The Next Frontier of Governance: AI Agents

Much of the AI governance conversation to date has centered around models and tools that perform a few primary tasks when prompted by a user. The current governance paradigms and frameworks accordingly depend on the regular human intervention that these models require. These conventions are quickly proving unfit for agentic models that, in many cases, can perform functions without a “human-in-the-loop". As this technology advances, the implications for capital markets, investment risk, and regulatory compliance are becoming increasingly urgent. Investors, particularly in venture capital and private equity, are grappling with how to evaluate, fund, and scale startups building agentic systems. This discussion will address these tensions and the key directions that AI governance conversations need to occupy to adapt to the changing technological landscape. This session will cover topics including current approaches and best practices for AI governance, the shifting dynamics for investors and operators, the functional differences between traditional and agentic AI systems, and suggestions for AI governance of the future.

What you will learn:

• Clear understanding of the new issues raised by agentic AI, AI governance frameworks, including the laws, policies, and practices needed to responsibly manage AI development, deployment, and risks.
• Best practices and lessons from organizations that have successfully implemented AI Governance Councils.