Agentic AI behavior monitoring: what IAM teams need to catch now

TL;DR: AI security fails when teams focus on code rather than emergent behaviour, because agentic drift can occur inside core business workflows and escape traditional AppSec scanning, according to Pillar Security. The editorial case is that continuous monitoring, posture baselining, and runtime guardrails now matter because AI has become an operational identity and governance problem, not just a model problem.

NHIMG editorial — based on content published by Pillar Security: Why I’m Joining Pillar

By the numbers:

• 96% of technology professionals identify AI agents as a growing security threat, and 66% believe this risk is immediate.

Questions worth separating out

Q: How should security teams govern AI systems that operate inside business workflows?

A: They should govern them as operational actors with runtime access, not as isolated software components.

Q: What breaks when AI security is limited to AppSec scanning?

A: Static scanning misses emergent behaviour, so the organisation can approve code that later behaves outside policy in production.

Q: How do you know if an AI governance programme is actually working?

A: It is working if you can show the system’s real access, real actions, and real deviations from approved behaviour.

Practitioner guidance

• Baseline live AI behaviour before expanding access Capture normal tool calls, data access patterns, and workflow paths for each AI-enabled system, then compare production activity against that baseline so drift is visible early.
• Separate code review from runtime governance Keep AppSec scanning for code and dependencies, but add operational controls that watch how the AI behaves after deployment, especially when it can invoke internal tools or sensitive datasets.
• Map AI-enabled workflows to identity and access owners Assign clear ownership for every AI system that can touch business data or trigger actions, and make the access review include the workflow, the data, and the delegated privileges together.

What's in the full article

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

• The company’s full description of its discovery, posture, red teaming, runtime guardrails, and governance workflow across the AI lifecycle.
• Its explanation of how the SAIL framework is intended to connect people, process, and product in AI security operations.
• The specific positioning behind its recursive defence model and how it is meant to support continuous oversight.
• The article’s own framing of market timing, adoption signals, and why Pillar says this category is taking shape now.

👉 Read Pillar Security’s commentary on why AI security is shifting from code to behaviour →

Agentic AI behavior monitoring: what IAM teams need to catch now?

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