White Papers
Detecting Shadow AI
This white paper distills two working sessions of the AI Security Council, where nine practitioners from Oracle Cloud, Western Union, Harvard, Baylor Scott & White Health, Synaptics, SNC-Lavalin / Atkins Global, Good Day Farm, IR Proactive, and AI Product Camp examined why shadow AI now lives inside the systems security already trusts.
What You’ll Learn
- Why the client-side blind spot is where shadow AI actually lives: browsers, local LLMs, personal devices, and embedded AI features in sanctioned SaaS
- How to extend insider-threat detection to AI agents by treating every agent as its own actor
- How to operationalize governance without becoming the bottleneck
- Why identity and authorization debt is the most dangerous inheritance for autonomous agents
- Where practitioners land on the centralized versus federated telemetry debate
- A maturity model and the Council Framework for detecting and governing shadow AI
Download the white paper to see how experienced practitioners are moving from AI adoption to AI accountability in real environments.
Nine security leaders on why the illusion of control is the enterprise's biggest AI security problem, and how behavioral baselines, identity hygiene, and agent-level accountability make shadow AI detectable.
