Birth, Life, Death: Managing Identities in the AI Age

Content creation, workflow assistance, task management. The long list of applications for agentic AI spans the gamut from cybersecurity to marketing and everything in between. But as organizations adopt autonomous AI agents, they aren’t just scaling automation – they’re creating a massive new ecosystem of identities to secure. All while upwards of 68% of organizations lack identity controls for AI and large language models (LLMs).

What was once a more human-centric discipline of identity and access management (IAM) now encompasses tens of thousands of non-human entities, each of which comes with its own access and autonomous actions. This explosion in volume has outpaced the reality of human management with traditional software.  And not only is there an abundance of machine identities, but they’re just as vulnerable as their human-owned counterparts. Yet, the belief in “identity as the perimeter of security” holds true, maybe now more than ever.

The shift from passwords to persistence

IAM was initially built for humans: passwords, MFA prompts, and periodic permission reviews. AI agents and other machine identities, however, don’t log in for a shift each day. They have persistent, often elevated access. They also self-authenticate, sometimes with tokens, certificates, and signatures that are created and destroyed faster than you or I can even blink.

In this new identity landscape, scale is a major challenge. Identities are created and retired, often by workloads in autonomous workflows, faster than humans can reasonably track. Lifecycle complexity is also a challenge, as the number of ephemeral agents and credentials needing to be managed has surged. Traditional IAM tools, designed for a predictable human workforce, are leaving dangerous gaps. But configuration alone is not enough. Only 12% of organizations report being highly confident in their ability to prevent attacks involving machine identities, while even fewer believe their legacy IAM systems can operate effectively in the AI era.

Identity-aware security for the AI era

To meet the identity reality head-on, organizations need a security approach that combines runtime visibility, real-time threat detection, and identity risk analytics across all workloads, services, and endpoints. By connecting identity to runtime behavior, teams gain high-fidelity telemetry that reveals risky or unused permissions, no matter how dynamic the workflow or how large the scale.

Securing machine identities at scale requires a mindset shift: stop treating them as a “static scan and remediate” problem, and start managing them as the dynamic risk surface they are. In the agentic era, that means establishing three non-negotiables for agents and their identities:

1. Policy-driven automation: Identity creation and access management must be automated. AI agents should inherit scoped identities with predefined permissions, boundaries, and expirations from the moment they’re spawned.
2. Defined purpose and ownership: Every machine identity must have a clear purpose and a human owner. If the agent can’t be justified or traced back to a responsible party, it shouldn’t exist.
3. Continuous validation: Standing privileges are a liability. Even if privileges are well-scoped, persistent access must be paired with constant monitoring to detect anomalous behavior the moment it occurs.

The lifecycle of a secure machine identity

In our increasingly AI-powered future, there is no “set-it-and-forget-it” approach that drives us toward security. Machine identities require the same persistent rigor throughout their entire, ever-changing lifecycle as production workloads. Unfortunately, more than 16% of organizations admit they do not track the creation of new AI-related identities.

• Birth: Automatically assign least privilege access upon creation.
• Life: Continuously evaluate permissions and behaviors, adjusting access in real-time as long as the agent is running.
• Death: If an agent is idle, replaced, or unused, reevaluate its use case, revoke its credentials, and retire its identities immediately.

This is the new normal. By embracing the waves of automation and rigorous identity lifecycle management, security teams can turn the “agent explosion” into a secure competitive advantage.