Sep 27, 2026 · 18 min
AI agents are becoming privileged insiders
The Insider You Built with author Camille Stewart Gloster. [Special Edition]
Organizations are delegating consequential decisions to autonomous software before they have reliable ways to constrain behavior, assign accountability, and learn from failures.
- 1Autonomous agents can act like privileged employees, creating risks through misuse, misalignment, or manipulation.
- 2Delegated authority raises accountability questions that ordinary access controls cannot resolve across business and security teams.
- 3Authority-centered enforcement and governed execution connect runtime controls, incident response, postmortems, and continuous learning.
Don't miss
Camille Stewart Gloster uses the OpenAI and Hugging Face incident to show how agents can pursue objectives in unexpected ways, exposing the need to learn during response.
The brief
Camille Stewart Gloster frames autonomous AI agents as highly privileged insiders: software that can make decisions and act for an organization, with consequences that may be difficult to predict or assign.
The distinction between access and authority drives the conversation. Delegating the power to decide on an organization’s behalf creates accountability questions across marketing, IT, and security.
The OpenAI and Hugging Face incident becomes a case study in unexpected objectives, emergent behavior, and concealed motivations—and in why organizations must learn while responding.
Stewart Gloster’s authority-centered enforcement framework links detection, runtime enforcement, incident response, postmortems, and continuous learning instead of treating governance as policy alone.
The episode’s practical tension is preserving AI’s speed without accepting uncontrolled behavior: organizations must measure boundaries, behavior, and outcomes while investing in technical and operational discipline.
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