Closing the AI control gap - architecting security across users, applications, and agents

As AI adoption accelerates, security and risk leaders face a daunting structural challenge: maintaining visibility, governance, and control when AI applications and autonomous agents access sensitive data, generate critical assets, and act on behalf of users at machine speed.

Traditional security architectures relies on rigid boundaries between identity, network, cloud, SaaS, and digital services. Yet AI operates fluidly across all of these layers simultaneously. 

 

How are infosec leaders establishing a unified control framework that governs human users, AI-powered applications, and autonomous agents alike?

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

• Eliminating security silos across identity, network, cloud, and application layers
• Achieving real-time visibility across hybrid environments via continuous runtime monitoring
• Repositioning your AI security architecture from risk mitigator to strategic business enabler

Join us as we examine how forward-thinking security leaders moving from fragmented controls to a single system of visibility, governance, and resilience across hybrid and cloud environments.