As enterprises rapidly transition from passive LLM chatbots to autonomous AI agents capable of executing multi-step business tasks, risk leaders face an entirely new paradigm of operational danger. Unlike static models, autonomous agents have the authority to act—calling APIs, querying databases, and modifying corporate environments. Knowing how to establish guardrails without halting business innovation has left many security leaders paralyzed. This session cuts through the hype, delivering hard-learned lessons and actionable insights gathered directly from the frontlines of enterprise AI deployment and incident response.

Moving past theoretical frameworks, this talk addresses the real-world friction points keeping leadership up at night: privilege creep, "black box" execution pathways, and the rise of shadow agent deployments by business units. Attendees will learn how organizations are successfully balancing innovation and risk, exploring practical strategies to safely enable these high-productivity tools without inadvertently opening a backdoor to enterprise data assets.

Key areas covered include:
- The Agentic Risk Landscape: A frontline analysis of the unique security, compliance, and operational risks introduced when autonomous agents are granted execution capabilities.
- The Governance Blueprint: Core pillars for establishing operational guardrails, creating cross-functional oversight, and integrating agentic threat modeling into existing enterprise risk management frameworks.
- Real-World Case Studies: Lessons learned from early enterprise deployments, highlighting both rapid business wins and overlooked security gaps that led to live incidents.
- Securing the Ecosystem: High-priority technical and procedural controls to secure the AI agent lifecycle without degrading model performance.