Understanding the risks, challenges, and strategies for securing unsanctioned AI in the enterprise

Shadow AI—the unsanctioned use of AI tools by employees without IT or security approval—has become the fastest-growing risk enterprises can’t see. According to Acuvity’s State of AI Security research, 49% of organizations expect Shadow AI incidents in the next 12 months. The gap between AI adoption and governance is widening. And as employees move from simple chatbots to autonomous agents that connect to enterprise systems, the stakes are getting higher.

Download the paper to learn:

• • The key risks Shadow AI introduces—from sensitive data leakage and compliance violations to expanded attack surfaces and credential exposure.
  • How AI agents amplify these risks by acting autonomously, holding credentials, and taking actions that look like normal user activity.
  • What semantic privilege escalation is, and why traditional RBAC can’t stop an agent from going beyond its instructions while staying within its permissions.
  • Why legacy security tools like CASB, SWG, and DLP lack the visibility and context to manage AI-native workflows.
  • How to build a Shadow AI management program—from discovery and risk assessment to policy enforcement, attribution, and agent audit trails.
  • How policy-as-code enables security teams to maintain consistent control across heterogeneous agent deployments at scale.