Derrick Gallegos

Generative and agentic AI systems create novel attack surfaces and operational risks for enterprises. This panel explores how technical leaders are designing secure architectures, applying threat modelling, and layering defence-in-depth to protect production AI. It focuses on embedding traceability, privacy, and validating outcomes while keeping systems reliable at scale.

• Designing secure architectures for GenAI and autonomous agents.

• Applying threat modelling to emerging AI attack surfaces.

• Implementing defence-in-depth for privacy, traceability, and control.

AI agents blur the boundary between technology and workforce: they operate within rules, yet exercise discretion in execution. This panel debates whether agentic systems should be governed like software, like employees, or through a new hybrid accountability model. Panellists examine how organizations define risk ownership and prioritize privacy when outcomes are unpredictable and failures carry operational, reputational, and regulatory consequences.