AI Agent Identity Security Maturity Model

Move your organization from unmanaged AI risk to continuous, intent-based security governance.

AI agents are already writing code, accessing sensitive data, calling APIs, and acting through powerful non-human identities. But most organizations still don’t know which agents exist, what they can access, or whether their permissions match their purpose.

The AI Agent Identity Security Maturity Model gives security, identity, and IT teams a practical framework to assess AI agent risk and move from invisible exposure to governed, scalable AI adoption.

What You Will Learn

Inside the guide, you’ll learn how to:

Assess your organization across five maturity stages: Unseen, Observed, Contextualized, Controlled, and Governed
Understand why traditional IAM and prompt guardrails fail for AI agents
Identify gaps in agent visibility, ownership, access control, and lifecycle governance
Move from reactive monitoring to intent-based least privilege
Build a path toward continuous governance and automated remediation

Why It Matters

AI agents don’t behave like human users. They operate continuously, inherit powerful credentials, and connect across cloud, SaaS, APIs, and business-critical systems.

Without identity-first controls, agents become trusted by default even when security teams can’t see them.

This maturity model helps you understand where risk exists today and what capabilities are needed to secure AI agents from creation to runtime.

The Five Stages of AI Agent Identity Security

Stage 1: Unseen‍

You don’t know what agents exist.

Stage 2: Observed
You can see some agents, but you can’t govern them.

Stage 3: Contextualized
You understand what agents are doing, but security is still reactive.

Stage 4: Controlled
Access is aligned to agent intent.

Stage 5: Governed
Security operates continuously at the speed of AI.

Built for AI Agent Identity Security

Token Security helps organizations secure every AI agent through three core capabilities:

Discover every AI agent, MCP server, custom GPT, and non-human identity

Understand each agent’s owner, access, behavior, intent, and blast radius

Enforce least privilege, lifecycle governance, policy, and remediation continuously

Download the AI Agent Identity Security Maturity Model

See where your organization stands and learn what it takes to reach governed, secured, and scalable AI adoption.

AI Agent Identity Security Maturity Model

Move your organization from unmanaged AI risk to continuous, intent-based security governance.

Download the Maturity Model eBook

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AI Agent Identity Security Maturity Model

Move your organization from unmanaged AI risk to continuous, intent-based security governance.

The AI Agent Identity Security Maturity Model gives security, identity, and IT teams a practical framework to assess AI agent risk and move from invisible exposure to governed, scalable AI adoption.

What You Will Learn

Inside the guide, you’ll learn how to:

Assess your organization across five maturity stages: Unseen, Observed, Contextualized, Controlled, and Governed
Understand why traditional IAM and prompt guardrails fail for AI agents
Identify gaps in agent visibility, ownership, access control, and lifecycle governance
Move from reactive monitoring to intent-based least privilege
Build a path toward continuous governance and automated remediation

Why It Matters

AI agents don’t behave like human users. They operate continuously, inherit powerful credentials, and connect across cloud, SaaS, APIs, and business-critical systems.

Without identity-first controls, agents become trusted by default even when security teams can’t see them.

This maturity model helps you understand where risk exists today and what capabilities are needed to secure AI agents from creation to runtime.

The Five Stages of AI Agent Identity Security

Stage 1: Unseen‍

You don’t know what agents exist.

Stage 2: Observed
You can see some agents, but you can’t govern them.

Stage 3: Contextualized
You understand what agents are doing, but security is still reactive.

Stage 4: Controlled
Access is aligned to agent intent.

Stage 5: Governed
Security operates continuously at the speed of AI.

Built for AI Agent Identity Security

Token Security helps organizations secure every AI agent through three core capabilities:

Discover every AI agent, MCP server, custom GPT, and non-human identity

Understand each agent’s owner, access, behavior, intent, and blast radius

Enforce least privilege, lifecycle governance, policy, and remediation continuously

Download the AI Agent Identity Security Maturity Model

See where your organization stands and learn what it takes to reach governed, secured, and scalable AI adoption.

AI Agent Identity Security Maturity Model

Move your organization from unmanaged AI risk to continuous, intent-based security governance.

Download the Maturity Model eBook

The POV was performed in production, staging, and test environments with members from the Security and SecOps teams, and integration was completed in two meetings.

About us

Token Security offers a centralized non-human identity security solution for modern cloud environments, mitigating risks and challenges originating from the inherent interaction between non-human and human identities.

Our solution offers comprehensive visibility into all non-human identities, providing granular inventory management. Using our AI-based engine, we offer a broader security context, conduct risk analysis, and establish identity ownership, enabling security teams to identify and automatically remediate critical risks. Additionally, we securely manage the lifecycle of all non-human identities.

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