A tailored course, built for your situation
Mastering ISO 42001 for HR Business Partners in Technology Services
Build AI governance frameworks that align with enterprise standards and expand your influence in people strategy
$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.
Policy documentation that stalls due to cross-functional misalignment and repeated stakeholder chasing during compliance cycles
The situation this course is for
HR practitioners in tech services often find themselves reacting to AI governance requests rather than leading them. The lack of standardized frameworks leads to rework, inconsistent interpretation, and delayed implementation, especially under regulator or internal audit timelines. This course eliminates that friction by grounding your role in a recognized international standard.
Who this is for
HR Business Partner in a global IT and technology services firm, focused on talent development, organizational change, and compliance alignment. Works at the intersection of people strategy and enterprise risk. Increasingly involved in AI governance discussions but lacks a structured framework to lead confidently.
Who this is not for
Individuals seeking general AI literacy or technical implementation of AI models. Not designed for standalone compliance auditors or legal counsel without HR partnership responsibilities.
What you walk away with
- Lead ISO 42001-aligned AI governance initiatives within HR without deferring to technical teams
- Produce consistent, audit-ready documentation that reduces rework and stakeholder chasing
- Position HR as a co-owner of AI risk and governance, expanding functional influence
- Navigate cross-functional alignment with legal, compliance, and engineering using standardized language
- Deliver a repeatable governance playbook that survives leadership changes and project cycles
The 12 modules (with all 144 chapters)
Module 1. Introduction to ISO 42001 and the HR Leader’s Role
Understand the structure and intent of ISO 42001, with a focus on how HR professionals contribute to AI governance. Learn how this standard creates new space for HR to lead beyond talent management into enterprise risk and ethics.
12 chapters in this module
- Defining AI governance in the context of international standards
- How ISO 42001 differs from previous compliance frameworks
- HR’s strategic position in AI system lifecycle oversight
- Mapping HR responsibilities to ISO 42001 clauses 4, 6
- Case study: HR-led AI governance rollout in a global IT firm
- Common misconceptions about HR’s role in technical standards
- Aligning people strategy with AI governance objectives
- Building credibility with engineering and compliance teams
- Establishing governance boundaries between HR and IT
- Documenting HR-specific AI use cases for compliance
- Integrating ethics by design into recruitment and performance systems
- Setting expectations for cross-functional collaboration
Module 2. Clause 4: Context of the Organization
Learn how to define the internal and external factors affecting AI governance within your organization, with HR as a central assessor of cultural and workforce impact.
12 chapters in this module
- Identifying stakeholders influenced by HR-driven AI systems
- Assessing workforce readiness for AI adoption
- Evaluating organizational culture’s openness to AI ethics
- Documenting HR-specific regulatory and legal obligations
- Analyzing power dynamics in AI decision-making workflows
- Mapping HR processes vulnerable to algorithmic bias
- Defining scope for AI governance within talent operations
- Engaging employee resource groups in governance design
- Using sentiment data to inform governance boundaries
- Balancing innovation speed with employee trust
- Creating feedback loops from teams affected by AI tools
- Updating governance scope as workforce needs evolve
Module 3. Clause 5: Leadership and Commitment
Discover how HR can demonstrate leadership in AI governance by aligning executive sponsorship with people practices and ethical commitments.
12 chapters in this module
- Articulating HR’s role in AI governance leadership
- Securing executive buy-in for people-centered AI policies
- Developing leadership statements on AI ethics and fairness
- Aligning AI governance with company values and mission
- Establishing accountability for AI-related HR decisions
- Training managers to uphold AI governance principles
- Incorporating governance expectations into leadership KPIs
- Creating incentives for ethical AI behavior
- Handling conflicts between performance goals and AI ethics
- Communicating governance commitments to employees
- Measuring leadership adherence to AI policies
- Updating governance commitments after organizational changes
Module 4. Clause 6: Planning for AI Risk
Develop skills to proactively identify and plan for AI-related risks in HR processes, from recruitment to performance management.
