Course Overview
This course provides learners with the essential skills to govern the design, deployment, and scaling of autonomous, Agentic AI systems. It focuses on enabling rapid innovation and accelerating speed-to-market while managing the unique risks presented by AI systems that can make decisions without constant human input.
The course is structured around the practical application of the four-phase Agentic AI Governance Maturity Roadmap (Establish, Implement, Scale, Accelerate).
The course uses a blend of presentations, detailed case-study scenarios (Cymbal Health, Cymbal Insurance, etc.), group discussions, a tabletop exercise, and quizzes to ensure effective learning. The real-world examples ensure participants can immediately connect theoretical principles to their own organizational and regulatory challenges.
Who should attend
- Business leaders
- Technical practitioners
- Governance professionals
Course Objectives
Learners will gain an understanding of:
- Defining Agentic AI and identifying the key risk vectors unique to autonomous systems (e.g., opacity of logic and the accountability void).
- Establishing the foundational structure, including a cross-functional AI governance committee and core ethical principles.
- Implementing technical enforcement mechanisms, such as real-time audit logging (Decision Provenance Logs) and building in technical guardrails like the Human Veto Point (HVP).
- Scaling governance enterprise-wide by standardizing tooling, establishing a centralized orchestration platform, and integrating controls into the CI/CD pipeline.
- Leveraging governance as a competitive advantage by shifting from oversight to enablement and monetizing trust through external transparency.
Outline: Agentic AI Governance Essentials (AAIGE)
Module 1 - The agentic AI governance imperative
Topics:
- Defining agentic AI
- The governance gap
- Agentic AI risk
- Introduction the governance maturity roadmap
Objectives:
- Define agentic AI and understand its governance implications.
Module 2 - Establish
Topics:
- Setting strategic vision and accountability
- Business scenario: Cymbal Health
- 6 steps for Establish phase
Objectives:
- Identify key risk vectors unique to autonomous AI systems.
- Establish accountability and oversight mechanisms.
Activities:
- 1 discussion topic
Module 3 - Implement
Topics:
- Building technical enforcement
- Business scenario: Cymbal Insurance
- 6 steps for Implement phase
Objectives:
- Implement governance frameworks for agentic AI deployments.
- Design controls that balance innovation with risk management.
Activities:
- 1 discussion topic
Module 4 - Scale
Topics:
- Embedding governance enterprise-wide
- Business scenario: Cymbal Shops
- 5 steps for Scale phase
Objectives:
- Establish accountability and oversight mechanisms.
Activities:
- 1 tabletop exercise
Module 5 - Accelerate
Topics:
- Leveraging governance for competitive advantage
- Business scenario: Cymbal Fintech
- 5 steps for Accelerate phase
Objectives:
- Design controls that balance innovation with risk management.
Activities:
- 1 discussion topic
Module 6 - Conclusion and quiz
Topics:
- Recap
- Q&A
- Quiz
- Survey