Zero Trust for the Age of Autonomous AI Agents - Part 1
AI Summary
Zero trust models fail in the context of autonomous AI agents because they were designed for human-centric security. Traditional zero trust approaches cannot resolve the paradox between utility and least privilege when applied to agentic AI at scale.
Texas Relevance
The article does not explicitly mention Texas, TX, TCUD, or any Texas-specific entities. It discusses a general issue in cybersecurity that applies broadly but is not specific to Texas credit unions.
Original Content
Why Human-Centric Zero Trust Models Fail in a World of Autonomous AI Agents Zero trust was built for humans, not autonomous AI agents. As organizations adopt agentic AI at scale, human-centric security assumptions break down - creating a paradox between utility and least privilege that traditional zero trust models cannot resolve.