What happens when an AI agent is compromised, manipulated, or simply does something nobody expected, but already has permission to access your most sensitive systems? In this episode of Tech Talks Daily, I speak with Geoffrey Mattson, CEO of SecureAuth, about why securing enterprise AI requires businesses to think beyond protecting models and start paying much closer attention to identity, authorization, access control, and what AI agents are actually allowed to do. Geoffrey argues that AI agents present a different security challenge from traditional software. Conventional applications can be tested against relatively predictable behavior. AI models are far less deterministic, particularly when prompt injection, excessive permissions, unexpected behavior, and autonomous actions enter the equation. His advice is to assume an agent could behave unpredictably and control what happens when it attempts to access a database, execute a financial transaction, call an API, or interact with another business system. We discuss what this means as companies race to introduce agentic AI. Geoffrey shares examples of employees granting AI tools permissions without fully understanding what they have approved, along with agents gathering information that creates unexpected privacy and compliance problems. This creates a difficult challenge for CIOs and CISOs. Boards want AI adoption because of its potential competitive value, while employees increasingly depend on AI tools to do their jobs. Simply blocking agents is unlikely to work. Security teams instead need mechanisms that allow innovation while controlling what those agents can access. Geoffrey explains why Zero Trust becomes particularly relevant here. Rather than authenticating a user or agent once and assuming it remains trustworthy, enterprises need to continually evaluate whether an action should be permitted at that specific moment. This leads to the concept of continuous authorization. Geoffrey explains how identity security is moving from asking "Who are you?" toward understanding intent, behavior, context, and authority for individual actions. This becomes increasingly important when one AI agent can create sub-agents, which can then create additional agents and pass permissions down the chain. We also discuss why agentic AI is exposing years of accumulated security debt. Many of the underlying problems are familiar: excessive privileges, inconsistent access controls, incomplete Zero Trust implementations, and systems that trust identities for too long. AI agents amplify those weaknesses because they can operate at machine speed. Geoffrey describes this as combining the unpredictability of humans with the power of machines. For CIOs, CISOs, security architects, identity teams, and business leaders deploying agentic AI, this conversation offers practical questions to ask before connecting agents to enterprise resources. What can the agent access? What authority does it have? Can that authority be reduced as tasks are delegated? Is every important action evaluated independently? And can access be revoked immediately when behavior changes? The goal is not to prevent organizations from using AI agents. It is to create a security layer that gives developers and employees room to experiment while ensuring agents only have the authority they need at the moment they need it. As autonomous AI becomes part of the enterprise workforce, identity alone may no longer be enough. Businesses increasingly need to understand intent, control authority, and continuously decide whether the next action should be allowed.

Ask this episode

“What did the council decide on item 42?” — answered with the speaker and the moment.

Transcript

Related