A tailored course, built for your situation
Deeper Command of AI Governance Frameworks
Build unshakable fluency in the structures shaping enterprise AI adoption
$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 consulting practitioner leading AI governance or risk advisory engagements in a global services firm
Who this is not for
Entry-level analysts, technical AI developers without client advisory responsibilities, or professionals outside the governance, risk, and compliance space
What you walk away with
- Confidently map client AI use cases to NIST AI RMF control categories
- Anticipate auditor expectations when designing governance playbooks
- Differentiate client proposals with framework-backed governance architecture
- Lead internal capability development with reusable governance templates
- Respond with precision when clients question model risk accountability
The 12 modules (with all 144 chapters)
Module 1. Core principles of AI governance
Establish the foundational goals of fairness, transparency, accountability, and risk proportionality across use cases.
12 chapters in this module
- Intent behind governance
- Trustworthiness dimensions
- Risk-based scoping
- Stakeholder mapping
- Ethical thresholds
- Regulatory anticipation
- Control depth by impact
- Human oversight models
- Lifecycle coverage
- Global alignment trends
- Sector-specific norms
- Governance maturity stages
Module 2. NIST AI Risk Management Framework
Break down the NIST AI RMF into actionable components for client advisory and implementation planning.
12 chapters in this module
- Mapping the framework
- Govern function
- Map function
- Measure function
- Manage function
- Cross-functional alignment
- Trustworthiness profiling
- Risk tiering methodology
- Control selection logic
- Implementation playbooks
- Validation techniques
- Iterative refinement
Module 3. ISO/IEC 42001 and audit alignment
Translate ISO/IEC 42001 requirements into governance artefacts that pass independent review.
12 chapters in this module
- Clause-by-clause breakdown
- Certification prerequisites
- Documentation standards
- Internal audit trails
- Policy linkage
- Role-based controls
- Evidence collection
- Gap remediation
- External auditor mindset
- Conformity statements
- Readiness assessment
- Certification roadmap
Module 4. OECD AI Principles in practice
Apply the OECD’s five principles to client governance models with real-world precedent and justification.
12 chapters in this module
- Inclusive growth focus
- Human-centered values
- Transparency expectations
- Robustness and safety
- Accountability mechanisms
- Public-private alignment
- Implementation guidance
- Case law references
- Benchmark comparisons
- Stakeholder trust metrics
- Responsible innovation
- Global interoperability
Module 5. Enterprise control frameworks
Integrate AI governance into existing internal control environments like COBIT, COSO, and SOC 2.
12 chapters in this module
- Control environment fit
- COSO integration points
- COBIT domains
- SOC 2 trust criteria
- Policy hierarchy
- Control ownership
- Monitoring cadence
- Exception handling
- Third-party assurance
- Automated controls
- Evidence retention
- Review cycle planning
Module 6. Client engagement structuring
Design advisory engagements that begin with governance architecture, not reactive remediation.
12 chapters in this module
- Scoping discovery questions
- Use case risk tiering
- Stakeholder alignment workshops
- Governance maturity assessment
- Framework selection matrix
- Control gap analysis
- Roadmap co-creation
- Client team enablement
- Change management planning
- Success metric definition
- Steering committee design
- Post-engagement review
Module 7. Policy development and articulation
Write clear, enforceable policies that reflect framework requirements and withstand scrutiny.
12 chapters in this module
- Policy hierarchy
- Audience-specific drafting
- Risk-based thresholds
- Enforcement mechanisms
- Version control
- Approval workflows
- Distribution tracking
- Acknowledgment records
- Translation needs
- Exception handling
- Review cycles
- Policy testing
Module 8. Audit and assurance preparation
Anticipate auditor questions and prepare evidence collections in advance of reviews.
12 chapters in this module
- Audit scope anticipation
- Evidence checklist
- Control testing plans
- Sampling methodology
- Deficiency classification
- Remediation tracking
- Management responses
- Internal review cycles
- External auditor coordination
- Findings resolution
- Follow-up verification
- Audit communication strategy
Module 9. Model risk governance
Apply financial and operational risk principles to AI model validation and oversight.
12 chapters in this module
- Model inventory design
- Risk classification
- Validation protocols
- Performance thresholds
- Drift detection
- Model documentation
- Version control
- Model retirement
- Independent review
- Challenge function
- Escalation pathways
- Governance committee reporting
Module 10. Cross-border compliance
Navigate differing AI governance expectations across regions and sectors.
12 chapters in this module
- EU AI Act implications
- US sectoral approach
- Singapore framework
- UK white paper
- Japan’s guidelines
- India’s draft rules
- Data sovereignty
- Transfer mechanisms
- Local enforcement
- Global policy harmonization
- Jurisdictional overlap
- Multi-region playbooks
Module 11. Implementation playbooks
Build reusable, modular templates for governance rollout across client engagements.
12 chapters in this module
- Playbook structure
- Client intake form
- Risk assessment template
- Control mapping matrix
- Policy draft library
- Audit prep checklist
- Stakeholder comms
- Training materials
- Review meeting agendas
- Status reporting
- Lessons learned log
- Versioned release
Module 12. Leading governance capability
Position yourself as the internal expert who shapes the firm’s approach to AI governance delivery.
12 chapters in this module
- Internal training design
- Capability roadmap
- Center of excellence
- Knowledge sharing
- Mentorship model
- Client reference stories
- Win theme integration
- Proposal differentiation
- Cross-practice alignment
- Thought leadership
- Feedback loops
- Continuous improvement
How this maps to your situation
- When scoping a new AI governance engagement
- When preparing for an internal or client audit
- When designing governance policies from scratch
- When advising on model risk management structure
Before vs. after
Before
Relying on general principles and reactive client input when designing AI governance structures
After
Leading with structured, framework-grounded governance models that anticipate audit needs and client challenges
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 3-4 hours per module, recommended over 6-8 weeks with real-world application between modules.
How this compares to the alternatives
Unlike vendor-specific certifications or academic courses, this program focuses on applied governance frameworks used in consulting engagements, with templates and examples tailored to advisory delivery in global firms.
Frequently asked
Is this course technical or compliance-focused?
It’s designed for advisory practitioners, balancing technical governance requirements with compliance, risk, and client delivery needs.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this to non-AI governance work?
The framework thinking and control structuring apply broadly to digital risk and compliance engagements.
$199 one-time. Approximately 3-4 hours per module, recommended over 6-8 weeks with real-world application between modules..
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