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Influence in Technical Direction Decisions Using OECD AI Principles

$199.00
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A tailored course, built for your situation

Influence in Technical Direction Decisions Using OECD AI Principles

Shape AI governance outcomes with framework-grade reasoning and peer credibility

$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 influencing AI governance across platforms and teams

Who this is not for

Junior implementers, compliance generalists, or auditors without technical decision-making scope

What you walk away with

  • Lead AI governance discussions with authority grounded in OECD AI Principles
  • Anticipate and shape vendor selection criteria before RFPs go out
  • Contribute to peer-reviewed technical design decisions with reusable rationale
  • Influence cross-functional AI initiatives without formal leadership authority
  • Surface strategic risks and opportunities during architecture reviews

The 12 modules (with all 144 chapters)

Module 1. OECD AI Principles in Practice
Ground your influence in the five pillars of the OECD AI Principles: inclusive growth, human-centered values, transparency, robustness, and accountability. Learn how to map abstract values to live design trade-offs in AI pipelines.
12 chapters in this module
  1. Origin of OECD AI Principles
  2. Human agency and oversight
  3. Fairness and non-discrimination
  4. Explainability in model design
  5. System robustness standards
  6. Accountability infrastructure
  7. National adoption patterns
  8. Mapping to technical controls
  9. Use in multijurisdictional projects
  10. Industry-specific interpretations
  11. Public sector benchmarks
  12. Private sector implementation gaps
Module 2. Speaking to Technical Peers
Master the language and examples that resonate in engineering forums. Build credibility fast by citing real implementations and known failure modes tied directly to governance frameworks.
12 chapters in this module
  1. Credibility signals engineers trust
  2. Citing failed AI deployments
  3. Framing governance as guardrails
  4. Using precedent over policy
  5. Timing your input correctly
  6. Avoiding compliance framing
  7. Examples from cloud migrations
  8. Naming technical debt types
  9. Linking ethics to performance
  10. Balancing innovation and risk
  11. Speaking in system terms
  12. Preempting scalability issues
Module 3. Influencing Architecture Reviews
Position yourself as the go-to voice in technical architecture sessions. Learn how to embed governance requirements early so they don’t become rework later.
12 chapters in this module
  1. When to enter design discussions
  2. Required vs optional controls
  3. Pre-review outreach tactics
  4. Annotating system diagrams
  5. Naming architectural smells
  6. Framing trade-offs objectively
  7. Suggesting pilot constraints
  8. Using sandbox outcomes
  9. Influence without ownership
  10. Timing for escalation paths
  11. Capturing dissenting views
  12. Documenting precedent cases
Module 4. Vendor Evaluation Leadership
Guide procurement discussions by shaping evaluation criteria early. Use OECD AI Principles to define what ‘responsible AI’ means in your stack.
12 chapters in this module
  1. Mapping principles to vendor RFPs
  2. Pre-RFP scoping influence
  3. Scoring explainability claims
  4. Assessing bias testing rigor
  5. Evaluating model documentation
  6. Reviewing audit trail design
  7. Checking red team access
  8. Measuring drift detection quality
  9. Benchmarking against peers
  10. Weighting criteria by risk
  11. Flagging greenwashing tactics
  12. Creating reusable checklists
Module 5. Cross-Functional Initiative Alignment
Ensure AI governance keeps pace with fast-moving initiatives across product, data, and infrastructure by contributing early and consistently.
12 chapters in this module
  1. Identifying high-leverage meetings
  2. Mapping stakeholder incentives
  3. Anticipating escalation points
  4. Offering pre-built templates
  5. Aligning on shared definitions
  6. Avoiding jurisdictional conflict
  7. Building coalition momentum
  8. Timing for fast feedback
  9. Reframing compliance as enablement
  10. Using neutral facilitation tone
  11. Escalating with evidence
  12. Maintaining influence remotely
Module 6. Building Peer-Reviewed Artifacts
Develop governance artifacts that earn peer sign-off. Move beyond documentation to create living resources others reference and reuse.
12 chapters in this module
  1. Designing for peer review
  2. Choosing review formats
  3. Setting acceptance criteria
  4. Versioning governance docs
  5. Linking to code repositories
  6. Using changelogs effectively
  7. Incorporating feedback loops
  8. Highlighting key decisions
  9. Reducing cognitive load
  10. Standardizing terminology
  11. Creating decision registries
  12. Publishing with context
Module 7. Strategic Risk Framing
Reframe governance discussions around strategic risk and opportunity, not just compliance. Position yourself as a forward-looking contributor.
