Managing the Risk of Agentic AI

As enterprises pivot from generative AI assistants to highly autonomous, goal-directed agentic AI, the risk landscape undergoes a fundamental shift. Traditional AI safety focused on filtering static text inputs and outputs; however, agentic AI risk management requires governing systems that autonomously break down tasks, select tools, modify data, and orchestrate other agents in non-deterministic ways. Managing this risk requires moving away from static policy documents toward a programmatic dual-control framework built directly into the agent’s execution platform.

Presented by:

Ronnie Owens

Ronnie has 20+ years of experience in marketing, focusing on developing and executing strategies that increase revenue, customer engagement and competitive differentiation. He holds an SHSMD credential in healthcare marketing, which demonstrates his knowledge and skills in marketing plans, communications and market research.

This meeting has been approved for a total of 1.0 contact hours of Continuing Education Credit toward fulfillment of the requirements of ASHRM designations of FASHRM (Fellow) and DFASHRM (Distinguished Fellow) and towards CPHRM renewal.