A tailored course, built for your situation
Deeper command of AI governance frameworks for program leaders
Build unshakable command of AI governance standards, frameworks, and implementation patterns as they apply to complex data platform rollouts
$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
Program leaders in data and AI platform organizations who are expected to orchestrate governance alignment without being told exactly how
Who this is not for
Individual contributors focused only on policy drafting or auditors seeking compliance checklists
What you walk away with
- Final say on governance artefact structure without escalation
- Source-backed reasoning for framework choices during cross-functional reviews
- First internal team to ship a working AI governance SoA tied to platform release
- Confident navigation of NIST, ISO, and EU AI Act alignment points
- Repeatable playbook for embedding governance into platform delivery milestones
The 12 modules (with all 144 chapters)
Module 1. Core AI governance standards landscape
Map the functional differences between NIST AI RMF, ISO/IEC 42001, and EU AI Act governance requirements as they apply to data platform programs.
12 chapters in this module
- NIST AI RMF intent vs implementation
- ISO 42001 controls for AI systems
- EU AI Act high-risk classification logic
- Mapping overlap between three standards
- Governance scope per deployment type
- Key decision thresholds in each framework
- Identifying applicable clauses quickly
- When to apply which standard
- Handling conflicting requirements
- Leveraging sector-specific guidance
- Core terminology alignment
- Framework maturity comparison
Module 2. Governance by design in platform delivery
Embed governance checkpoints into data platform rollout timelines without slowing velocity.
12 chapters in this module
- Pre-kickoff governance alignment
- Architecture review triggers
- Model inventory design
- Data provenance integration
- Bias assessment integration points
- Security-governance handoffs
- Release gate criteria
- Staging environment checks
- Production audit trail setup
- Post-deployment monitoring rules
- Versioning governance artefacts
- Rollback decision matrix
Module 3. Artefact command and documentation standards
Produce authoritative, stakeholder-ready governance documentation that withstands executive and regulatory scrutiny.
12 chapters in this module
- SoA structure for AI systems
- Model card components
- System description templates
- Risk assessment narrative flow
- Control mapping clarity
- Auditor-friendly formatting
- Executive summary writing
- Version control for docs
- Stakeholder annotation workflows
- Cross-reference indexing
- Change justification logs
- Approval chain design
Module 4. Cross-functional governance alignment
Lead alignment across legal, risk, engineering, and product teams using shared governance language and decision frameworks.
12 chapters in this module
- Identifying governance decision owners
- Legal-risk threshold definitions
- Engineering feasibility filters
- Product timeline constraints
- Facilitating joint risk reviews
- Conflict resolution protocols
- Escalation pathways
- Consensus-building techniques
- Meeting structure for alignment
- Documenting agreed trade-offs
- Tracking alignment over time
- Feedback integration loops
Module 5. Model risk management integration
Apply financial-grade model risk principles to enterprise AI systems in non-regulated environments.
12 chapters in this module
- MRM lifecycle stages
- Model inventory requirements
- Pre-deployment validation steps
- Ongoing monitoring thresholds
- Performance decay detection
- Adversarial testing design
- Model lineage tracking
- Version comparison protocols
- Decommissioning criteria
- Third-party model oversight
- Risk rating calibration
- MRM-reporting cadence
Module 6. AI impact assessments in practice
Conduct assessments that drive real design decisions, not just compliance checkboxes.
12 chapters in this module
- Scoping the assessment
- Stakeholder identification
- Harm typology mapping
- Use case risk scoring
- Mitigation strategy formulation
- Documentation standards
- Review cycle timing
- Integration with design sprints
- Feedback from impacted teams
- Public disclosure preparation
- Regulator-facing versions
- Internal summary variants
Module 7. Vendor and third-party governance
Extend governance control to external AI components and platform dependencies.
12 chapters in this module
- Third-party risk classification
- Contractual control points
- API governance standards
- Data sharing agreements
- Audit rights negotiation
- Vendor compliance verification
- Subprocessor oversight
- Model update notification rules
- Penalty clauses enforcement
- Exit strategy documentation
- Dependency mapping
- Fallback mechanism design
Module 8. Automating governance workflows
Design repeatable, tool-integrated governance processes that scale with platform velocity.
12 chapters in this module
- Identifying automation candidates
- CI/CD governance gates
- Policy-as-code principles
- Metadata tagging standards
- Automated risk scoring
- Alerting threshold design
- Dashboard KPIs
- Integration with Jira and Slack
- Role-based access rules
- Audit log automation
- Scheduled review triggers
- Self-service governance portals
Module 9. Incident response and escalation
Respond to AI incidents with structured protocols that preserve trust and regulatory standing.
12 chapters in this module
- Incident definition criteria
- Triage workflow design
- Cross-team notification rules
- Containment procedures
- Root cause analysis method
- Remediation tracking
- Regulator communication rules
- Public statement protocols
- Internal post-mortem structure
- Pre-approved messaging templates
- Escalation to legal
- Closure criteria
Module 10. Metrics that demonstrate governance value
Track and report on governance outcomes that matter to leadership and auditors.
12 chapters in this module
- Time-to-compliance measurement
- Risk reduction quantification
- Audit finding trends
- Stakeholder satisfaction surveys
- Incident frequency tracking
- Control effectiveness scores
- Policy adoption rates
- Training completion metrics
- Escalation volume analysis
- Cost of non-compliance estimates
- Benchmarking against peers
- Executive dashboard design
Module 11. Global alignment and localization
Adapt core governance frameworks for regional variations without fragmenting the program.
12 chapters in this module
- Identifying jurisdictional differences
- EU vs US vs APAC priorities
- Local regulator expectations
- Language and translation needs
- Cultural risk perceptions
- Data sovereignty rules
- Cross-border data flow controls
- Localization review process
- Central-local coordination
- Version divergence tracking
- Legal counsel engagement
- Compliance exception logging
Module 12. Sustaining governance maturity
Evolve the governance program from ad hoc responses to a mature, adaptive function.
12 chapters in this module
- Maturity model assessment
- Annual governance planning
- Resource allocation strategy
- Team capability development
- External benchmarking
- Lessons learned integration
- Stakeholder feedback loops
- Innovation testing framework
- Governance roadmap creation
- Budget justification templates
- Succession planning
- Program review cadence
How this maps to your situation
- When launching a new AI-enabled feature
- During platform-wide compliance audit
- After an AI incident or near-miss
- Before engaging external auditors
Before vs. after
Before
Governance decisions feel reactive, dependent on external input, and subject to rework during reviews.
After
You command the frameworks, set the artefact standards, and lead alignment with confidence, governance becomes a program strength, not a handoff.
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 active program work.
How this compares to the alternatives
Unlike generic compliance courses, this program focuses on the specific governance decisions, artefacts, and trade-offs faced by program leaders in data and AI platform organizations.
Frequently asked
Who is this course designed for?
Program leaders in data, AI, and platform organizations who need to command governance frameworks and drive alignment across technical and non-technical stakeholders.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Will this help me respond to auditors or regulators?
Yes, each module includes templates and reasoning patterns used in regulator-facing documentation and audit responses.
$199 one-time. Approximately 3 hours per module, designed to be completed alongside active program work..
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