A tailored course, built for your situation
Direct sign-off authority on AI governance framework decisions
A 12-module course to establish ownership of AI governance calls within high-impact teams
$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 practitioner in talent or governance roles at AI-forward tech companies who influences policy implementation and cross-functional standards adoption
Who this is not for
Entry-level hires, individual contributors without cross-functional influence, or practitioners focused only on technical AI model development
What you walk away with
- Own the approval chain for AI governance documentation updates
- Make binding decisions on alignment with OECD AI Principles
- Lead cross-functional reviews without requiring senior sign-off
- Deploy standardized templates that accelerate team-wide compliance
- Build auditable records that reflect direct ownership of governance thresholds
The 12 modules (with all 144 chapters)
Module 1. Foundations of OECD AI Principles in talent and tech operations
Understand how the OECD AI Principles apply to recruitment, onboarding, and governance workflows in AI-driven organizations. Map each principle to operational decisions you already influence.
12 chapters in this module
- Origin of OECD AI Principles
- Fairness and non-discrimination in hiring
- Transparency in AI-augmented recruitment
- Accountability in team composition
- Robustness in hiring systems
- Respect for human rights
- Inclusive growth focus
- International cooperation angle
- Mapping to internal policies
- Linking to vendor standards
- Benchmarking maturity level
- Operationalizing due diligence
Module 2. Governance ownership in cross-functional AI initiatives
Identify where you can claim ownership in AI governance without overstepping. Learn to frame decisions as extensions of existing coordination authority.
12 chapters in this module
- Recognizing decision boundaries
- When to escalate versus act
- Claiming review authority
- Setting thresholds for autonomy
- Documenting ownership precedent
- Aligning with legal teams
- Engaging engineering leads
- Managing stakeholder pushback
- Building consensus quietly
- Using precedent to expand scope
- Tying to performance goals
- Measuring governance throughput
Module 3. Designing compliant AI recruitment workflows
Integrate OECD-aligned practices into job descriptions, screening processes, and candidate engagement to pre-empt compliance reviews.
12 chapters in this module
- AI use disclosure templates
- Bias mitigation in sourcing
- Candidate consent frameworks
- Audit-ready documentation
- Vendor AI tool assessments
- Hiring panel guidelines
- Scoring rubric design
- Candidate communication logs
- Retention of decision records
- Version control for workflows
- Policy opt-in mechanisms
- Feedback loop integration
Module 4. Policy thresholds and exception handling
Define clear rules for when deviations require approval and when you can resolve them independently.
12 chapters in this module
- Setting default acceptance levels
- Defining minor versus major changes
- Creating exception logs
- Approval delegation paths
- Time-bound overrides
- Risk-based triage model
- Documentation completeness rules
- Peer review triggers
- Escalation decision trees
- Post-action reporting
- Compliance drift monitoring
- Threshold adjustment protocol
Module 5. Stakeholder alignment without executive dependency
Lead alignment across legal, HR, and engineering using structured frameworks that reduce back-and-forth.
12 chapters in this module
- Pre-aligning meeting agendas
- Standardized comment cycles
- Role-based access definitions
- Feedback consolidation methods
- Silent approval workflows
- Version comparison techniques
- Stakeholder impact scoring
- Conflict de-escalation scripts
- RACI for governance tasks
- Escalation path documentation
- Decision log transparency
- Quarterly alignment canvass
Module 6. Building auditable governance artifacts
Create documentation that stands up to internal and external scrutiny without requiring rework.
12 chapters in this module
- Single source of truth design
- Metadata tagging standards
- Version history requirements
- Ownership attribution fields
- Change rationale capture
- Review timestamp protocols
- Access control documentation
- Retention schedule mapping
- Cross-reference indexing
- Audit trail generation
- Export-ready formatting
- Regulator-facing summaries
Module 7. Vendor AI tool governance
Own the evaluation and onboarding of third-party AI tools used in recruitment and talent operations.
12 chapters in this module
- Pre-vetting checklists
- Compliance gap analysis
- Data handling assessments
- Bias testing requirements
- Output transparency standards
- Human oversight mandates
- Contractual clause integration
- Performance benchmarking
- Renewal review authority
- Incident response planning
- Usage policy enforcement
- Offboarding documentation
Module 8. Team-level governance adoption
Drive consistent use of governance practices across coordinators, recruiters, and hiring managers.
12 chapters in this module
- Onboarding training design
- Quick-reference guide creation
- Governance champion roles
- Monthly compliance check-ins
- Peer audit pairings
- Template adoption tracking
- Feedback loop mechanisms
- Mistake logging without blame
- Recognition for adherence
- Updating team playbooks
- Leadership visibility tactics
- Sustainability planning
Module 9. Incident response for AI-assisted hiring
Lead the response when AI tools produce biased or inaccurate outcomes in recruitment.
12 chapters in this module
- Detection trigger setup
- Bias incident triage
- Candidate notification scripts
- Root cause documentation
- Remediation workflows
- Legal team coordination
- Internal reporting timelines
- Corrective action tracking
- Process improvement loops
- Training updates post-incident
- Public statement alignment
- Lessons learned archiving
Module 10. Continuous improvement in AI governance
Implement feedback systems that keep your governance approach adaptive and future-ready.
12 chapters in this module
- Candidate feedback collection
- Hiring manager surveys
- Performance metric review
- Regulatory change tracking
- Peer benchmarking
- Lessons learned integration
- Tool upgrade planning
- Policy sunset protocols
- Innovation testing windows
- Stakeholder input cycles
- Annual framework refresh
- Future-state forecasting
Module 11. Scaling governance ownership beyond initial scope
Extend your authority to adjacent domains by demonstrating consistent, low-friction outcomes.
12 chapters in this module
- Identifying adjacent workflows
- Demonstrating process efficiency
- Building stakeholder trust
- Documenting success metrics
- Proposing expanded remit
- Piloting new domains
- Leveraging peer advocates
- Measuring governance leverage
- Reducing review cycle time
- Increasing decision velocity
- Expanding template reuse
- Showcasing audit readiness
Module 12. Sustaining governance leadership over time
Ensure your governance role endures leadership changes, restructuring, and evolving AI capabilities.
12 chapters in this module
- Documenting institutional knowledge
- Onboarding successors
- Maintaining stakeholder maps
- Updating contact lists
- Preserving decision logs
- Archiving templates securely
- Creating handover checklists
- Defining continuity rules
- Scheduling leadership updates
- Tracking policy evolution
- Monitoring regulatory shifts
- Updating training materials
How this maps to your situation
- When onboarding a new AI-powered recruiting tool
- During internal compliance audit prep
- Before finalizing a high-impact hiring policy
- After a leadership transition in HR or legal
Before vs. after
Before
Reactive coordination, frequent escalations, dependency on approvals for standard updates
After
Ownership of final governance decisions, reduced review cycles, trusted authority on AI policy thresholds
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 to be completed alongside regular work over 6-8 weeks.
How this compares to the alternatives
Unlike generic AI ethics courses, this program focuses on concrete decision rights and documentation ownership within real-world talent operations. No other course trains practitioners to claim and defend direct sign-off authority on governance outcomes.
Frequently asked
Who is this course for?
Senior coordinators, HR leads, and governance practitioners who influence AI policy in talent or technical teams and want to own final decisions.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Does this course cover technical AI model development?
No. It focuses on governance, policy, documentation, and decision ownership in AI-augmented workflows, not model building.
$199 one-time. Approximately 3 hours per module, designed to be completed alongside regular work over 6-8 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