Autonomous AI agents are transforming enterprise workflows, but they bring a new set of security challenges that traditional controls weren’t designed to solve.
Unlike conventional apps, agents can discover tools, delegate tasks, and trigger workflows independently. Securing them requires more than just model guardrails or static API scopes—it requires a dedicated runtime control plane.
Our latest white paper, „Architecting Governed Agentic AI,“ details how Broadcom’s AgentMinder addresses the Agentic Control Gap. We explore how to:
• Establish verifiable, mission-scoped agent identities.
• Enforce intent-aware authorization in the execution path, before tool calls reach your systems.
• Maintain clear accountability with correlated runtime evidence.
• Scale autonomous workflows while keeping security, operations, and audit teams in the loop.
Read the full white paper to learn how to move from static permissions to risk-aware, governed autonomy.
#AgenticAI #Broadcom #CyberSecurity #AgentMinder #AIgovernance
Architecting Governed Agentic AI: The Broadcom…
This asset is a longer white paper that describes in detail how AgentMinder establishes identity, enforces intent, controls delegation, and produces runtime evidence for autonomous AI agents. It is intended for security/enterprise architects. Please share with your networks.
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