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Reference of choice on cross-functional AI governance calls

$199.00
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A tailored course, built for your situation

Reference of choice on cross-functional AI governance calls

Become the practitioner peers seek out when AI policy meets execution

$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 at a cloud-first data platform company, operating at the intersection of AI engineering and governance, with demonstrated platform mastery and a growing remit beyond pure execution

Who this is not for

Entry-level engineers, compliance staff without technical fluency, or executives seeking board-level summaries

What you walk away with

  • Lead cross-functional AI governance discussions with confidence backed by OECD AI Principles
  • Anchor debates in concrete implementation trade-offs, not just policy abstractions
  • Become the first call when teams face ethical AI dilemmas in deployment
  • Produce reusable position papers that elevate team decision-making
  • Strengthen visibility as a go-to voice on AI governance beyond your immediate domain

The 12 modules (with all 144 chapters)

Module 1. Mapping OECD AI Principles to data pipeline design
Translate high-level OECD guidance into controls at each stage of the data lifecycle, from ingestion to inference.
12 chapters in this module
  1. Data stewardship obligations
  2. System lifecycle transparency
  3. Human oversight integration
  4. Bias detection thresholds
  5. Documentation scope
  6. Version control alignment
  7. Stakeholder notification triggers
  8. Model rollback criteria
  9. Audit trail depth
  10. Access logging standards
  11. Risk classification bands
  12. Escalation playbooks
Module 2. Building governance into MLOps workflows
Embed compliance checks directly into CI/CD pipelines without slowing innovation.
12 chapters in this module
  1. Pre-commit validation hooks
  2. Model registry approvals
  3. drift detection alerts
  4. Performance decay thresholds
  5. Shadow deployment rules
  6. Approval chain automation
  7. Rollout safety gates
  8. Canary release audits
  9. Version compatibility checks
  10. Dependency scanning
  11. License compliance in models
  12. Model pedigree tracking
Module 3. Facilitating cross-team AI ethics reviews
Structure and lead sessions that balance innovation speed with accountability.
12 chapters in this module
  1. Review cadence design
  2. Stakeholder mapping
  3. Decision log templates
  4. Risk appetite calibration
  5. Use case screening
  6. Harm scenario modeling
  7. Mitigation feasibility
  8. Documentation standards
  9. Escalation paths
  10. Legal alignment
  11. External benchmarking
  12. Lessons learned loops
Module 4. Creating audit-ready policy implementation records
Turn governance intentions into artefacts that satisfy internal and external reviewers.
12 chapters in this module
  1. Control mapping matrices
  2. Evidence collection protocols
  3. Policy exception logs
  4. Remediation tracking
  5. Versioned policy documents
  6. Stakeholder sign-offs
  7. Compliance gap dashboards
  8. Third-party assessment prep
  9. Internal review cycles
  10. External auditor briefings
  11. Regulatory correspondence logs
  12. Policy drift detection
Module 5. Designing human oversight mechanisms
Implement practical review points that preserve autonomy while ensuring accountability.
12 chapters in this module
  1. Oversight threshold definition
  2. Alert triage workflows
  3. Escalation routing rules
  4. Human-in-the-loop triggers
  5. Review frequency bands
  6. Override justification
  7. Audit sampling methods
  8. False positive handling
  9. Feedback incorporation
  10. Process refinement
  11. Role clarity documentation
  12. Escalation fatigue mitigation
Module 6. Communicating AI risks to non-technical leaders
Frame technical trade-offs in business terms that drive informed decision-making.
12 chapters in this module
  1. Risk heat mapping
  2. Business impact scoring
  3. Scenario storytelling
  4. Mitigation cost framing
  5. Timeline trade-off visuals
  6. Reputational exposure bands
  7. Brand alignment checks
  8. Investor communication prep
  9. Crisis response alignment
  10. Media readiness inputs
  11. Stakeholder concern mapping
  12. Escalation narrative drafting
Module 7. Integrating fairness and non-discrimination checks
Operationalize bias detection across training, inference, and feedback loops.
12 chapters in this module
  1. Protected attribute handling
  2. Bias audit frequency
  3. Disparate impact thresholds
  4. Model fairness metrics
  5. Data slice analysis
  6. Third-party validation
  7. Remediation workflows
  8. Stakeholder notification
  9. Bias mitigation techniques
  10. Evaluation data refresh
  11. Community feedback loops
  12. Transparency reporting
Module 8. Establishing AI incident response protocols
Define clear actions when AI systems behave unexpectedly or cause harm.
12 chapters in this module
  1. Incident classification
  2. Detection trigger design
  3. Alert routing trees
  4. Initial response checklist
  5. Stakeholder notification
  6. Legal counsel engagement
  7. Public statement drafting
  8. Remediation tracking
  9. Post-mortem templates
  10. System rollback procedures
  11. Root cause analysis
  12. Prevention updates
Module 9. Managing third-party AI component risks
Assess and govern external models, APIs, and data sources integrated into workflows.
12 chapters in this module
  1. Vendor risk tiers
  2. Due diligence checklists
  3. Contractual safeguards
  4. Audit rights negotiation
  5. Performance SLAs
  6. Data handling clauses
  7. Exit strategy planning
  8. License compliance
  9. Subprocessor oversight
  10. Incident response alignment
  11. Renewal review triggers
  12. Replacement readiness
Module 10. Developing internal AI governance training
Equip teams across the organization with practical understanding of AI ethics and controls.
12 chapters in this module
  1. Role-specific modules
  2. Onboarding integration
  3. Refresher timing
  4. Assessment design
  5. Scenario library
  6. Feedback loops
  7. Adoption tracking
  8. Champion networks
  9. Leadership messaging
  10. Legal alignment
  11. Escalation path clarity
  12. Version update comms
Module 11. Creating reusable governance playbooks
Document processes so they compound across teams and projects.
12 chapters in this module
  1. Playbook scope definition
  2. Decision rationale capture
  3. Template creation
  4. Version control strategy
  5. Access permissions
  6. Feedback incorporation
  7. Cross-team alignment
  8. Update triggers
  9. Success metrics
  10. Lessons integration
  11. Archival rules
  12. Searchability design
Module 12. Scaling personal influence in AI governance
Position yourself as the go-to voice across the organization and beyond.
12 chapters in this module
  1. Internal speaking opportunities
  2. Cross-functional collaboration
  3. Mentorship roles
  4. External conference prep
  5. Publication drafting
  6. Stakeholder mapping
  7. Influence mapping
  8. Thought leadership topics
  9. Content distribution
  10. Feedback synthesis
  11. Reputation tracking
  12. Visibility benchmarks

How this maps to your situation

  • When a new AI project starts
  • During quarterly compliance reviews
  • After an AI incident
  • When onboarding third-party models

Before vs. after

Before
AI governance discussions happen around you, with fragmented inputs and unclear ownership
After
Peers proactively seek your input, and cross-functional calls default to your framing

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 45 minutes per module, designed for real-world application during regular workflow.

If nothing changes
Without sharpened governance positioning, even deep technical expertise remains siloed, missing the chance to shape ethical AI adoption enterprise-wide.

How this compares to the alternatives

Generic AI ethics courses focus on theory; this program delivers actionable frameworks tied directly to OECD AI Principles and real implementation challenges in data-rich environments.

Frequently asked

How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Which framework does the course center on?
The OECD AI Principles, applied to technical implementation and cross-functional governance.
Is prior certification required?
No, but the course is designed for practitioners with hands-on AI and data platform experience.
$199 one-time. Approximately 45 minutes per module, designed for real-world application during regular workflow..

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
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