From Shadow AI to Agent Inventory: Building a Risk-Driven Governance Model for Enterprise AI Agents

From Shadow AI to Agent Inventory: Building a Risk-Driven Governance Model for Enterprise AI Agents Webinars From Shadow AI to Agent Inventory: Building a Risk-Driven Governance Model for Enterprise AI Agents About the session As enterprises accelerate adoption of agentic AI, security teams are struggling to keep pace with a rapidly expanding and often invisible attack surface. From embedded automation features in enterprise platforms to stand-alone and goal-driven AI agents, organizations face growing risks tied to privilege misuse, unmanaged access, and “shadow AI” proliferation.

In this session, we will explore how security and IT leaders can move from reactive discovery to a structured, risk-driven governance model for AI agents. Attendees will learn practical approaches to identifying high-risk AI agents, mapping agent access and privilege, and implementing sustainable oversight mechanisms that reduce exposure while enabling innovation.

Grounded in real-world security principles and aligned with emerging guidance on agentic AI risk management, this webinar will outline how organizations can bring visibility, identity governance, and accountability to AI agents — without slowing down business transformation.

Key Takeaways:

How to identify and inventory embedded, stand-alone, and goal-driven AI agents

Why privilege modeling and identity governance are foundational to securing AI agents

Strategies to reduce shadow AI risk and regain visibility into automated workflows

How intent-based monitoring and analytics can shorten the threat exposure window

Practical steps to operationalize AI agent governance within existing security programs

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