Description

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.

Learning 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.

Who Should Attend

• Business leaders
• Technical practitioners
• Governance professionals

Course Outline

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