A tailored course, built for your situation
Mastering NIST AI RMF for HR Problem Solvers
Build defensible AI governance practices with structured reasoning and real-world examples
$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.
Feeling questioned or second-guessed when proposing AI-driven HR changes?
The situation this course is for
HR leaders are expected to lead on AI, but without a shared framework, it's easy to be challenged on approach. Without clear rationale, even good decisions get stalled.
Who this is for
HR practitioners leading AI adoption, workforce transformation, and governance in tech-forward organizations
Who this is not for
This course is not for consultants selling generic AI policies or engineers building models. It's for HR practitioners who need to justify and defend governance choices.
What you walk away with
- Map HR-driven AI decisions directly to NIST AI RMF functions and subcategories
- Document decision rationales using standardized framework language
- Anticipate pushback with pre-mapped counterpoints and real-world precedents
- Lead cross-functional AI governance discussions from a position of prepared depth
- Produce repeatable briefing templates that survive team and leadership changes
The 12 modules (with all 144 chapters)
Module 1. Introduction to NIST AI RMF and HR’s Role
Establish the foundation of the NIST AI Risk Management Framework and how HR uniquely contributes to governance. Understand the core functions: Govern, Map, Measure, and Manage. Learn how HR decisions in workforce planning and retraining align with RMF objectives.
12 chapters in this module
- What is NIST AI RMF
- Core functions explained
- HR’s role in AI governance
- Skill displacement and AI risk
- Govern function overview
- Map function overview
- Measure function overview
- Manage function overview
- Real-world AI governance cases
- HR-specific risk categories
- Linking HR outcomes to RMF
- First steps for HR practitioners
Module 2. Govern Function: HR Policies and Oversight
Dive into the Govern function, focusing on developing HR-aligned policies, accountability structures, and oversight mechanisms. Learn how to establish clear roles for AI-driven workforce changes and ensure ethical deployment in reskilling initiatives.
12 chapters in this module
- Govern function purpose
- HR policy design principles
- Accountability frameworks
- Ethical AI in HR contexts
- Stakeholder mapping
- Policy enforcement mechanisms
- Documenting oversight roles
- AI use case review process
- HR governance committee setup
- Risk tolerance thresholds
- Escalation paths
- Policy version control
Module 3. Map Function: Identifying HR Risks in AI Systems
Learn how to map AI system impacts to HR functions, including hiring, retention, and development. Identify where bias, transparency, and accountability matter most in workforce-facing AI tools.
12 chapters in this module
- Map function purpose
- HR-specific AI use cases
- Bias in hiring algorithms
- Transparency expectations
- Impact on employee trust
- Workforce sentiment tracking
- Reskilling risk exposure
- Mapping tool types to roles
- Risk heat mapping
- Cross-functional alignment
- Documentation standards
- Linking to NIST subcategories
Module 4. Measure Function: Evaluating AI Impact on Talent
Develop metrics for assessing AI's impact on workforce equity, mobility, and engagement. Learn how to measure fairness, interpretability, and effectiveness in HR-led AI initiatives.
12 chapters in this module
- Measure function purpose
- Fairness metrics for hiring
- Turnover risk indicators
- Promotion equity measures
- Employee sentiment analysis
- Reskilling success tracking
- Bias detection methods
- Interpretability in HR models
- Performance benchmarking
- Feedback loop design
- Data quality for HR AI
- Audit-ready reporting
Module 5. Manage Function: Mitigating Workforce Disruption
Build strategies to manage AI-driven workforce changes, including retraining programs, role transitions, and change communication. Align mitigation plans with NIST AI RMF’s Manage function.
12 chapters in this module
- Manage function purpose
- Change readiness assessment
- Retraining program design
- Role transition frameworks
- Communication strategy
- Stakeholder engagement
- Monitoring rollout success
- Support system integration
- Escalation protocols
- Mitigation timeline planning
- Workforce impact tracking
- Post-implementation review
Module 6. Documentation for Defensible Decision-Making
Create clear, source-backed documentation that supports HR’s AI governance choices. Learn how to structure artefacts so they stand up to scrutiny and enable peer review.
