A tailored course, built for your situation
More Defensible AI Governance Artefacts from First Draft
Turn policy intent into audit-ready governance packages that hold up under scrutiny
$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.
The situation this course is for
Who this is for
Senior AI governance lead at a global services firm responsible for translating ethics principles and regulatory signals into operational policy and control frameworks
Who this is not for
This is not for entry-level compliance analysts or those focused solely on data privacy or cybersecurity without AI governance scope
What you walk away with
- Build governance documentation with embedded citations to NIST, OECD, and ISO frameworks
- Map controls to specific model lifecycle stages with clear ownership and testability
- Produce AI risk classifications that reflect real-world harm scenarios and regulatory expectations
- Justify threshold decisions (e.g., high-risk designation) with documented precedent and internal alignment
- Create living artefacts that evolve with regulatory updates without full rewrites
The 12 modules (with all 144 chapters)
Module 1. From Principles to Actionable Criteria
Transform high-level AI ethics statements into operational definitions for risk classification, review thresholds, and escalation paths using real governance board decisions as models.
12 chapters in this module
- Defining 'fairness' in lending models
- Setting harm thresholds for customer impact
- Mapping intent to measurable outcomes
- Aligning with EU AI Act high-risk tags
- Using NIST AI RMF to scope controls
- Benchmarking against internal audit standards
- Documenting rationale for exemptions
- Weighting stakeholder risk tolerance
- Classifying model autonomy levels
- Setting review frequency triggers
- Assigning validation ownership
- Creating versioned decision logs
Module 2. Control Selection with Justification
Choose controls that match both technical feasibility and governance expectations, with documented reasoning that survives senior challenge.
12 chapters in this module
- Matching controls to risk level
- Using ISO/IEC 23894 for due diligence
- Selecting monitoring frequency
- Defining human-in-the-loop requirements
- Referencing NIST SP 1270 examples
- Justifying control exceptions
- Aligning with model card standards
- Documenting testing assumptions
- Linking to data lineage practices
- Specifying rollback conditions
- Choosing bias detection methods
- Creating control crosswalks
Module 3. Evidence-Backed Risk Assessments
Build AI risk assessments that cite real incidents, regulatory actions, and sector-specific harm patterns to make classifications credible and consistent.
12 chapters in this module
- Sourcing real-world AI failures
- Mapping harms to business lines
- Using FTC enforcement letters
- Classifying severity levels
- Benchmarking against peer disclosures
- Documenting mitigation effectiveness
- Creating harm scenario libraries
- Referencing EU AI Watch examples
- Weighting likelihood factors
- Including third-party audit input
- Updating assessments quarterly
- Flagging emerging risk indicators
Module 4. Audit-Ready Documentation Packages
Assemble governance outputs that include version control, sourcing, approval trails, and test evidence so they pass internal and external review without revision.
12 chapters in this module
- Structuring the governance binder
- Including framework crosswalks
- Versioning control documents
- Embedding approval signatures
- Attaching testing results
- Referencing training data policies
- Linking to model inventory
- Adding change logs
- Creating executive summaries
- Indexing for regulator access
- Using metadata tags
- Generating PDF audit packages
Module 5. Stakeholder Alignment Scripts
Use proven language and framing to align legal, risk, engineering, and product teams during governance reviews and challenge points.
12 chapters in this module
- Explaining risk classifications
- Negotiating control trade-offs
- Handling scope disagreement
- Responding to 'this slows us down'
- Aligning on review thresholds
- Defending high-risk tags
- Integrating with sprint planning
- Escalating unresolved conflicts
- Presenting to governance boards
- Summarizing for executives
- Answering auditor questions
- Updating team playbooks
Module 6. Regulatory Signal Integration
Track and incorporate new guidance from jurisdictions and standards bodies into existing governance without overhauling templates.
12 chapters in this module
- Monitoring EU AI Office updates
- Tracking NIST AI RMF changes
- Ingesting FTC AI guidance
- Mapping UK ICO signals
- Updating control libraries
- Flagging jurisdiction conflicts
- Adjusting risk thresholds
- Notifying stakeholders of shifts
- Versioning policy updates
- Archiving old baselines
- Creating change impact logs
- Using regulatory heatmaps
Module 7. Model Lifecycle Gate Reviews
Design stage-gate governance checkpoints that enforce consistency and capture evidence before deployment.
