A tailored course, built for your situation
Influence on AI Governance Direction with OECD AI Principles
Shape internal standards and lead cross-functional alignment using globally recognised AI governance benchmarks
$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 technical practitioner influencing AI governance decisions within a data platform environment
Who this is not for
Entry-level engineers, product marketers, or consultants without hands-on governance experience
What you walk away with
- Lead internal AI governance working groups with authority
- Anchor technical design decisions in OECD-aligned reasoning
- Influence vendor selection and integration roadmaps
- Drive consistency in cross-team AI policy interpretation
- Become the go-to reference for governance sign-off
The 12 modules (with all 144 chapters)
Module 1. Foundations of the OECD AI Principles
Understand the five pillars of the OECD AI Principles and how they map to technical implementation decisions in modern data platforms.
12 chapters in this module
- AI system lifecycle phases
- Human agency and oversight
- Technical robustness essentials
- Transparency expectations
- Fairness benchmarks
- Privacy by design alignment
- Accountability structures
- Global adoption trends
- Sector-specific guidance
- Stakeholder mapping
- Policy intent decoding
- Implementation maturity models
Module 2. Translating Principles into Policy
Turn abstract values into enforceable standards that engineering teams can implement and auditors can verify.
12 chapters in this module
- From principle to control
- Policy drafting conventions
- Scope definition techniques
- Enforceability testing
- Versioning governance
- Exception handling design
- Cross-team feedback loops
- Sign-off workflows
- Integration with SDLC
- Monitoring triggers
- Incident response mapping
- Stakeholder review cadence
Module 3. Influencing Design Authority
Position yourself as the governance voice in technical architecture discussions without formal power.
12 chapters in this module
- Design review entry points
- Pre-mortem framing
- Risk lever identification
- Alternative proposal structuring
- Stakeholder pre-briefing
- Consensus-building tactics
- Decision log documentation
- Escalation path design
- Influence without ownership
- Peer credibility signals
- Technical debt trade-offs
- Roadmap alignment arguments
Module 4. Vendor Evaluation Frameworks
Lead the selection process for third-party AI tools with a structured, principle-based assessment model.
12 chapters in this module
- Request for information design
- Scoring rubric creation
- OECD alignment mapping
- Due diligence triggers
- Integration risk flags
- Compliance gap analysis
- Audit trail requirements
- Data provenance checks
- Explainability benchmarks
- Model drift detection
- Human oversight mechanisms
- Exit strategy planning
Module 5. Internal Audit Enablement
Equip internal audit teams with the tools and references they need to validate AI governance effectively.
12 chapters in this module
- Audit scope definition
- Evidence checklist creation
- Control testing methods
- Exception reporting design
- Sampling strategy development
- Remediation tracking
- Cross-functional verification
- Automation feasibility
- Documentation standards
- Audit trail completeness
- Stakeholder confirmation
- Continuous monitoring design
Module 6. Strategic Alignment Workshops
Run effective sessions that align engineering, legal, and business teams around shared AI governance goals.
12 chapters in this module
- Workshop objective setting
- Stakeholder pre-reads
- Scenario-based discussion
- Risk prioritisation matrix
- Decision boundary mapping
- Accountability assignment
- Escalation criteria
- Outcome documentation
- Follow-up cadence
- Progress tracking
- Feedback integration
- Executive summary creation
Module 7. Incident Response Coordination
Lead coordinated responses when AI systems behave unexpectedly, using OECD principles as an anchor.
12 chapters in this module
- Incident classification
- Response team activation
- Root cause analysis
- Stakeholder communication
- Regulatory reporting
- Remediation planning
- Lessons learned
- Policy update triggers
- Systemic risk identification
- Preventive control design
- Public statement drafting
- Post-mortem facilitation
Module 8. Model Lifecycle Governance
Apply OECD principles across the full lifecycle of AI models, from ideation to decommissioning.
12 chapters in this module
- Idea validation
- Data sourcing rules
- Model development
- Testing protocols
- Deployment controls
- Monitoring thresholds
- Retraining triggers
- Decommissioning checklist
- Version tracking
- Dependency mapping
- Access control design
- Audit readiness
Module 9. Cross-Functional Policy Rollout
Drive adoption of AI governance standards across teams with different incentives and priorities.
12 chapters in this module
- Change management planning
- Champion network design
- Training material development
- Adoption metrics
- Feedback collection
- Iterative improvement
- Compliance monitoring
- Enforcement mechanisms
- Incentive alignment
- Leadership engagement
- Communication cadence
- Success story sharing
Module 10. Metrics That Matter
Define and track KPIs that reflect true adherence to OECD AI Principles, not just checkbox compliance.
12 chapters in this module
- Principle-linked metrics
- Adoption rate tracking
- Incident frequency
- Remediation speed
- Stakeholder satisfaction
- Audit finding trends
- Risk exposure reduction
- Policy exception rates
- Training completion
- Feedback loop quality
- Escalation volume
- Preventive action count
Module 11. Executive Communication Design
Translate technical governance work into strategic narratives that resonate with senior leadership.
12 chapters in this module
- Executive summary structure
- Risk framing
- Opportunity highlighting
- Resource request justification
- Progress reporting
- Crisis communication
- Board messaging
- Media inquiry handling
- Stakeholder segmentation
- Narrative consistency
- Visual storytelling
- Escalation framing
Module 12. Building a Living Governance System
Create a self-sustaining AI governance practice that evolves with organisational needs and external standards.
12 chapters in this module
- Feedback mechanism design
- Policy review cadence
- External trend monitoring
- Stakeholder input
- Change approval process
- Version control
- Knowledge base maintenance
- Training refresh
- Audit integration
- Benchmarking against peers
- Continuous improvement
- Organisational memory
How this maps to your situation
- When leading an AI system design review
- During vendor selection for ML tools
- Before internal audit cycles
- After model incident response
Before vs. after
Before
Governance input is reactive, fragmented, and relies on ad hoc influence.
After
You lead governance initiatives proactively, with structured frameworks and broad buy-in.
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 real-world application alongside current responsibilities.
How this compares to the alternatives
Unlike generic compliance courses, this program is built specifically around the OECD AI Principles and their practical application in data platform environments, making it uniquely relevant for practitioners shaping AI governance from within technical teams.
Frequently asked
Who is this course for?
Senior technical practitioners influencing AI governance, policy, or architecture decisions.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this if my organisation hasn’t adopted OECD AI Principles?
Yes, this course teaches how to introduce and operationalise them meaningfully, even in early-stage environments.
$199 one-time. Approximately 3 hours per module, designed for real-world application alongside current responsibilities..
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