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.
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