A tailored course, built for your situation
Expanded influence in AI governance decisions across talent and technical domains
A tailored course for Talent Acquisition leaders shaping AI-ready organizations
$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.
Who this is for
Senior Talent Acquisition leader in a fast-moving AI organization, trusted to align workforce strategy with technical ambition
Who this is not for
Recruiters focused only on volume hiring or transactional talent operations
What you walk away with
- Lead talent strategy integration into formal AI governance frameworks
- Own workforce planning aligned with NIST AI RMF implementation cycles
- Shape cross-functional influence through structured people-system mapping
- Document decision rights in AI talent governance for leadership visibility
- Drive proactive reskilling plans tied to AI governance milestones
The 12 modules (with all 144 chapters)
Module 1. AI Governance Trends Shaping Talent Strategy
Examine how AI governance standards like NIST AI RMF create new openings for talent leaders to shape organizational readiness.
12 chapters in this module
- Enterprise adoption of NIST AI RMF
- Talent's role in governance foundation
- Signals from innovator organizations
- Workforce implications by domain
- Mapping AI risk to team composition
- Talent gaps in model lifecycle roles
- Responsible AI hiring benchmarks
- Vendor partnerships and talent access
- Executive expectations on AI teams
- Workforce planning under scrutiny
- Governance-first organizational design
- Early indicators of talent debt
Module 2. Integrating Talent Strategy with NIST AI RMF
Learn how to align workforce planning with each core function of the NIST AI RMF to increase remit and visibility.
12 chapters in this module
- Mapping Govern function to hiring
- Talent needs in Map phase
- Measure phase staffing models
- Design phase role clarity
- Train phase capability sourcing
- Validate phase assurance roles
- Deploy phase support teams
- Monitor phase operational roles
- Govern phase leadership needs
- Cross-phase talent coordination
- Identifying missing roles
- Documenting workforce coverage
Module 3. Workforce Planning Under AI Risk Classifications
Translate AI risk tiers into staffing strategies that preempt technical bottlenecks and compliance gaps.
12 chapters in this module
- Understanding risk impact levels
- Tier 1 systems and staffing rules
- Tier 2 workforce triggers
- Tier 3 hiring thresholds
- External vs internal sourcing
- Contractor governance rules
- Reskilling pipeline design
- Certification requirements
- Audit-readiness hiring
- Leadership representation needs
- Succession planning under risk
- Budget alignment with risk tier
Module 4. Talent’s Role in AI Risk Assessments
Position Talent as a core participant in AI risk reviews by contributing workforce data and organizational insight.
12 chapters in this module
- Workforce data for risk scoring
- Team tenure and model stability
- Certification coverage gaps
- Hiring velocity metrics
- Cross-functional team balance
- Leadership oversight indicators
- Turnover risk modeling
- Skills inventory integration
- Vendor staffing compliance
- Audit evidence readiness
- Peer benchmarking inputs
- Reporting workforce resilience
Module 5. Designing AI-Ready Organization Structures
Architect team topologies that support governed AI development while expanding Talent’s strategic footprint.
12 chapters in this module
- Centers of excellence models
- Embedded AI teams
- Hybrid governance structures
- Talent’s place in org chart
- Reporting line decisions
- Dual-hat role design
- AI ethics staffing models
- Cross-domain coordination
- Matrix structures and flow
- Decision rights mapping
- Influence without authority
- Documenting organizational design
Module 6. Building Cross-Functional Influence
Develop playbooks for earning a seat in AI governance forums through demonstrated capability and structured contributions.
12 chapters in this module
- Identifying key decision forums
- Mapping stakeholder priorities
- Creating value in meetings
- Pre-reads and position papers
- Speaking the risk language
- Anticipating technical concerns
- Workforce data storytelling
- Influence through documentation
- Building peer alliances
- Feedback loop integration
- Tracking influence growth
- Elevating talent insights
Module 7. Workforce Resilience and Audit Readiness
Ensure talent strategies support audit requirements and long-term sustainability of AI systems.
12 chapters in this module
- Audit expectations for staffing
- Evidence of role clarity
- Documented hiring rationale
- Retention under scrutiny
- Succession in high-risk roles
- Training completion tracking
- Certification validation
- Vendor staffing audits
- Workforce diversity metrics
- Equity in promotion paths
- Long-term capability planning
- Reporting to oversight bodies
Module 8. Talent Sign-Off in AI Framework Decisions
Establish formal input rights in AI governance framework adoption and updates.
12 chapters in this module
- Identifying sign-off points
- Workforce impact assessments
- Change management triggers
- Talent review gates
- Version control processes
- Stakeholder consultation logs
- Documented rationale archiving
- Escalation paths for talent
- Cross-team approval flows
- Governance committee roles
- Leadership alignment tactics
- Formalizing your remit
Module 9. Reskilling Strategies for AI Governance Roles
Design internal mobility paths that close critical skill gaps in AI governance functions.
12 chapters in this module
- Identifying reskill candidates
- Assessment frameworks
- Learning pathways by role
- Mentorship integration
- External certification plans
- Internal credentialing
- Time-to-competency goals
- Manager support systems
- Progress tracking metrics
- Retention impact analysis
- Budgeting for development
- Scaling reskilling programs
Module 10. Metrics That Expand Talent’s Remit
Measure and communicate outcomes that position Talent as a strategic driver of AI governance success.
12 chapters in this module
- Hiring speed by risk tier
- Time-to-fill governance roles
- Reskilling completion rate
- Retention in critical roles
- Diversity in AI teams
- Certification attainment rate
- Workforce coverage ratio
- Strategic hire ratio
- Influence metric design
- Leadership engagement index
- Cross-functional feedback
- Talent impact scorecard
Module 11. Documenting Decision Rights and Influence
Create a living playbook that captures Talent’s growing remit in AI governance decisions.
12 chapters in this module
- Decision rights mapping
- Influence tracking system
- Stakeholder logs
- Playbook versioning
- Evidence of expansion
- Cross-functional recognition
- Escalation ownership
- Policy input documentation
- Meeting contribution logs
- Leadership feedback archive
- Remit boundary clarity
- Growth narrative drafting
Module 12. Sustaining Momentum in Evolving AI Governance
Institutionalize Talent’s role in AI governance to ensure continued expansion of scope and impact.
12 chapters in this module
- Leadership renewal planning
- Succession for key roles
- Knowledge transfer design
- Playbook maintenance
- Feedback integration
- Trend monitoring systems
- Benchmark updates
- Peer sharing forums
- Lessons learned cycles
- Internal advocacy groups
- External representation
- Long-term vision setting
How this maps to your situation
- When launching a new AI initiative
- During NIST AI RMF implementation
- Before audit cycles begin
- When expanding team responsibilities
Before vs. after
Before
Talent strategy operates parallel to AI governance, with limited input into core decisions.
After
Talent Acquisition owns key inputs into NIST AI RMF implementation, with documented influence across workforce planning, risk assessment, and organizational design.
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: 30-45 minutes per module, designed to fit within weekly planning cycles.
How this compares to the alternatives
Generic AI governance courses focus on technical controls and ignore Talent’s strategic role. This course is built specifically for senior HR and Talent leaders who are positioned to expand their remit within current roles.
Frequently asked
Who is this course for?
Senior Talent Acquisition leaders in organizations adopting formal AI governance frameworks like NIST AI RMF.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course cover technical AI details?
No. It focuses on Talent’s strategic influence in AI governance decisions, not model development or engineering controls.
$199 one-time. 30-45 minutes per module, designed to fit within weekly planning cycles..
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