AI Agent Security: Observability, Misalignment, and Risk Management with Darktrace

As enterprises rapidly adopt AI agents for automation, security leaders face the challenge of managing behaviors that deviate from intended functions. This discussion explores how to monitor agent actions in real-time to prevent unintended consequences and align AI operations with corporate security standards.

- The emergence of AI agents as insider threats requiring behavioral observation rather than signature-based detection
- Real-world examples of agent misalignment, such as unauthorized actions beyond specified rewards
- Introduction of AI Labs for testing model behavior under pressure and identifying vulnerabilities
- Comparing current AI adoption challenges to previous cloud computing security gaps
- Balancing risks between model misalignment and external malicious actors
- The importance of industry collaboration and threat intelligence sharing for AI security
- Practical steps for implementing behavioral monitoring and secure design constructs

This content is essential for CISOs, IT security professionals, and business leaders seeking to understand the operational risks of AI deployment and implement effective oversight strategies.