In this module, participants move from understanding why boards must govern AI to learning how to build a durable governance architecture that blends control with innovation. Effective AI oversight demands clarity, not just in principles, but in organizational structures, decision rights, and accountability mechanisms that scale as AI adoption expands.
By completing Module 2, participants will:
• understand three proven AI governance architectures and learn how to select the model best suited to their organization,
• define clear roles, decision rights, and accountability across the enterprise, from the boardroom to operational teams,
• create a documented AI Governance Charter that formalizes board-approved standards and enforcement mechanisms,
• design a scalable three-layer governance structure (board, executive, operational) that avoids bottlenecks while maintaining oversight,
• align internal governance frameworks to global standards such as NIST AI RMF, ISO 42001, EU AI Act,
• assess their organization’s maturity and readiness across key governance dimensions.
To operationalize these learnings, participants will gain access to a suite of customizable frameworks, templates and/or other materials that make implementation immediately actionable. These resources include:
• a detailed charter blueprint for establishing governance principles,
• a decision rights matrix clarifying accountability across teams,
• a comparison guide covering the three leading AI governance architecture models,
• a 90-day implementation checklist for launching governance effectively,
• a quick-reference card summarizing structure and responsibilities,
• a learning and reflection worksheet to support continuous improvement.
Next is your main slide deck:
Disclaimer
Next are your compendium of and individual frameworks, templates and other materials. You can customize per your organization’s contextual needs: