A tailored course, built for your situation
Faster path from AI governance intent to working implementation using OECD AI Principles
A 12-module course to turn policy goals into operational artefacts in record time
$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.
Governance work that stays stuck in review cycles instead of moving to deployment
The situation this course is for
AI governance teams often spend weeks aligning stakeholders, only to face rework when implementation reveals gaps. The delay isn't from lack of effort, it's from missing a shared, actionable framework that bridges policy and engineering. This creates bottlenecks, especially in regulated domains like healthcare AI, where velocity and compliance must coexist.
Who this is for
Senior AI governance practitioner in a technical organisation, responsible for turning ethical AI principles into enforceable processes and working systems
Who this is not for
Entry-level compliance staff, non-technical ethics board members, or consultants without hands-on AI deployment experience
What you walk away with
- Repeatable artefacts that compound across AI governance engagements
- Stakeholder alignment achieved in half the review time
- Complete documentation package ready for auditor handoff
- First internal team to ship a working OECD AI Principles conformance report
- Faster path from policy intent to functioning model deployment
The 12 modules (with all 144 chapters)
Module 1. Mapping OECD AI Principles to technical controls
Translate high-level principles like transparency and accountability into specific data lineage, model logging, and traceability requirements. Start with healthcare AI use cases.
12 chapters in this module
- Principle 1: Inclusive growth and well-being
- Principle 2: Human-centred values
- Principle 3: Transparency in AI systems
- Principle 4: Robustness and security
- Principle 5: Accountability mechanisms
- Turning principles into control statements
- Mapping to model registry fields
- Aligning with internal audit criteria
- Healthcare-specific compliance triggers
- Crosswalk to internal data policies
- Stakeholder alignment checklist
- First draft of conformance table
Module 2. Stakeholder alignment playbook for AI governance rollout
Identify key decision points and pre-empt friction between data science, compliance, and product teams using proven sequencing.
12 chapters in this module
- Identifying decision owners
- Timing policy rollout before model sprints
- Preempting legal team concerns
- Engineering sign-off triggers
- Product manager engagement sequence
- Documentation expectations by role
- Feedback loop design
- Escalation path mapping
- Healthcare regulatory liaison
- Internal audit integration
- Version control for policy drafts
- Approval workflow finalisation
Module 3. Model intake process with built-in governance
Design a standard intake form that captures OECD-aligned requirements at first submission, reducing rework.
12 chapters in this module
- Required fields for model registration
- Risk categorisation by use case
- Healthcare data sensitivity flags
- Automated control suggestions
- Data provenance requirements
- Model owner attestation
- Third-party model handling
- Version history capture
- Explainability threshold settings
- Bias assessment trigger points
- Documentation checklist auto-fill
- Integration with model registry
Module 4. Building the AI documentation package
Assemble a living document set that satisfies both internal review and external auditor needs.
12 chapters in this module
- Executive summary template
- Model purpose and scope section
- Data sources and lineage map
- Training data inclusion criteria
- Preprocessing logic documentation
- Model architecture diagram guide
- Explainability method description
- Performance monitoring plan
- Bias and fairness assessment log
- Human oversight protocol
- Incident response playbook
- Version update log structure
Module 5. From policy draft to implementation checklist
Break down high-level governance goals into executable steps for engineering teams.
12 chapters in this module
- Policy statement decomposition
- Control mapping to system features
- Ownership assignment matrix
- Timeline for implementation phases
- Testing validation criteria
- Integration with CI/CD pipeline
- Logging and monitoring hooks
- Audit trail configuration
- Access control alignment
- Data retention rules
- Model rollback procedure
- Final sign-off checklist
Module 6. Designing automated compliance checks
Embed OECD-aligned validation into the model development lifecycle.
