Trusting your AI agents

Autonomous AI agents are shifting from passive advisory tools to active enterprise operators. But as agents gain execution authority, they also introduce unprecedented operational and security risks.

When an AI agent "hallucinates" a permission, ignores safety guardrails, or pursues an goal at the expense of system stability, traditional monitoring fails to catch the drift until the damage is already done. 

 

How do you move beyond basic model accuracy to engineer hard systemic controls, behavioral incentives, and strict lifecycle governance?

In our next episode of teissTalk with Thom Langford, we’ll explore:

• Building oversight to spot when an AI agent ignores warning signs and the controls to put in place
• Exploring whether agents, like people, respond better to incentives and consequences
• Building trust into the agentic lifecycle through defined identity, least-privileged permissions and continuous monitoring

Join us as we explore how security and technology leaders are building real-world oversight frameworks to monitor, constrain, and safely scale Agentic AI across the enterprise.