From Human IAM to AI Identity Security
Enterprise IAM was built for employees and contractors, but organizations now depend on non-human identities such as software bots, cloud services, scripts and increasingly autonomous AI agents. These agents can make decisions and trigger actions at machine speed, often without clear ownership or consistent oversight. That shift is driving a new focus on AI identity security and agentic access control, where agents are treated as first-class identities that must be discovered, catalogued, governed and continuously monitored. Industry research underscores the urgency: surveys show most organizations already run AI agents in production, yet many security teams struggle to distinguish agent activity from human activity across systems. Traditional identity governance tools, which assume relatively static applications and long‑lived accounts, are being stretched by the autonomy, ephemerality and delegated authority typical of AI agents. In response, leading vendors are re-architecting platforms to unify human, machine and agentic identities under a single governance model.
Palo Alto Networks’ Idira: A Unified Control Layer for Human and Agentic Access
Palo Alto Networks’ new Idira platform positions identity as the central control plane for human, machine and fully agentic accounts. Instead of treating AI agents as an afterthought, Idira brings employee logins, service accounts and autonomous agents into one policy framework, allowing security teams to see who or what can access which systems, grant just‑in‑time privileges and automatically revoke access once tasks are complete. The platform aggregates capabilities from CyberArk for privileged-access management, Koi for visibility into AI-related assets such as plugins and scripts, and Portkey for AI-agent governance across enterprise AI systems. Integrated with Prisma AIRS, Cortex and Strata, Idira pushes identity decisions directly into AI runtime security, security operations and network enforcement workflows. With over nine in ten surveyed organizations reportedly running autonomous agents in production, the aim is to cut the risk and operational cost of sluggish privilege changes, weak revocation and opaque agent behavior.
SailPoint’s Agentic Fabric: Mapping AI Agents to Owners and Data
SailPoint is extending identity governance through its Agentic Fabric, a new layer that brings AI agents and other non-human identities into the same discipline traditionally applied to employees and service accounts. The platform is designed to inventory AI agents, machine identities and applications across clouds, application agents and endpoints, then connect those entities to critical data via an identity graph. Crucially, Agentic Fabric maps every agent to a human owner, assigning clear accountability and enabling lifecycle controls and real-time authorization. SailPoint also offers a Discovery Tool to uncover shadow AI and unmanaged applications that may be operating outside existing controls. New commercial tiers such as Agentic Business and Agentic Business Plus aim to enforce least-privilege and zero-standing privilege models, where powerful rights are granted just in time and revoked immediately after use. This approach keeps SailPoint firmly in the identity governance and administration space while adapting to agentic use cases.
Why Non-Human Identities Demand New Governance Patterns
AI agents introduce autonomy, ephemerality and delegation patterns that strain conventional enterprise IAM. Agents spawn on demand, chain tasks to other services and operate across multiple systems without persistent accounts. Industry groups highlight that many organizations cannot reliably distinguish human and agent activity, despite relying on agents for automation, research, development and even security monitoring. This creates blind spots where agents may over‑reach their intended scope, retain excessive privileges or access sensitive data without adequate supervision. Effective AI identity security therefore requires traceable agent identities, fine‑grained, policy-driven authorization and continuous monitoring of multi-agent workflows. Governance models must ensure that every agent has a defined owner, clearly scoped permissions and a lifecycle tied to specific business tasks. Without these controls, enterprises risk unauthorized agent actions, data leakage and difficulty proving compliance, especially as AI agents become embedded in everyday operations and decision-making pipelines.
Towards Unified Agentic Access Control in Enterprise IAM
Taken together, platforms like Idira and Agentic Fabric signal a broader shift toward unified agentic access control in enterprise IAM. Rather than bolting AI-specific tools onto existing stacks, vendors are integrating AI agents into core identity governance workflows. Unified control layers now cover human users, machine identities and autonomous agents through common policies, entitlement models and monitoring interfaces. Privileged access for agents can be granted just in time, routed through AI-aware gateways and continuously evaluated in the context of data sensitivity and runtime behavior. For security leaders, this means identity governance agents and control planes become strategic instruments for managing AI adoption, not just compliance checkboxes. The emerging best practice is clear: treat every agent as an identity, tie it to a responsible owner, restrict it to least-privilege by default and embed its governance into the same frameworks that already protect human and machine access.