AI Agents Intensify Challenges in Identity and Access Management
The rapid rise of AI agents performing complex tasks independently is pushing security teams to reassess their strategies for AI identity management. As these autonomous systems become more common, experts caution that traditional identity and access management (IAM) frameworks may not be enough to address the unique risks introduced by non-human digital entities.
Unlike earlier automation tools, AI agents can make decisions, initiate workflows, and interact with various services without constant human oversight. This evolution, according to industry analysts and IT leaders, significantly complicates efforts to monitor, authorize, and control access within enterprise environments. The stakes are high: improperly managed AI agents could inadvertently expose sensitive data, propagate errors at scale, or fall prey to malicious manipulation.
“The nature of identity is changing fast,” said Jim Mercer, research vice president of DevOps and DevSecOps at IDC. “Now we have to manage machines and agents with as much rigor as we do with human identities, if not more.”
The recent wave of generative AI models, such as ChatGPT and its peers, has accelerated the adoption of autonomous agents that can execute tasks across email, documents, codebases, and customer service systems. These agents can compose emails, retrieve data, modify records, or escalate issues with minimal instruction. But while productivity gains are evident, the security implications are only beginning to be understood.
Industry insiders emphasize that identity and access management systems must evolve quickly to address this new reality. In particular, organizations must ensure that AI agents have clearly defined roles, limited privileges, and robust authentication methods. Just as human users are governed by the principle of least privilege—only accessing the resources necessary for their roles—AI agents must also operate under strict constraints.
“Most of the IAM tools today were built with humans in mind,” said Andras Cser, a vice president and principal analyst at Forrester Research. “We’re now moving toward a world where these agents are acting semi-autonomously. You need a new layer of identity governance that understands how to evaluate the context, behavior, and intentions of these agents.”
Traditional IAM systems typically rely on role-based or attribute-based access controls. However, experts suggest these methods may fall short when applied to AI agents, which do not follow conventional employment structures or organizational hierarchies. Instead, companies must look toward behavior-based analytics and real-time monitoring to detect anomalies in how agents interact with systems.
Security leaders also point to the need for more granular oversight of how AI agents are provisioned, what credentials they use, and how they are decommissioned. Unlike human employees who have start and end dates, AI agents can be created and replicated in seconds, making it difficult to maintain a clean and auditable identity inventory.
“If you spin up 500 agents overnight and forget to delete them, that’s 500 potential attack surfaces,” said Mercer. “We’re seeing a scenario where identity sprawl becomes even more of a nightmare than it already is.”
Some vendors have begun introducing new IAM features tailored to AI workloads. These include automated identity verification for agents, contextual access policies based on machine behavior, and centralized dashboards for monitoring both human and non-human entities. But widespread adoption is still in its early stages, and many organizations remain unprepared.
A key concern among CISOs is how to balance the operational benefits of AI agents with the growing risk landscape. With AI systems increasingly integrated into critical workflows—such as finance, HR, and cybersecurity—any compromise in agent behavior could result in cascading failures or unauthorized transactions.
“The attack surface is expanding, and it’s doing so at machine speed,” said Cser. “Security teams need to move fast to catch up. Otherwise, the tools meant to increase efficiency could become liabilities.”
As enterprises race to deploy generative AI across departments, IAM policies must be revisited with urgency. Experts advise organizations to begin inventorying all AI agents currently in use, identifying the data they can access, and implementing safeguards to ensure accountability and compliance.
“The future of identity is no longer just about people,” said Mercer. “It’s about every digital thing that acts on your behalf. And if you’re not securing those things, you’re already behind.”
