Defending Against Adversarial AI Agents – From Digital Darwinism to Guardrails

As enterprises adopt agentic AI, they face a new class of adversary: autonomous, goal-seeking agents that probe controls, data, and policies at machine speed. Building on ideas like “Digital Darwinism” and adversarial agents competing to optimize infrastructure, this session asks: what happens when attackers weaponize agents—and how do
we respond?
Key Questions: – How will adversarial agents change red-teaming, penetration testing, and threat modeling? – What defensive patterns are emerging for agent endpoint protection, data controls, and PII sensitivity mitigation? – Where do AI guardrails, content moderation, and design best practices fit in the security architecture versus at the application layer? – How do we monitor for agent-vs-agent “arms races” inside the enterprise and prevent unintended escalation?
Takeaways: – A taxonomy of adversarial agent threats relevant to Global 2000 environments. – Concrete examples of guardrail policies and monitoring approaches that actually reduce risk.