12 chapters in this module
  1. Identifying leverage points
  2. From checklist to strategy
  3. Naming silent risks
  4. Highlighting first-mover advantages
  5. Connecting ethics to brand
  6. Linking AI governance to trust
  7. Using competitor examples
  8. Framing long-term scenarios
  9. Balancing speed and safety
  10. Documenting assumptions
  11. Creating risk heatmaps
  12. Prioritizing by impact
Module 8. Decision Influence Without Authority
Lead from the middle by shaping outcomes even when you don’t control the budget or roadmap. Influence through preparation, timing, and trusted inputs.
12 chapters in this module
  1. Identifying decision inflection points
  2. Pre-positioning key arguments
  3. Building credibility over time
  4. Using data as leverage
  5. Naming unspoken assumptions
  6. Offering alternatives quietly
  7. Testing waters informally
  8. Creating consensus paths
  9. Timing for maximum impact
  10. Navigating chain of command
  11. Building informal coalitions
  12. Measuring influence over time
Module 9. Embedding Governance in Development
Ensure AI governance is not bolted on but built in. Learn how to integrate requirements into CI/CD, testing, and deployment workflows.
12 chapters in this module
  1. Integrating with CI pipelines
  2. Adding model cards automatically
  3. Enforcing documentation gates
  4. Checking for bias in training sets
  5. Validating explainability outputs
  6. Monitoring for drift at scale
  7. Using policy-as-code tools
  8. Creating automated red flags
  9. Linking to incident response
  10. Versioning policies with models
  11. Auditing governance enforcement
  12. Scaling with infrastructure as code
Module 10. Public-Facing Stance Preparation
Prepare for moments when your organization must speak publicly about AI use. Help shape the narrative with governance-first reasoning.
12 chapters in this module
  1. Anticipating public scrutiny
  2. Preparing proactive disclosures
  3. Aligning legal and technical views
  4. Creating public model cards
  5. Using OECD principles as anchor
  6. Explaining trade-offs transparently
  7. Handling edge case questions
  8. Documenting intent and choices
  9. Supporting PR with evidence
  10. Rehearsing Q&A scenarios
  11. Tracking public sentiment
  12. Adapting posture over time
Module 11. Maintaining Influence Across Change
Keep your voice relevant as teams, projects, and technologies shift. Build durable influence that survives reorgs and turnover.
12 chapters in this module
  1. Documenting decision rationale
  2. Creating reusable templates
  3. Training successors effectively
  4. Building institutional memory
  5. Publishing governance playbooks
  6. Archiving key debates
  7. Standardizing review cycles
  8. Updating frameworks iteratively
  9. Measuring team adoption
  10. Linking to onboarding
  11. Sustaining momentum
  12. Recognizing contributors
Module 12. Measuring and Compounding Influence
Track how your inputs shape outcomes over time. Turn influence into a measurable, repeatable capability.
12 chapters in this module
  1. Defining influence metrics
  2. Tracking participation depth
  3. Measuring downstream adoption
  4. Capturing peer endorsements
  5. Counting avoided rework
  6. Quantifying risk reduction
  7. Benchmarking against peers
  8. Creating feedback loops
  9. Linking to career growth
  10. Sharing impact summaries
  11. Scaling influence beyond self
  12. Building a legacy of impact

How this maps to your situation

  • During architecture review for new AI pipeline
  • Before vendor selection for AI monitoring tool
  • While scoping a cross-team AI rollout
  • After public scrutiny on model behavior

Before vs. after

Before
Input often overlooked in technical governance discussions despite deep platform expertise
After
Consistently shapes AI governance outcomes in design, review, and vendor selection

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 week over 6 weeks, designed to fit around live project cycles.

If nothing changes
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How this compares to the alternatives

Unlike generic AI ethics courses, this program focuses on actionable influence in technical decision-making using OECD AI Principles as a foundation. It avoids abstract theory and delivers specific, reusable tools for earning peer buy-in and shaping real-world outcomes.

Frequently asked

Who is this course for?
Senior technical practitioners who influence AI governance decisions through architecture, code, or cross-functional collaboration.
How is the course structured?
12 modules, each containing 12 chapters (144 chapters total).
Can I apply this across AI platforms?
Yes, the OECD AI Principles are platform-agnostic and designed for implementation across AWS, Lightspeed, and other cloud environments.
$199 one-time. Approximately 3 hours per week over 6 weeks, designed to fit around live project cycles..

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