A tailored course, built for your situation
Influence across more business lines with OECD AI Principles
Build authority and consistent AI governance adoption across functions by leading with globally recognised standards
$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.
Siloed AI governance slows adoption and dilutes impact
The situation this course is for
AI initiatives often stall when teams disagree on fairness, interpretability, or risk thresholds. Without a shared reference, alignment happens too late or not at all, resulting in rework, compliance friction, and missed momentum.
Who this is for
Technical founder or IC driving AI product strategy with exposure to compliance, governance, or cross-functional scale challenges
Who this is not for
Those not involved in AI design, deployment, or governance decisions; anyone seeking certification prep only
What you walk away with
- Lead cross-functional AI discussions using a neutral, globally recognised reference framework
- Produce governance documentation that aligns product, data, and compliance stakeholders
- Anticipate regulatory expectations using OECD-aligned risk classification patterns
- Design AI systems with audit readiness built in, reducing downstream rework
- Scale governance practices across use cases without recreating foundations
The 12 modules (with all 144 chapters)
Module 1. Foundations of the OECD AI Principles
Map each of the five OECD principles to real-world AI system decisions and stakeholder concerns.
12 chapters in this module
- Principle 1: Inclusive growth
- Principle 2: Human-centred values
- Principle 3: Transparency and explainability
- Principle 4: Robustness and safety
- Principle 5: Accountability
- How governments adopted the principles
- Mapping to national AI strategies
- Linking to EU AI Act intent
- Connecting to ISO 42001 structure
- Benchmarking existing AI policies
- Identifying alignment gaps
- Setting baseline expectations
Module 2. Translating principles into policy language
Turn high-level commitments into actionable, team-specific guidelines.
12 chapters in this module
- From fairness to testable criteria
- Defining 'transparency' per audience
- Setting safety thresholds by use case
- Accountability mapping to roles
- Versioning governance documents
- Creating living policy pages
- Policy diff tracking over time
- Linking decisions to Jira tickets
- Embedding checklists in PRs
- Automating policy reminders
- Handling exceptions gracefully
- Documenting rationale consistently
Module 3. Stakeholder mapping across functions
Identify who needs what from AI governance and when.
12 chapters in this module
- Product team concerns
- Engineering team needs
- Compliance priorities
- Legal department red lines
- Risk management inputs
- Security team expectations
- Customer support insights
- Sales enablement requests
- Executive comms angles
- Investor due diligence items
- Audit trail requirements
- Escalation path design
Module 4. Designing for audit readiness
Structure documentation and decisions so they survive scrutiny.
12 chapters in this module
- Building decision provenance
- Capturing design trade-offs
- Versioning model cards
- Logging data lineage choices
- Documenting bias testing
- Tracking third-party components
- Creating inspectable artefacts
- Standardising review templates
- Setting retention rules
- Indexing for searchability
- Preparing for surprise reviews
- Responding to audit findings
Module 5. Scaling governance across use cases
Reuse patterns without stifling innovation.
12 chapters in this module
- Classifying AI risk levels
- Tiered review processes
- Fast-track pathways
- Exemption justification
- Pattern library creation
- Template adaptation workflow
- Cross-team pattern sharing
- Measuring reuse frequency
- Updating patterns quarterly
- Feedback loops from incidents
- Versioning governance patterns
- Retiring outdated templates
Module 6. Embedding governance in development workflows
Integrate checks where decisions happen.
12 chapters in this module
- Pre-commit hooks for AI
- PR checklist integration
- CI/CD gate design
- Model registration steps
- Automated risk scoring
- Human-in-the-loop triggers
- Documentation auto-generation
- Reviewer assignment rules
- Escalation criteria
- Post-deployment monitoring
- Incident response alignment
- Lessons learned capture
Module 7. Communicating governance value
Frame governance as speed infrastructure, not overhead.
12 chapters in this module
- Messaging to engineers
- Talking to product managers
- Explaining to execs
- Reporting progress visibly
- Celebrating shipped audits
- Sharing risk averted stories
- Highlighting time saved
- Positioning as enablement
- Avoiding compliance theatre
- Using real project data
- Benchmarking maturity
- Showing ROI clearly
Module 8. Navigating vendor AI tools
Apply principles even when using third-party systems.
12 chapters in this module
- Vendor assessment criteria
- Contractual safeguards
- Audit rights negotiation
- Transparency gap analysis
- Explainability workarounds
- Bias mitigation planning
- Data ownership terms
- Incident response SLAs
- Exit strategy planning
- Multi-vendor consistency
- Documentation requirements
- Reference architecture use
Module 9. Building internal training content
Spread understanding without centralising control.
12 chapters in this module
- Identifying knowledge gaps
- Creating role-specific guides
- Workshop design templates
- Onboarding integration
- Just-in-time learning spots
- Gamifying adoption
- Leaderboard design
- Feedback collection loops
- Updating materials quarterly
- Leveraging internal influencers
- Tracking completion rates
- Measuring behaviour change
Module 10. Anticipating regulatory evolution
Stay ahead of formal requirements using OECD as a proxy.
12 chapters in this module
- Tracking AI Act developments
- Mapping DORA implications
- Watching NIS2 updates
- Interpreting GDPR overlap
- Following US state laws
- Monitoring China AI rules
- Reading between the lines
- Inferring regulator intent
- Preparing for inspections
- Benchmarking against peers
- Adjusting risk thresholds
- Updating internal policies
Module 11. Creating defensible decision trails
Show your work in a way that earns trust.
12 chapters in this module
- Documenting alternatives considered
- Recording rationale explicitly
- Archiving context permanently
- Linking to meeting notes
- Naming decision owners
- Timestamping key choices
- Capturing dissenting views
- Referencing external sources
- Using standard templates
- Making trails searchable
- Balancing transparency and IP
- Handling confidential inputs
Module 12. Leading by example across the ecosystem
Become the reference others adopt.
12 chapters in this module
- Open-sourcing templates
- Publishing learnings
- Speaking at meetups
- Writing public case studies
- Mentoring others
- Contributing to standards
- Engaging regulators
- Hosting internal talks
- Building external credibility
- Earning industry recognition
- Setting de facto norms
- Influencing tool design
How this maps to your situation
- When launching a new AI product line
- Before an external audit cycle
- After a regulatory update
- During cross-functional team expansion
Before vs. after
Before
AI governance happens reactively, varies by team, and requires constant justification.
After
Governance is proactive, consistent, and assumed, freeing time to focus on innovation and scale.
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: 6-8 hours of focused reading and implementation over 3 weeks, designed to fit around product development cycles.
If nothing changes
Without a shared framework, AI initiatives risk rework, inconsistent compliance, and stalled adoption across teams, limiting both impact and influence.
How this compares to the alternatives
Unlike generic compliance trainings or country-specific regulatory deep dives, this course focuses on practical, repeatable patterns built around the OECD AI Principles, making it ideal for technical leaders shaping AI governance in fast-moving environments.
Frequently asked
Is this course about getting certified in OECD AI Principles?
No. This is a practice-focused course on applying the principles to real-world AI development, documentation, and cross-functional alignment, not exam preparation.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this work if my company uses other frameworks like ISO 42001 or NIST AI RMF?
Yes. The course shows how to align OECD principles with other major frameworks, making it easier to bridge internal and external expectations.
$199 one-time. 6-8 hours of focused reading and implementation over 3 weeks, designed to fit around product development 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