12 chapters in this module
- Setting pre-training review gates
- Requiring data provenance docs
- Validating fairness testing plans
- Checking model card completeness
- Approving pilot parameters
- Reviewing real-world testing
- Signing off on deployment
- Scheduling post-launch audits
- Tracking performance drift
- Requiring quarterly reassessments
- Updating risk classifications
- Closing out project reviews
Module 8. Third-Party AI Oversight
Extend governance rigor to vendor models and APIs with consistent evaluation, documentation, and monitoring practices.
12 chapters in this module
- Assessing vendor model risk
- Requiring transparency reports
- Reviewing third-party audits
- Mapping external models to inventory
- Setting integration controls
- Monitoring API behavior
- Detecting model drift externally
- Enforcing right-to-explain clauses
- Documenting fallback plans
- Reviewing contract terms
- Benchmarking against in-house models
- Creating vendor scorecards
Module 9. Incident Response Preparedness
Build response protocols for AI incidents that include investigation steps, stakeholder comms, and remediation tracking.
12 chapters in this module
- Defining AI incident criteria
- Triggering response workflows
- Assigning investigation roles
- Preserving model logs
- Analyzing root causes
- Notifying regulators if needed
- Communicating to customers
- Updating controls post-incident
- Logging resolution steps
- Sharing lessons internally
- Testing response plans
- Integrating with security teams
Module 10. Living Policy Frameworks
Maintain governance policies that evolve with technology and regulation through structured review cycles and change tracking.
12 chapters in this module
- Scheduling policy refreshes
- Assigning ownership
- Incorporating feedback
- Tracking regulatory changes
- Updating risk models
- Versioning policy documents
- Archiving retired versions
- Communicating updates
- Training teams on changes
- Auditing policy adherence
- Measuring policy effectiveness
- Reporting to leadership
Module 11. Cross-Functional Governance Alignment
Coordinate across risk, legal, compliance, data, and engineering to ensure consistent application of governance standards.
12 chapters in this module
- Mapping governance dependencies
- Aligning on definitions
- Sharing documentation access
- Creating joint review calendars
- Resolving conflicting requirements
- Integrating with data governance
- Linking to security controls
- Coordinating audit schedules
- Standardizing reporting formats
- Building shared playbooks
- Conducting alignment workshops
- Measuring cross-team adherence
Module 12. Executive Communication for Governance Leads
Frame governance outcomes in business terms that resonate with senior leaders and reinforce the value of proactive oversight.
12 chapters in this module
- Translating risk to financial impact
- Highlighting brand protection
- Showing compliance efficiency
- Demonstrating innovation enablement
- Reporting on audit outcomes
- Measuring control effectiveness
- Tracking issue resolution
- Benchmarking against peers
- Presenting maturity progress
- Linking to ESG goals
- Summarizing regulatory exposure
- Recommending strategic investments
How this maps to your situation
- When launching a new AI initiative
- Before internal audit cycles
- After regulatory guidance changes
- During M&A due diligence involving AI assets
Before vs. after
Before
Governance outputs require multiple rounds of review, lack consistent sourcing, and are challenged on specificity.
After
First-draft artefacts are precise, cited, and structured to pass scrutiny, reducing revision cycles and increasing stakeholder trust.
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 total, self-paced over 3-4 weeks with implementation steps built into each module.
How this compares to the alternatives
Unlike generic AI ethics courses, this program delivers actionable documentation patterns used in real governance reviews at global services firms, focused on output quality, not conceptual familiarity.
Frequently asked
Is this course technical or policy-focused?
It’s designed for policy and governance leads who need to produce technically credible, regulator-ready documentation without being an engineer.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I use this for multiple engagements?
Yes, the templates and playbook are built to compound across projects and reduce setup time for future governance work.
$199 one-time. 6-8 hours total, self-paced over 3-4 weeks with implementation steps built into each module..
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