12 chapters in this module
- Identifying high-risk HR processes using AI
- Conducting risk assessments for algorithmic decision-making
- Documenting potential harm from biased AI models
- Prioritizing risks based on employee impact and likelihood
- Designing mitigation strategies for recruitment algorithms
- Planning for transparency in AI-driven performance reviews
- Assessing vendor AI tools for compliance with ISO 42001
- Creating risk registers specific to HR use cases
- Integrating AI risk planning into change management
- Setting thresholds for acceptable AI influence in HR
- Engaging legal and compliance in risk prioritization
- Updating risk plans after incident reviews
Module 5. Clause 7: Support and Awareness
Equip yourself to lead training, communication, and documentation efforts that ensure organizational awareness of AI governance in HR contexts.
12 chapters in this module
- Developing AI governance awareness programs for HR teams
- Creating accessible training for non-technical stakeholders
- Designing onboarding materials for new hires using AI tools
- Documenting HR-specific AI policies and procedures
- Translating technical jargon into people-focused language
- Building internal knowledge bases for AI governance
- Measuring employee understanding of AI systems
- Running workshops on ethical AI use in people operations
- Supporting managers in discussing AI with their teams
- Establishing helpdesk protocols for AI-related concerns
- Updating support materials after policy changes
- Evaluating the effectiveness of awareness campaigns
Module 6. Clause 8: Operational Controls in HR
Implement operational controls for AI systems used in recruitment, performance, and talent development, ensuring alignment with ISO 42001 requirements.
12 chapters in this module
- Defining control objectives for HR AI applications
- Validating fairness in AI-driven candidate screening
- Monitoring performance evaluation algorithms for bias
- Setting access controls for sensitive AI-generated insights
- Establishing approval workflows for AI model updates
- Auditing AI tool usage across departments
- Documenting decision trails for AI-assisted promotions
- Integrating human oversight into automated workflows
- Creating fallback procedures when AI systems fail
- Ensuring data quality for AI training in HR contexts
- Reviewing third-party AI vendor controls
- Updating operational controls after audits
Module 7. Clause 9: Performance Evaluation
Learn how to measure and report on the effectiveness of AI governance in HR processes using meaningful, employee-centered metrics.
12 chapters in this module
- Defining KPIs for ethical AI use in people operations
- Tracking employee trust in AI-driven decisions
- Measuring fairness in AI-assisted recruitment outcomes
- Evaluating transparency of AI explanations to employees
- Conducting regular audits of HR AI systems
- Benchmarking against industry standards and peers
- Gathering feedback from employees affected by AI
- Analyzing grievance data related to AI decisions
- Reporting governance performance to leadership
- Using metrics to justify governance investments
- Adjusting evaluation methods after organizational changes
- Documenting performance trends over time
Module 8. Clause 10: Improvement and Incident Response
Develop a structured approach to improving AI governance in HR, including incident reporting, root cause analysis, and continuous refinement.
12 chapters in this module
- Establishing channels for AI-related employee concerns
- Documenting incidents involving AI in HR processes
- Conducting root cause analysis for AI-driven errors
- Implementing corrective actions for biased outcomes
- Updating policies after incident reviews
- Creating post-mortems for failed AI deployments
- Building a culture of psychological safety around AI
- Preventing retaliation for reporting AI issues
- Integrating lessons into training and awareness
- Tracking improvement over time
- Engaging external experts after major incidents
- Updating incident response plans after drills
Module 9. HR-Specific AI Use Cases and Governance
Explore real-world applications of AI in HR and how to apply ISO 42001 principles to recruitment, performance, and talent development systems.
