{"id":11966,"date":"2026-04-09T14:36:34","date_gmt":"2026-04-09T19:36:34","guid":{"rendered":"https:\/\/www.carahsoft.com\/wordpress\/?p=11966"},"modified":"2026-04-09T14:38:59","modified_gmt":"2026-04-09T19:38:59","slug":"silverfort-4-ways-ai-agents-change-the-way-we-approach-identity-security-blog-2026","status":"publish","type":"post","link":"https:\/\/www.carahsoft.com\/wordpress\/silverfort-4-ways-ai-agents-change-the-way-we-approach-identity-security-blog-2026\/","title":{"rendered":"4 ways AI agents change the way we approach Identity Security"},"content":{"rendered":"\n

As if gaining visibility into all human and non-human identities wasn\u2019t a big enough task for security teams, adding AI agents into the mix takes identity complexity to a new level. Organizations of all sizes are tackling this new reality, where it feels premature to confidently say they know about all the AI agents running in their environment. <\/p>\n\n\n\n

That uncertainty is not a knowledge gap. It is an attack surface. <\/p>\n\n\n\n

Gartner\u2019s new report on IAM for AI agents<\/a> names the real nugget of truth: \u201cPurpose\/intent cannot be discovered after the fact by monitoring and observability capabilities.\u201d<\/p>\n\n\n\n

That is not just analyst language. It is a fundamental shift in how we need to think about governing agents. You cannot govern agents by watching them after-the-fact. You must know who they are, what they are for, and who is accountable before<\/em> they run. <\/strong><\/p>\n\n\n\n

The numbers that should change your priorities<\/h2>\n\n\n\n

Gartner\u2019s data reinforces the urgency. By 2029, over 50% of successful attacks against AI agents will exploit access control weaknesses. By the year before, 90% of organizations that share credentials between humans and agents will need to make significant investments to undo that design.\"Gartner<\/p>\n\n\n\n

Those numbers are consequences, not causes. The root cause is structural: IAM maturity for agents is uneven. The Gartner lifecycle maturity assessment makes this visible. Authentication and monitoring capabilities are relatively mature. Identity registration and authorization are not. That gap is the story. <\/p>\n\n\n\n

Weak identity registration means the agent was never properly onboarded as an identity. No defined owner. No declared purpose. No documented scope. It has credentials and it is running, but nobody can tell you who built it, what it is supposed to do, or what happens when it breaks. When registration is weak, ownership is unclear. And when ownership is unclear, accountability does not exist. <\/p>\n\n\n\n

Weak authorization means the agent has more access than it needs. It can reach databases, APIs, and workflows that have nothing to do with its intended function. Nobody scoped it down because nobody defined what \u201cdown\u201d looks like. When authorization is weak, privilege is excessive.<\/p>\n\n\n\n

Now combine excessive privilege with autonomy. <\/strong>An agent that can reason, chain tools, and act on its own<\/strong><\/a>, with more access than it should have, and no one clearly accountable for what it does. That is the exploitable attack surface. That is the chain revealed in Gartner\u2019s data.<\/strong><\/p>\n\n\n\n

You cannot protect what you cannot see<\/h2>\n\n\n\n

Before you can govern agents, you need to find them. All of them. Not just the ones your platform team sanctioned. The ones that developers spun up to solve an issue. The ones contractors built. The ones that exist because someone needed to \u201cjust get this working.\u201d <\/p>\n\n\n\n

We hear this consistently from security teams. As one InfoSec manager at a professional services firm put it: \u201cWe do not find out about it until someone goes and does an actual audit of the system.\u201d <\/p>\n\n\n\n

Gartner\u2019s assessment confirms it: identity registration is one of the least mature IAM capabilities for AI agents. Most organizations cannot answer the basics: What is this agent supposed to do? Who owns it? What happens when it breaks? <\/p>\n\n\n\n

Discovery is not a checkbox. It is the foundation. Without it, every policy you write is based on assumptions, and assumptions do not survive first contact with autonomous agents operating at machine speed.<\/strong><\/p>\n\n\n\n

The identity registration gap<\/h2>\n\n\n
\n
\"\"<\/figure><\/div>\n\n\n

Most organizations are trying to govern agents with the wrong tools. They are monitoring. They are logging. But monitoring tells you what happened. Identity registration tells you what should happen. Authorization enforces the boundary between them. <\/p>\n\n\n\n

If your governance model depends on catching problems after they occur, you are always going to be behind. <\/p>\n\n\n\n

This is where many organizations reach for familiar tools. IGA platforms can help with registration and lifecycle management. IAM solutions like Okta or Entra ID can register agent identities. These are necessary steps. But they stop there. They can tell you an agent exists and who requested it. They cannot enforce anything at the moment that agent acts. <\/p>\n\n\n\n

That is the gap: governance on paper versus enforcement in production.<\/strong> <\/p>\n\n\n\n

Agents are identities, but not like any you have managed before<\/h2>\n\n\n\n

The way I read Gartner\u2019s recommendations, there is a unifying thread: treat AI agents like you would treat any identity in your organization. They authenticate. They access resources. They act on behalf of someone. That is not a tool. That is an identity. <\/p>\n\n\n\n

But agents are more complex than traditional identities. They are what we call composite identities. They combine the blast radius of service accounts with the unpredictability of human decision-making at machine speed.<\/p>\n\n\n\n

Four reasons that make them different: <\/p>\n\n\n\n