Download The AI Agent Governance Playbook

An AI Agent Governance Playbook addresses the gap between widespread enterprise agent deployment and limited security approval, arguing that traditional governance models struggle because agents act on behalf of accountable users rather than acting as those users directly. It distinguishes model-level guardrails from action-layer governance, emphasizing that controls should be enforced at tool calls, where agents initiate consequential actions such as payments, deletions, or communications. The playbook outlines six action-layer controls: user-agent authorization, policy-as-code, deny-by-default access, step-up approvals, immutable auditing, and deployment isolation. It also provides a reference architecture for integrating governance with existing identity, data loss prevention, and SIEM systems, maps practices to standards including NIST AI RMF, ISO/IEC 42001, the EU AI Act, and OWASP guidance, and includes readiness tools, autonomy tiers, and phased rollout guidance.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.