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06/06/2026 11:14 am
TL;DR: RSA 2026 conversations showed the industry has moved from asking what an AI agent is to asking how to secure and govern it in production, according to Zenity. The governance gap is now about frameworks arriving after deployment, while agentic systems are already operating at scale.
NHIMG editorial — based on content published by Zenity: My First RSA: Agents, Challenges, and Community
Questions worth separating out
Q: How should security teams govern AI agents that are already in production?
A: Security teams should treat production agents as governed identities with explicit ownership, scoped permissions, monitoring, and lifecycle review.
Q: Why do AI agents change the way IAM and governance teams think about access?
A: AI agents change access governance because the relevant privilege is not just the account they hold, but the task, context, and tool chain active during execution.
Q: What do security teams get wrong about AI governance?
A: A common mistake is treating AI governance as a model-policy exercise instead of an operational control problem.
Practitioner guidance
- Define agents as governed identities Assign ownership, approval, and review paths to every deployed agent so the security team knows who is accountable for its actions across its lifecycle.
- Measure runtime context, not just access grants Track which tools, datasets, and execution contexts each agent can reach during a live session, then compare that to the intended policy boundary.
- Extend lifecycle governance to agent retirement Require offboarding steps for agents just as you would for privileged human users or service accounts, including revocation of access, tokens, and integrations.
What's in the full article
Zenity's full blog post covers the conference conversations and operational detail this post intentionally leaves at the strategy level:
- First-hand examples of the technical questions practitioners asked about agent security at RSA
- Community observations on how agentic AI governance discussions have shifted from definition to implementation
- The author's broader take on how AI governance teams are responding to real deployment pressure
- Related RSA blog posts that expand on runtime context, full lifecycle security, and practical agent defence
👉 Read Zenity’s RSA 2026 blog on agentic AI security and governance →
Agentic AI governance at RSA: are frameworks keeping up?
Explore further
06/06/2026 11:55 am
Agentic AI governance is arriving after deployment, not before it. The article describes a market where practitioners are already asking how to secure agents in production, while governance frameworks are still catching up. That pattern means security programmes are being asked to retro-fit oversight onto working systems instead of shaping adoption from the start. The implication is that agentic AI is now an operational identity problem, not a future policy exercise.
A few things that frame the scale:
- 85% of organisations lack full visibility into third-party vendors connected via OAuth apps, according to The State of Non-Human Identity Security.
- Only 1.5 out of 10 organisations are highly confident in their ability to secure NHIs, compared to nearly 1 in 4 for securing human identities.
A question worth separating out:
Q: How can organisations tell whether their agent governance is working?
A: A useful signal is whether every agent has a clear owner, a defined use case, a live access boundary, and a documented retirement path. If any of those are missing, governance is incomplete. The strongest programmes can show that permissions, monitoring, and review all change when the agent changes role.
👉 Read our full editorial: Agentic AI governance is lagging as RSA conversations mature
