The Evolution of AI Agents in Enterprise Security

Written by: Itamar Apelblat, CEO and Co-Founder, Token Security

Gone are the days when AI deployments in businesses were limited to drafting emails or summarizing documents. Today, AI agents are taking on more significant roles within enterprises, from provisioning infrastructure to writing production code. They have transitioned from passive assistants to active operators.

However, this shift poses a new challenge for Chief Information Security Officers (CISOs): access control.

Each AI agent within an organization interacts with systems and services, using various authentication methods such as API keys, OAuth tokens, and service accounts. Despite behaving like identities, many AI agents are not treated as such in terms of governance. They often inherit excessive privileges, operate under over-scoped service accounts, and lack proper controls.

This gap in security represents a critical blind spot in AI deployments.

The solution lies in adopting an “identity-first security for AI” approach. This involves treating AI agents as unique identities, defining their roles, establishing clear ownership, managing their lifecycle, enforcing access controls, and ensuring auditability.

However, merely focusing on identity is no longer sufficient.

Traditional Identity and Access Management (IAM) systems were adequate when dealing with human users and predefined workflows. Still, they fall short when handling AI agents that operate at machine speed and evolve dynamically.

The Challenge of Dynamic AI Agents

AI agents are designed to be dynamic, adapting to inputs, planning actions, and interacting with tools based on context. This dynamic nature can lead to unexpected behaviors, such as accessing unauthorized systems or performing actions beyond their original scope.

Unlike traditional IAM controls, which rely on predetermined roles, AI agents require a more nuanced approach known as intent-based permissioning. This method evaluates an agent’s declared mission and runtime context to determine whether it should be granted access at a given moment.

By shifting from static roles to intent-based permissions, organizations can address common security risks associated with AI deployments, such as privilege inheritance and mission drift.

Enhancing Governance with Intent-Based Security

Intent-based security simplifies oversight by focusing on managing defined identity profiles and approved intent boundaries, rather than individual action rules. This shift enables security teams to assess an agent’s mission appropriateness and ensure alignment with its approved purpose.

Moreover, intent-based controls enhance auditability, providing detailed insights into an agent’s actions and the reasoning behind them. This level of traceability is crucial for regulatory compliance and maintaining accountability at the organizational level.

In the era of agentic AI systems, it is essential to treat AI agents as accountable identities constrained by both static roles and declared purpose.

Securing Agentic AI for the Future

As AI agents continue to evolve rapidly, organizations must prioritize governance and security measures that align with their dynamic nature. By assigning unique, lifecycle-managed identities to AI agents, defining their missions clearly, and enforcing controls based on identity, intent, and context alignment, enterprises can mitigate risks associated with autonomous AI systems.

Autonomy without governance poses a significant risk, while identity without intent is incomplete. In the agentic era, understanding the “who” behind actions is just as crucial as ensuring they are acting for the right reasons.

If you’re exploring agentic AI security, we invite you to experience a technical demo of Token and share your insights with us.

Presented by Token Security.