Identity for AI Agents

Artificial Intelligence (AI) agents are software entities endowed with the ability to plan, reason, and act on behalf of humans or other systems. They can automate repetitive tasks, dynamically adapt to new information, and interact with external systems via APIs or graphical user interfaces (GUIs). Because they can operate at scale and with high autonomy, organizations must carefully consider how Identity & Access Management (IAM) practices should evolve to accommodate these agents.

According to recent industry perspectives, AI agents are becoming a top strategic technology trend, with major technology providers already investing heavily in agent frameworks and platforms. Equally, key stakeholders are highlighting identity management as a critical requirement – especially as AI agents begin to handle sensitive data and transactions on behalf of users. These needs include authenticating agents, limiting their privileges, and tracking their lifecycle.

In particular, Computer Using Agents (CUA) introduce complexities that do not align perfectly with traditional IAM models, which were designed for human users or API-based client applications. These agents operate in ways that blur the lines between automation and human-driven interactions, requiring new IAM strategies to ensure security and control.

As AI agents become an integral part of enterprise ecosystems, Identity & Access Management (IAM) must evolve to address new security, governance, and compliance challenges. Agents are a new class of user that requires a thoughtful IAM approach across the entire agent lifecycle.

To address these challenges, organizations must adopt a proactive IAM approach for AI agents, focusing on:

• Visibility: Detecting and discovering agents interacting with the digital estate

• Onboarding & Management: Managing agents and the resources they can access under a centralized control plane

• Authentication & Authorization: Enforce least-privilege access with the right human and agent authentication and authorization controls

• Human Oversight: Ensuring human approval and accountability for agent actions

• Threat Protection: Continuously monitor agent behavior, detect anomalies, and revoke access when risks arise

Looking ahead, AI agents present not only IAM challenges but also opportunities to redefine identity management at scale. Organizations that embed AI agent-specific IAM strategies into their security frameworks will be better equipped to harness the full potential of AI-driven automation while maintaining trust, accountability, and control.

By adopting best practices in IAM for AI agents, enterprises can ensure the secure, efficient, and compliant integration of AI automation into business workflows. Those that take the lead in adapting IAM policies for this new paradigm will gain a competitive advantage in managing AI-powered identities effectively.