From Shadow AI to Agentic Risk: A Security Leader's Guide

AI agents introduce security risks that traditional tools weren't built to handle. Unlike conventional software, AI systems are non-deterministic — data becomes executable logic, agents act autonomously, and shadow AI proliferates faster than security teams can track. Regulatory frameworks like the EU AI Act demand continuous, documented oversight.

What you'll learn:

• How to discover every AI asset — models, agents, MCP servers, and shadow AI — across code, cloud, and SaaS
• Strategies for detecting compound risks that only emerge at the intersection of data, identity, and agent behavior
• Best practices for continuous AI governance and live compliance mapping to EU AI Act, NIST AI RMF, and ISO 42001
• How to eliminate the investigation tax with contextual remediation that assembles the full risk story automatically

This guide reveals how leading security teams are closing the AI visibility gap with a platform that connects every AI asset, identity, and data flow into a single risk view, delivering continuous governance and compliance evidence.