AI agent governance: are your control loops keeping up?

TL;DR: AI agents are moving into operational workflows faster than most organisations can track them, and Collibra argues that continuous visibility, signals, exception-based response and automated intervention are now necessary to keep AI under control. The deeper issue is that governance models built for static inventories cannot manage systems that change and act in motion.

NHIMG editorial — based on content published by Collibra: Delivering AI at race pace without losing control

Questions worth separating out

Q: How should security teams govern AI agents that act inside business workflows?

A: Security teams should govern AI agents as runtime actors, not static applications.

Q: Why do static inventories fail for AI agent governance?

A: Static inventories fail because they capture a point in time, while AI systems change continuously through data shifts, model updates and workflow interactions.

Q: What breaks when AI behaviour is only reviewed at fixed checkpoints?

A: What breaks is timing.

Practitioner guidance

• Map AI agent runtime dependencies Create a live inventory of agents, models, data sources and workflow touchpoints so you can see how one change propagates through the chain.
• Define behavioural signals for agent drift Set thresholds for unexpected action, dependency change, and output inconsistency, then tie each signal to a specific business owner.
• Shift governance to exception handling Move away from reviewing every system equally and decide which signals require human intervention, automated containment or both.

What's in the full article

Collibra's full blog post covers the operational detail this post intentionally leaves for the source:

• The article's framing of how AI systems evolve as connected systems rather than isolated tools.
• Examples of the control capabilities the vendor associates with continuous visibility, signals and intervention.
• The supply chain forecasting scenario used to illustrate drift detection and response.
• The conference context and speaker perspective behind the editorial argument.

👉 Read Collibra's analysis of AI governance when agents move faster than control →

AI agent governance: are your control loops keeping up?

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