By Itamar Apelblat, CEO & Co-founder, Token Security
If you are a CISO today, agentic AI probably feels familiar in an uncomfortable way. The technology is new, but the pattern is not. Business leaders are pushing hard to deploy AI agents across the organization, while security teams are expected to make it safe without slowing anything down.
That tension has existed before with cloud, SaaS, and DevOps. Each time, identity sat at the center of both the risk and the solution.
Agentic AI is no different. It is not primarily an AI governance problem. It is an identity problem, and CISOs will ultimately own the outcome.
For years, security programs were designed around human identities. Employees and contractors were centralized, roles were defined, access was reviewed, and offboarding was predictable. Machine identities disrupted that model by multiplying rapidly and spreading across clouds, pipelines, and SaaS platforms. Governance lagged, but the core assumptions still held. AI agents break those assumptions entirely.
AI agents represent a new class of identity. They behave with intent like humans, yet operate with the scale and persistence of machines. They are decentralized by default, easy to create, and capable of acting across multiple systems without direct human involvement.
From an identity perspective, this is the most complex combination possible. These agents authenticate, authorize, and take action, but they do not fit cleanly into existing identity models.
AI agents aren’t just following instructions, they’re taking action.
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This matters because identity remains the most common root cause of breaches. Credentials are abused. Privileges accumulate. Ownership becomes unclear. Agentic AI amplifies all of these risks at once.
Many agents are granted broad access simply to function quickly. Few are reviewed. Fewer are ever decommissioned.
Some continue operating long after the projects or people that created them are gone. For an attacker, these always-on, overprivileged identities are an ideal target, just look at the latest from OWASP which qualifies that risk.
Traditional IAM and PAM tools were not designed for this reality. They assume users are people or, at best, predictable workloads. AI agents do not live in a single directory, do not follow static roles, and do not remain within a single platform boundary.
Trying to secure them with legacy, human-centric controls creates blind spots and false confidence. Relying on AI platform vendors to solve this problem is equally risky. Just as cloud providers did not solve cloud security, agent platforms will not solve enterprise identity risk.
The way forward is not to restrict innovation, but to apply a discipline CISOs already understand: lifecycle management. Workforce identity security only became scalable once organizations treated identity as a lifecycle, from onboarding through offboarding. AI agents require the same thinking, adapted for speed and scale.
Every agent needs clear ownership tied to the identity provider. Its purpose must be explicit and measurable. Its access should align with what it actually does, not what was convenient at creation. Activity must be continuously visible so privilege drift can be detected early. And when agents go idle, projects end, or owners leave, access must be revoked automatically. Without these controls, AI adoption will eventually collapse under its own risk.
One critical shift CISOs must internalize is that agent identity security is fundamentally a data correlation problem. You cannot understand an agent’s risk by looking only at the agent itself.
The true risk is defined by what the agent can reach. That includes the cloud roles it assumes, the SaaS applications it accesses, the data it can read or modify, and the downstream identities it uses.
Securing agentic AI requires correlating identity signals across agent platforms, identity providers, infrastructure, applications, and data layers.
This correlation is what enables CISOs to answer the questions that matter during audits, board reviews, and incident response. Who had access? Why did they have it? Was it appropriate? And, should it still exist? Without that context, AI agents remain opaque and ungovernable. Here’s a security checklist for CISOs that helps plan for questions like these.
Many organizations are currently in a reactive phase, discovering agent sprawl after it has already reached production. That phase will pass quickly. The next stage is prevention.
Identity discipline must move earlier in the lifecycle, at the moment agents are created. Builders need guardrails that force clarity around intent and scope, rather than defaulting to broad privileges just to make it work. If this discipline is absent, CISOs inherit the risk and eventually the consequences.
Agentic AI is becoming a permanent part of how enterprises operate. The question is not whether it will scale, but whether it will scale safely. CISOs will determine the answer. If agent identities remain unmanaged, AI will introduce breaches, compliance failures, and executive backlash that slow innovation.
If agent identities are governed through lifecycle management and visibility, AI becomes sustainable, agile, and secure.
The organizations that succeed will not be the ones that say yes or no to agentic AI. They will be the ones that say yes with confidence, because they recognized early that securing agentic AI is an identity prerogative.
If you’re ready to confidently address your agentic AI security, Token can help.
Schedule a demo here so we can show you what sets our platform apart in keeping your organization secure.
Sponsored and written by Token Security.