12 chapters in this module
- Governance for AI-powered resume screening tools
- Ethical considerations in AI-driven candidate matching
- Managing bias in automated interview analysis
- Transparency requirements for algorithmic performance reviews
- AI in succession planning and leadership assessment
- Using AI to identify skill gaps and development needs
- Balancing personalization with privacy in learning platforms
- AI in employee churn prediction models
- Handling sensitive data in wellness and engagement tools
- Auditing third-party HR tech vendors for compliance
- Creating governance checklists for new AI tools
- Retiring legacy AI systems responsibly
Module 10. Cross-Functional Collaboration Models
Master strategies for leading AI governance initiatives that require alignment between HR, legal, compliance, IT, and business units.
12 chapters in this module
- Defining roles and responsibilities in joint governance
- Building trust between HR and technical teams
- Creating shared vocabulary for AI ethics discussions
- Running cross-functional governance workshops
- Resolving conflicts between operational speed and compliance
- Documenting decisions from interdepartmental meetings
- Establishing escalation paths for governance disputes
- Integrating HR input into technical design phases
- Aligning AI governance timelines across functions
- Measuring collaboration effectiveness
- Managing governance in decentralized organizations
- Updating collaboration models after reorganizations
Module 11. Preparing for Certification and Audit
Prepare HR-specific documentation and evidence needed for ISO 42001 certification and internal audits, reducing last-minute scrambling.
12 chapters in this module
- Identifying HR-specific audit requirements
- Compiling evidence for AI governance in people processes
- Preparing for auditor interviews as an HR lead
- Documenting risk assessments and mitigation actions
- Organizing policies and procedures for review
- Demonstrating leadership commitment from HR
- Responding to auditor findings in people systems
- Creating audit-ready templates for recurring reviews
- Leveraging internal audits to improve HR practices
- Coordinating with central compliance teams
- Tracking open items until closure
- Updating documentation after audit cycles
Module 12. Sustaining Governance Beyond Certification
Ensure long-term success by embedding AI governance into HR culture, processes, and leadership expectations.
12 chapters in this module
- Integrating governance into onboarding for new HR staff
- Updating policies as AI capabilities evolve
- Maintaining momentum after initial certification
- Recognizing teams that uphold AI ethics
- Sharing governance successes across the organization
- Revisiting governance scope after major changes
- Conducting regular refreshers for HR leaders
- Adapting to new regulations affecting HR AI use
- Building redundancy into governance ownership
- Measuring cultural adoption of AI ethics
- Planning for leadership transitions in governance roles
- Establishing governance as a continuous practice
How this maps to your situation
- HR’s expanding role in enterprise AI governance
- Need for standardized frameworks in cross-functional alignment
- Growing scrutiny on algorithmic fairness in talent systems
- Opportunity to lead beyond traditional HR boundaries
Before vs. after
Before
Reactive involvement in AI governance discussions, dependent on technical teams for framework knowledge, frequent rework on policy documents, limited influence beyond talent operations
After
Proactive leadership in AI governance, ability to produce audit-ready documentation independently, expanded remit into enterprise risk and ethics, recognized as a cross-functional partner in technology decisions
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 90 minutes per module, designed for completion over 8, 10 weeks with weekend study sessions. Includes just-in-time resources for immediate application.
If nothing changes
Without structured governance, HR remains sidelined in AI decisions that directly impact workforce trust, fairness, and compliance. This increases exposure to regulatory scrutiny, reputational risk, and internal conflict when AI systems produce biased or poorly explained outcomes.
How this compares to the alternatives
Generic AI ethics courses lack HR-specific applications and compliance alignment. Internal training often lacks ISO 42001 structure. This course fills the gap by combining international standards with practical HR implementation, giving you a unique advantage in governance leadership.
Frequently asked
Is this course technical or suitable for non-engineers?
Designed specifically for HR and people leaders, it avoids technical jargon and focuses on governance, policy, and organizational impact using plain language.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me lead AI governance without a technical background?
Yes. The course equips you with standardized frameworks and language to lead confidently across functions, even without coding or data science expertise.
$199 one-time. Approximately 90 minutes per module, designed for completion over 8, 10 weeks with weekend study sessions. Includes just-in-time resources for immediate 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