The foundational principle of identity security is the Principle of Least Privilege (PoLP) — giving an entity only the access it needs to perform its job and nothing more. But how do you define “least privilege” for an AI agent whose tasks are fluid? If an agent is tasked with “optimizing supply chain logistics,” it may legitimately need access to finance, inventory and vendor databases. Over-provisioning access makes the agent a dangerous attack vector; under-provisioning it renders it useless.

Human employees have a clear lifecycle: join, move, leave. AI agents are often ephemeral, spun up for a specific project or sprint. However, the credentials and access rights granted to these agents are rarely revoked when the project ends. This creates thousands of “orphaned” identities with active access to critical infrastructure, sitting dormant and waiting to be exploited by malicious actors.

When a human makes a mistake, accountability is straightforward and the audit trail leads back to them. But when an autonomous AI agent modifies a secure database, transfers funds or alters a critical workflow, who is accountable? The employee who prompted it? The developer who built the agent? Or the identity and governance framework that authorized its actions? Establishing clear, immutable audit trails for autonomous agent actions is an unsolved challenge for many organizations, yet it is critical for compliance and risk management.

As identity ecosystems continue to evolve, regularly assessing your identity governance program is essential to maintaining trust, reducing risk and enabling secure innovation. Understanding your current maturity, identifying governance gaps and prioritizing improvements are the first steps toward building a resilient identity strategy.

Product Marketing Manager