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AI Business & IndustryLarge Language ModelsAI Safety & AlignmentSiliconANGLE AIPublished: Sep 1, 2026, 10:00 JST1 min read

Enterprises face agent governance gap

Enterprises face agent governance gap

Key takeaway

  • AI agents now handle mission-critical work fast, outpacing governance.

  • Broadcom says treating agents as identities is key.

  • Firms should start by watching traffic, then add controls.

3 Key Points

  1. What happened

    Broadcom's Clayton Donley says companies are doing mission-critical work with AI agents quickly, but without the controls built for human employees.

  2. Why it matters

    This gap means agents can act without certification or audit, a risk regulated industries can't carry for long, Donley explained.

  3. What to watch

    Broadcom recommends starting passively by watching traffic, then adding a central control point to enforce policy.

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Context & Analysis

The conversation at VMware Explore 2026 highlights a shift in AI security: from external threats to internal agent behavior. Broadcom's approach extends distributed tracing to agent actions, applying lessons from employee access control to AI. As agents take on more mission-critical tasks, enterprises must adopt identity-based governance to avoid regulatory and operational risks.

FAQ

What does Broadcom suggest as a first step for AI agent governance?
Start passively by watching the traffic, which is easy and cheap, then introduce a central control point to enforce policy.
Why is agent identity important?
Treating agents as identities first allows you to control access and monitor actions, which is critical for safe operation.
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