Enterprise AI Agent Governance: A Layered Approach (Build, Deployment And Runtime)
Security Bouelevard, Wednesday, March 18th, 2026
As organizations implement AI agents on a large scale, they are likely to encounter governance challenges.
The current focus in AI security primarily centers on several key concerns: prompt injection, model misuse, and unsafe responses. These issues reflect the immediate risks that enterprises must address as they deploy AI agents, highlighting the need for robust safeguards and monitoring practices throughout the agent lifecycle.
These are important issues, but they represent only one part of the problem.
Three Layers of Governance
In reality, governing AI agents requires three distinct layers of control across the agent lifecycle:
- Build-time governance
- Deployment-time governance
- Runtime governance
Each layer addresses a different type of risk.