Did we solve AI agent identity in 2025? (raxit.ai)

AI agents are fundamentally challenging traditional identity and access management (IAM) systems, driving the need for innovative frameworks that ensure security and accountability. As these autonomous entities operate using user credentials to perform tasks across organizational boundaries, they create significant impersonation risks and accountability gaps. With the recent insights from Arnab Bose of Okta and the OpenID Foundation, it's clear that existing OAuth 2.1 frameworks fall short in managing AI agents' non-deterministic actions, dynamic lifecycles, and cross-domain operations. The rapid growth of AI-driven automation necessitates new approaches to identity that can accommodate the complexities of these agents while maintaining regulatory compliance. The industry's transition from traditional IAM to more adaptable models is urgent. Current gaps in identity standards—such as identity fragmentation, consent fatigue, and recursive delegation—jeopardize security and create compliance challenges, particularly concerning the EU AI Act's requirements for accountability in high-risk AI systems. Proposed solutions, like policy-based governance and the OpenID Connect for Agents standard, aim to redefine how AI agents authenticate and operate while promoting interoperability among systems. Addressing these challenges is essential not only for the security of enterprise data but also to foster the responsible deployment of AI technologies across varying domains.