AI Agents in the Enterprise and Their Implications for Identity Security

The rapid advancement of Large Language Models (LLMs) and Generative AI (GenAI) is ushering in a new era of technology, where AI systems are no longer just tools but active participants in enterprise workflows. This shift is driven by Agentic AI—AI systems that can function autonomously, make decisions, retrieve real-time data, and execute complex actions across the enterprise environment. The two primary flavors of AI agents expected to see in enterprises are Enterprise-Managed AI Agents and Employee-Managed AI Agents, each with its benefits and risks. These agents promise tremendous productivity gains but also introduce significant identity security challenges that organizations must address proactively. To manage these risks, a robust identity security framework is critical, and organizations must determine a strategy for the "security" of AI agents quickly, which expands to one about "trust." How much capability and access are provided depends on how much trust is placed in the agent. Ultimately, the future of enterprise AI is both exciting and complex, requiring organizations to acknowledge the tremendous pull to adopt this technology and develop strategies for managing its risks.

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