Agentic IAM Fundamentals

Q1. What is Agentic IAM and how does it differ from traditional IAM?

Agentic IAM is a model of identity and access management for the governance of autonomous AI agents that can make decisions, invoke tools, and continuously act across systems. In contrast to traditional IAM, which authenticates a human and/or an application at login time, Agentic IAM treats agents as first-class identities, with their permissions, lifecycle, and accountability.

One-time access grants are replaced by the introduction of continuous authorization.

Agentic IAM puts an emphasis on context, intent, and scope-not just a matter of credentials.

It supports non-human actors operating without direct interaction with a human.

This allows Access decisions to be assessed dynamically, at the time agents act rather than when they initiate.

Auditability becomes mandatory since agents act at machine speed.

In short, Agentic IAM governs behavior and not just access.

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Q2. What is the "Third Identity Problem" in cybersecurity?

The Third Identity Problem: The increasing divide between human identities, machine identities, and AI agents. Human access was solved by IAM, then machine identities were managed for applications/services. AI doesn’t belong to either category.

Agents behave autonomously, in chain reactions, and in continuous processes.

These can’t be mapped easily to users, apps, or static service accounts.

As a result of this decimal system of measurement, there are blind spots in authorization, auditing

Security personnel have no way of explaining who did it or why.

It's not an authentication issue, it’s scale governance.

Agentic IAM fills the specific purpose of covering the third identity gap.

Q3. What is Agentic Access Management (AAM)?

Agentic Access Management (AAM) refers to the access control layer in Agentic IAM. Agentic AAM regulates the operations that AI agents can perform as well as when and under which circumstances they can happen. Agentic Access Management enforces contextual access in place of permissions as it relies on policies.

Access is assessed on an ongoing basis as agents undertake actions. Permissions are context-specific to intent, task, and environment.

AAM offers step-up controls, revocation, and containment capabilities on a real-time basis.

It prevents agents from going beyond their limitations. It is extremely important when dealing with agents and APIs, data, and workflows.

AAM moves access control from static rules to live policy enforcement.

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Q4. Why was traditional IAM not built for AI agents?

Traditional IAM typically presumes that identities exist for people logging in or apps making API calls. AI agents violate both of these presumptions.

They function with autonomy and without any sign of specific log-in events. Their behavior is subject to dynamic changes based on context and inputs. They may chain together tools, systems, or decisions in a random manner.

Static roles, long-lived credentials become dangerous. The traditional IAM system does not have the concept of intent or continuous control.

It was never intended for explaining or controlling autonomous actions.

Agentic IAM bridges this architecture gap.

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Q5. What defines an "agentic identity" on the Gartner Tech Radar?

An agentic identity is characterized by its ability to act autonomously, to situationally adapt, and to system-level goal fulfillment. Users or services lack this ability, since an agentic identity symbolizes a party capable of taking an action on its own initiative.

They have their own permissions, policies, limitations, and principles.

These run all the time and are not based on

Their activities must be observable and auditable.

Identity is a function not of credentials, but of capability and intent.

Lifecycle Management becomes obligatory from creation and retired.

Such a definition extends IAM into the realm of governed autonomy.

Q6. What is the difference between Generative AI (GenAI) and Agentic AI?

Generative AI emphasizes the creation of text, image, code, or answer content in response to input. Agentic AI extends this capability to take action toward the attainment of goal-states.

Gen AI: answering questions.

Agentic AI: doing tasks.

GenAI is a reactive system, while agentic AI is proactive.

In agentive AI, APIs can be accessed, workflows initiated, and decisions made.

This makes AI no longer a tool but an actor.

Once AI achieves activeness, then identity and access management are utmost important.

That’s where Agentic IAM becomes imperative.

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Q7. Are AI agents considered "users," "applications," or "services" in IAM terms?

AI agents do not fit into any of the existing traditional categories of IAM. They are not users because they do not authenticate in the same manner that users do. They are not simply applications because applications do not act independently. They are not static services because they adapt and evolve.

They are operating on behalf of intent, not sterile logic.

However, they demand scoped, revocable, and auditable access

These could potentially pose risks when they are considered service accounts.

They are considered as ‘users’ which generates friction.

Today, IAM acknowledges agents as a new identity type.

The third, Agentic IAM, properly formalizes this.