12 chapters in this module
- Static analysis rules
- Model card completeness check
- Data license verification
- Bias detection on training set
- Explainability threshold alert
- Logging requirement validator
- Access control audit script
- Version diff tracker
- Stakeholder notification triggers
- Automated report generation
- Dashboard for compliance status
- Integration with alerting system
Module 7. Healthcare-specific governance adaptations
Apply OECD principles to HIPAA, 21st Century Cures, and other healthcare compliance drivers.
12 chapters in this module
- Patient data handling rules
- De-identification standards
- Clinician-in-the-loop design
- Emergency override protocols
- Audit trail for clinical decisions
- Model validation for medical impact
- FDA pre-market alignment
- Real-world performance tracking
- Provider feedback loop
- Incident reporting to medical boards
- Ethics review board coordination
- Specialty-specific risk thresholds
Module 8. Running the first conformance review
Simulate a full internal review using the OECD framework as the benchmark.
12 chapters in this module
- Assembling the review panel
- Scheduling cross-functional session
- Pre-read package structure
- Presenting conformance evidence
- Handling technical objections
- Documenting gaps and action items
- Prioritisation of fixes
- Versioning the conformance report
- Internal audit submission
- Regulatory liaison options
- Public disclosure considerations
- Lessons learned capture
Module 9. Scaling governance across teams
Extend the framework to multiple AI initiatives without slowing down delivery.
12 chapters in this module
- Central governance team role
- Self-service onboarding
- Standardised templates
- Training for new teams
- Model registry governance layer
- Cross-team review rotation
- Shared documentation hub
- Automated compliance scoring
- Benchmarking team performance
- Governance debt tracking
- Quarterly maturity assessment
- Recognition for compliance excellence
Module 10. Maintaining conformance over time
Keep systems compliant as models evolve and regulations shift.
12 chapters in this module
- Change approval process
- Model re-certification cycle
- Version diff analysis
- Stakeholder re-approval triggers
- Regulatory update monitoring
- Impact assessment workflow
- Patch deployment protocol
- Incident-driven review
- Annual conformance audit
- Documentation refresh schedule
- Staff turnover mitigation
- Lessons from prior updates
Module 11. Communicating governance outcomes
Tell the story of AI governance success to leadership and external partners.
12 chapters in this module
- Executive dashboard design
- Metrics that matter
- Narrative for legal teams
- Transparency report drafting
- Public trust messaging
- Regulator-facing summaries
- Board-level summary version
- Media inquiry protocol
- Partnership disclosure standards
- Case study development
- Lessons from peer organisations
- Public benefit storytelling
Module 12. Building the implementation playbook
Assemble a custom, reusable guide that captures your team’s governance journey.
12 chapters in this module
- Cover and version page
- Team roles and responsibilities
- Timeline for rollout
- Stakeholder map
- Policy-to-control crosswalk
- Tooling integration guide
- Training materials index
- Review meeting agenda
- Compliance checklist
- Incident response flow
- Improvement backlog
- Lessons learned section
How this maps to your situation
- When starting a new AI governance initiative
- Before model deployment in production
- During internal audit preparation
- After regulatory guidance update
Before vs. after
Before
Governance initiatives stall between policy and implementation, with inconsistent stakeholder alignment and rework.
After
Teams ship compliant AI systems faster, using a repeatable method grounded in OECD AI Principles.
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 2 hours per module, designed to fit around active projects.
If nothing changes
Without a structured path from intent to artefact, AI governance remains a bottleneck, slowing innovation, increasing rework, and exposing teams to compliance drift in fast-moving healthcare environments.
How this compares to the alternatives
Unlike generic AI ethics courses, this program delivers specific, actionable artefacts tied to the OECD AI Principles, proven to shorten the path from policy to deployment by up to 40% in healthcare AI contexts.
Frequently asked
Why focus on OECD AI Principles?
They’re the most widely adopted global benchmark for trustworthy AI, giving your governance work broad recognition and interoperability.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is this relevant for healthcare AI?
Yes, module 7 covers healthcare-specific adaptations, and examples are drawn from life sciences use cases.
$199 one-time. Approximately 2 hours per module, designed to fit around active projects..
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