI Policy Development for HR Systems
Build a defensible, organization-specific AI policy tied to compensation integrity and equity goals. Use ISO 42001 clauses to justify requirements.
12 chapters in this module
- Policy statement drafting
- Fairness definitions
- Transparency thresholds
- Vendor disclosure rules
- Employee communication plans
- Audit readiness
- Update protocols
- Escalation paths
- Compliance monitoring
- Performance metrics
- Documentation standards
- Third-party alignment
Module 5. Risk Assessment and Impact Analysis for AI Tools
Conduct structured risk assessments for AI-powered compensation tools. Identify bias, equity, and legal exposure points unique to global pay programs.
12 chapters in this module
- Risk identification
- Bias in pay models
- Cross-jurisdiction risks
- Data source validation
- Model transparency gaps
- Audit trail completeness
- Remediation planning
- Severity scoring
- Likelihood assessment
- Risk treatment options
- Documentation templates
- Review cycles
Module 6. Establishing Human Oversight Mechanisms
Design human-in-the-loop processes for AI-driven compensation decisions. Ensure meaningful review exists at critical decision points.
12 chapters in this module
- Oversight triggers
- Approval workflows
- Exception handling
- Review frequency
- Compensation committee role
- Manager training
- Escalation protocols
- Documentation requirements
- Bias override process
- Audit readiness
- Performance tracking
- Feedback integration
Module 7. Data Governance for AI in Compensation Systems
Apply ISO 42001 data controls to HR data used in AI models. Ensure quality, fairness, and privacy across global datasets.
12 chapters in this module
- Data quality standards
- Bias detection methods
- Source documentation
- Data lineage tracking
- Access control rules
- Anonymization techniques
- Consent management
- Retention policies
- Cross-border transfers
- Vendor data handling
- Audit trail design
- Data owner roles
Module 8. Vendor and Third-Party Governance
Lead vendor evaluations with ISO 42001 as a baseline. Define contract requirements and audit rights for AI-enabled HR platforms.
12 chapters in this module
- Vendor selection criteria
- RFP integration
- Contract clauses
- Audit rights
- Transparency obligations
- Bias testing requirements
- Data use restrictions
- Remediation protocols
- Performance SLAs
- Exit strategies
- Compliance certifications
- Ongoing monitoring
Module 9. Monitoring, Measurement, and Continuous Improvement
Implement metrics and review processes to ensure AI governance remains effective. Turn oversight into a continuous cycle, not a one-time project.
12 chapters in this module
- KPI selection
- Performance dashboards
- Review frequency
- Audit integration
- Remediation tracking
- Stakeholder feedback
- Bias retesting
- Model drift detection
- Policy update triggers
- Training effectiveness
- Benchmarking
- Improvement roadmaps
Module 10. Internal Audit and Compliance Demonstration
Prepare for internal and external scrutiny. Document compliance in a way that satisfies auditors while preserving strategic discretion.
12 chapters in this module
- Audit planning
- Evidence collection
- Control mapping
- Compliance narratives
- Gap remediation
- Executive summaries
- Risk-based sampling
- Vendor audit rights
- Documentation templates
- Interview preparation
- Regulator expectations
- Continuous audit integration
Module 11. Training and Awareness for HR Teams
Roll out AI governance understanding across HR teams. Build organization-wide competence without overburdening staff.
12 chapters in this module
- Training needs analysis
- Role-based modules
- Manager toolkits
- Awareness campaigns
- Policy communication
- Case studies
- Feedback loops
- Competency tracking
- Reinforcement methods
- Leadership messaging
- Global adaptation
- Ongoing education
Module 12. Integration with Broader ESG and Governance Frameworks
Align AI governance with ESG, DEI, and enterprise risk initiatives. Position HR as a leader in responsible AI across the organization.
12 chapters in this module
- ESG linkage
- DEI integration
- Board-level alignment
- Risk framework convergence
- Sustainability reporting
- Stakeholder communication
- Public disclosures
- Investor expectations
- Third-party ratings
- Benchmarking
- Future-proofing
- Strategic positioning
How this maps to your situation
- HR leaders adopting AI in pay equity tools
- Global teams deploying AI for salary benchmarking
- Organizations facing regulatory scrutiny on algorithmic fairness
- Compensation leaders needing to justify vendor choices
Before vs. after
Before
AI governance input is reactive, ad hoc, and often deferred to compliance or IT teams.
After
You lead AI governance initiatives within compensation, with documented authority and structured frameworks in place.
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 flexible pacing.
If nothing changes
Without a formal framework, influence on AI use in compensation systems will default to other functions, reducing HR's strategic impact.
How this compares to the alternatives
Generic AI ethics courses lack actionable governance pathways. Internal frameworks are often incomplete. This course delivers a standards-based, implementable approach tailored to global HR leadership.
Frequently asked
Is this course only for HR professionals in regulated industries?
No, it's designed for global HR and compensation leaders in any industry where AI is used in people decisions.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me influence vendor decisions?
Yes, Module 8 focuses entirely on vendor governance using ISO 42001 as leverage.
$199 one-time. Approximately 3 hours per module, designed for completion within 6 weeks with flexible pacing..
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