12 chapters in this module
- Why documentation matters
- Standardized template design
- Linking decisions to NIST
- Rationale writing techniques
- Evidence citation methods
- Version tracking
- Approval workflows
- Internal audit alignment
- Peer review preparation
- Decision registry setup
- Cross-team documentation
- Archiving governance records
Module 7. Anticipating Pushback with Framework Fluency
Prepare for challenges from engineering, legal, and leadership by grounding responses in NIST AI RMF. Develop go-to responses and reasoning paths for common objections.
12 chapters in this module
- Common pushback types
- Technical team objections
- Legal and compliance concerns
- Executive skepticism
- Cost versus value debates
- Speed versus safety trade-offs
- NIST-based rebuttals
- Pre-mapped counterpoints
- Scenario walkthroughs
- Building peer consensus
- Escalating with authority
- Staying within HR scope
Module 8. Cross-Functional AI Governance Leadership
Lead design sessions and working groups with engineering, security, and legal. Establish HR as a core voice in AI governance by speaking in shared framework language.
12 chapters in this module
- Leading governance sessions
- Speaking the framework language
- Aligning with security teams
- Partnering with legal
- Engaging engineering leads
- Facilitation techniques
- Conflict de-escalation
- Building shared artefacts
- Decision log maintenance
- Influence without authority
- HR as governance hub
- Sustaining cross-functional work
Module 9. AI Ethics and HR Policy Development
Develop AI ethics policies tailored to HR contexts, including hiring, performance, and development. Ensure alignment with NIST AI RMF’s Trustworthiness characteristics.
12 chapters in this module
- AI ethics in HR
- Hiring fairness principles
- Performance evaluation bias
- Development opportunity equity
- Transparency standards
- Explainability expectations
- Human oversight mechanisms
- Bias mitigation strategies
- Policy drafting process
- Stakeholder review
- Version control
- Policy enforcement tracking
Module 10. Workforce Transformation Playbook
Create a repeatable process for managing AI-driven talent changes. Build a playbook that documents decisions, outcomes, and lessons for future use.
12 chapters in this module
- Playbook purpose
- Phased rollout planning
- Stakeholder comms calendar
- Retraining module design
- Success metric tracking
- Feedback integration
- Change agent network
- Support resource mapping
- Lessons learned process
- Template adaptation
- Version control system
- Leadership reporting rhythm
Module 11. Vendor and Tool Governance in HR AI
Evaluate and govern third-party AI tools used in HR functions. Apply NIST AI RMF to vendor selection, contract terms, and integration planning.
12 chapters in this module
- HR tool vendor landscape
- Vendor evaluation criteria
- NIST alignment check
- Data privacy considerations
- Bias audit requirements
- Explainability expectations
- Contract terms for AI
- Pilot program design
- Integration risk mapping
- Performance tracking
- Exit strategy planning
- Ongoing vendor review
Module 12. Sustaining AI Governance Over Time
Ensure governance evolves with changing AI systems and workforce needs. Build processes that maintain defensibility across leadership and team changes.
12 chapters in this module
- Governance lifecycle
- Review and refresh cycles
- Leadership transition planning
- New hire onboarding
- Framework update tracking
- Regulatory change monitoring
- Internal audit prep
- Lessons documented
- Playbook iteration
- Stakeholder feedback loops
- Succession planning
- Long-term ownership
How this maps to your situation
- HR-led AI governance decisions
- Cross-functional AI design sessions
- Vendor AI tool evaluations
- Workforce transformation initiatives
Before vs. after
Before
Frequent challenges to HR’s AI decisions, relying on intuition or incomplete justification
After
Clear, source-backed rationale for every AI governance choice, grounded in NIST AI RMF
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 busy practitioners. Total investment: 36 hours over 3-6 weeks.
If nothing changes
Without defensible frameworks, HR risks being sidelined in AI governance conversations, losing influence on workforce strategy and ethical deployment.
How this compares to the alternatives
Unlike generic AI ethics courses, this program is tailored to HR practitioners using NIST AI RMF. Unlike consultant-led workshops, it provides permanent artefacts and self-paced mastery.
Frequently asked
Is this course technical or for engineers?
No, it's designed specifically for HR practitioners leading AI governance. No coding or engineering background required.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will I receive templates I can use at work?
Yes, every module includes downloadable templates and worked examples you can adapt to your organization.
$199 one-time. Approximately 3 hours per module, designed for busy practitioners. Total investment: 36 hours over 3-6 weeks..
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