A tailored course, built for your situation
Executive Visibility on AI Governance Work That Stays Below the Line
Turn unseen AI strategy work into recognized leadership contributions with OWASP-aligned governance patterns
$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.
Your AI governance work is critical, but if it doesn’t reach decision-makers, it won’t shape the direction of the platform.
The situation this course is for
Important technical and strategic work in AI governance often stays buried in execution layers, never reaching the stakeholders who could amplify it. Without structured ways to elevate this work, impact remains local and invisible.
Who this is for
Senior AI strategy leader driving governance and adoption within a major cloud platform
Who this is not for
Individuals looking for introductory AI training or hands-on coding labs in machine learning
What you walk away with
- Patterns to structure AI governance artefacts for executive consumption
- Proven methods to align AI risk frameworks with business growth objectives
- Templates to document OWASP AI controls in leadership-facing narratives
- Strategies to position internal AI policy work as strategic initiatives
- Confidence in elevating technical debt and control gaps as leadership opportunities
The 12 modules (with all 144 chapters)
Module 1. Mapping AI Governance to Growth Strategy
Align AI risk controls with market expansion goals using real examples from cloud platform rollouts.
12 chapters in this module
- Defining governance scope
- Linking AI controls to revenue lines
- Identifying growth blockers
- Stakeholder priority mapping
- Benchmarking against OWASP Tier 1
- Documenting control tradeoffs
- Risk appetite calibration
- Translating technical depth
- Framing constraints as options
- Building executive summaries
- Versioning control narratives
- Tracking decision readiness
Module 2. Positioning Technical Work for Visibility
Transform backend AI audits and framework mappings into recognized contributions.
12 chapters in this module
- Identifying invisible work
- Spotting escalation triggers
- Elevating control findings
- Narrative structuring
- Executive audience analysis
- Timing visibility moves
- Creating progress markers
- Linking to KPIs
- Using OWASP control tags
- Versioning deliverables
- Gaining peer validation
- Securing feedback loops
Module 3. OWASP AI Controls in Practice
Apply OWASP AI Security and Resilience controls to real governance scenarios.
12 chapters in this module
- Understanding OWASP tiers
- Threat modeling basics
- Model integrity checks
- Data lineage tracking
- Prompt injection defenses
- Access control mapping
- Bias detection workflows
- Logging requirements
- API exposure risks
- Supply chain verification
- Incident simulation design
- Control validation timing
Module 4. From Policy to Executive Narrative
Turn compliance frameworks into strategic talking points for leadership.
12 chapters in this module
- Opening with business impact
- Naming decision thresholds
- Using OWASP as benchmark
- Highlighting risk ownership
- Demonstrating readiness
- Avoiding technical overload
- Building repeatable briefs
- Integrating audit cycles
- Linking to customer trust
- Versioning policy updates
- Creating escalation paths
- Measuring narrative uptake
Module 5. Strategic Artefact Design
Build templates that make AI governance work inherently visible.
12 chapters in this module
- Choosing artefact types
- Defining ownership fields
- Including escalation clauses
- Adding maturity scales
- Embedding OWASP references
- Standardizing risk labels
- Creating executive footnotes
- Designing review cycles
- Enabling cross-team reuse
- Version control strategy
- Archiving inactive versions
- Linking to roadmap
Module 6. Influencing Without Authority
Shape AI governance direction using structured influence, not hierarchy.
12 chapters in this module
- Mapping decision networks
- Identifying quiet champions
- Timing proposal releases
- Using data proxies
- Creating visibility loops
- Leveraging peer reviews
- Framing tradeoffs neutrally
- Highlighting precedent use
- Avoiding ownership conflict
- Building coalition logic
- Documenting subtle wins
- Tracking influence velocity
Module 7. AI Risk Reporting That Resonates
Design reports that get read by leaders focused on growth and exposure.
12 chapters in this module
- Opening with context
- Using OWASP baselines
- Quantifying risk exposure
- Comparing control maturity
- Highlighting customer impact
- Avoiding fear framing
- Including mitigation velocity
- Showing trend lines
- Adding decision triggers
- Using color conservatively
- Versioning report formats
- Tracking executive engagement
Module 8. Control Mapping Across AI Layers
Connect OWASP controls to infrastructure, model, and application layers.
12 chapters in this module
- Mapping to data layer
- Linking to training pipeline
- Embedding in deployment
- Monitoring inference layer
- Connecting to API gateways
- Tagging model versions
- Logging control checks
- Validating input filters
- Tracking prompt audits
- Enabling rollback triggers
- Documenting control gaps
- Reporting coverage metrics
Module 9. Building Repeatable Governance Patterns
Create templates that compound visibility across engagements.
12 chapters in this module
- Identifying rework points
- Designing standard blocks
- Creating modular sections
- Adding adaptable footnotes
- Versioning control logic
- Linking to playbook
- Embedding OWASP tags
- Testing reuse velocity
- Gathering feedback
- Improving narrative flow
- Archiving deprecated versions
- Scaling across teams
Module 10. Gaining Recognition for Foundational Work
Ensure AI governance contributions are attributed and valued.
12 chapters in this module
- Documenting design choices
- Capturing rationale
- Including stakeholder input
- Highlighting tradeoff calls
- Using version timestamps
- Linking to decisions
- Creating contribution logs
- Sharing updates proactively
- Inviting feedback
- Measuring recognition signals
- Amplifying peer nods
- Securing leadership mentions
Module 11. Scaling Visibility Across AI Initiatives
Extend governance recognition patterns to new projects and teams.
12 chapters in this module
- Identifying high-visibility projects
- Applying proven templates
- Adapting OWASP mappings
- Training peer leads
- Creating visibility checklists
- Monitoring adoption
- Sharing success patterns
- Refining messaging
- Leveraging cross-org wins
- Building governance network
- Tracking expansion rate
- Updating central playbook
Module 12. Owning the AI Governance Narrative
Become the recognized voice shaping how AI risk and control are discussed.
12 chapters in this module
- Defining core messages
- Using consistent framing
- Publishing updates
- Speaking at forums
- Answering peer queries
- Documenting positions
- Linking to OWASP
- Tracking narrative spread
- Measuring influence reach
- Refining talking points
- Building reference library
- Establishing go-to status
How this maps to your situation
- When launching a new AI service
- Before executive strategy reviews
- After AI incident or audit
- During cross-team alignment efforts
Before vs. after
Before
AI governance work remains in technical silos, rarely influencing leadership decisions or growth direction.
After
Governance contributions are systematically elevated, shaping strategic AI decisions and earning executive recognition.
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, designed for completion over 6-8 weeks with real-world application between chapters.
If nothing changes
Continuing to operate below the line means missed opportunities for influence, even as AI governance becomes more central to platform trust and customer adoption.
How this compares to the alternatives
Unlike generic AI ethics courses or technical security bootcamps, this program focuses specifically on making governance work visible and valued in strategic decision-making contexts.
Frequently asked
Does this course cover hands-on coding or model development?
No, this course focuses on governance, risk alignment, and executive communication strategies for AI systems, not technical implementation or coding.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Is OWASP certification included?
No, this course teaches practical application of OWASP AI guidelines to elevate governance work, not exam preparation.
$199 one-time. Approximately 3-4 hours per module, designed for completion over 6-8 weeks with real-world application between chapters..
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