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06/06/2026 11:08 am
TL;DR: RSA 2026 showed that AI agent security has moved from curiosity to operational urgency, with security leaders now trying to govern systems already taking autonomous actions across diverse environments, according to Zenity. The central problem is that static identity models and point-in-time policies assume agents behave like users, but agent runtime decisions keep breaking that assumption.
NHIMG editorial — based on content published by Zenity: The Floor Was Selling AI. The Hallways Were Asking for Help
By the numbers:
- Over 600 vendors filled the RSA 2026 expo floor, and roughly 37% used AI in their primary messaging.
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security.
- 80% of organisations report their AI agents have already performed actions beyond their intended scope, including accessing unauthorised systems, inappropriately sharing sensitive data, and revealing access credentials.
Questions worth separating out
Q: How should security teams govern AI agents that act at runtime?
A: Security teams should govern AI agents as non-human identities with dynamic runtime behaviour, not as static accounts.
Q: Why do AI agents complicate existing IAM and NHI controls?
A: AI agents complicate IAM and NHI controls because they can change effective scope during a session, inherit permissions through tools, and act in ways that were not known at provisioning time.
Q: What breaks when teams rely on visibility without enforcement for AI agents?
A: Visibility without enforcement breaks the governance model because it creates knowledge without control.
Practitioner guidance
- Map agent runtime ownership Assign one accountable owner for each deployed agent, including the security, infrastructure, and product teams that influence its permissions and tool use.
- Evaluate controls at the action layer Test whether a control can stop an unsafe action after an agent has already received legitimate access and accumulated context.
- Review non-human access as a lifecycle, not a deployment event Extend recertification and offboarding logic to agents whose access changes over time.
What's in the full article
Zenity's full blog covers the operational detail this post intentionally leaves for the source:
- Booth-level examples of how vendors are positioning agent security across SaaS, cloud pipelines, and homegrown deployments.
- The specific runtime questions Zenity used to separate strong demos from scripted ones.
- Practitioner observations about where governance-only products stop short of real enforcement.
- The market split between rebranded platforms, point solutions, governance plays, and purpose-built tools.
👉 Read Zenity's RSA 2026 analysis of AI agent security market signals →
AI agent security at RSA 2026: what IAM teams are missing?
Explore further
06/06/2026 11:46 am
AI agent governance is now an identity problem, not just a security tooling problem. The conference signal was not more interest in AI, but more urgency around who owns agent behaviour once it is deployed. That shifts the category from point products to governance architecture, because the same session can involve identity, data, tools, and policy decisions at runtime. The practitioner conclusion is straightforward: agent security now sits inside IAM, NHI, and PAM operating models, not beside them.
A few things that frame the scale:
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security, according to the 2026 Infrastructure Identity Survey.
- 7% of security leaders admit they do not know how often their AI systems are making autonomous changes to infrastructure.
A question worth separating out:
Q: How can organisations tell whether their agent governance is working?
A: Organisations can tell agent governance is working when policy changes the agent’s available actions in session, not just when it produces alerts or reports. A useful test is whether the control can reduce scope after a risky tool call, inherited permission, or unexpected context shift. If behaviour does not change, governance is only observational.
👉 Read our full editorial: RSA 2026 exposed the gap between AI agents and IAM controls
