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Agentic AI is showing up everywhere, and it is not waiting for your security program to catch up. From the VMware Explore floor, we talk with Umesh Mahajan, General Manager for Broadcom’s Application Networking and Security Division, about what changes when AI agents become real workloads that talk constantly, call tools through APIs, and evolve by the week. The headline is uncomfortable but useful: AI helps defenders ship faster, but Frontier AI also helps attackers find vulnerabilities and drive more zero-day behavior than many teams are ready to handle.
We dig into the security model that holds up when agents are dynamic and mistakes travel fast. Umesh explains why you have to solve a dual problem: protecting agents from attacks while also preventing a compromised or misdirected agent from attacking others. That leads to concrete priorities like lateral segmentation, distributed firewalling, IDS/IPS, and NDR-style behavioral detection, plus network-level controls to reduce the risk of sensitive data exfiltration. We also talk about discovery, because shadow AI is already a reality. If you cannot identify which agents, MCP tools, servers, and models are running, you cannot confidently separate authorized usage from risky sprawl.
Finally, we tackle the fear every operator has: security that slows the business down. We cover why performance and latency matter more for AI workloads, how enforcement close to the hypervisor can reduce overhead, and what it takes to deploy protection quickly so “bought but not deployed” does not become your weak spot. If you’re building enterprise AI on VMware infrastructure, this is a practical map for getting safer without stalling momentum.
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Learn more about Microsoft's ISOC announcement: https://fandf.co/4iQ9b5n
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