Machine identities now dwarf human ones by a staggering 82 to 1. CyberArk's 2025 research confirmed this dramatic shift. Legacy Identity and Access Management (IAM) systems, designed for human users, are struggling to keep pace.
This imbalance poses a significant security risk. AI agents, the fastest-growing segment of machine identities, are often poorly governed. Microsoft Copilot Studio users created over 1 million AI agents in the last quarter alone, a 130% increase. These agents don't just authenticate; they act, making them prime targets for abuse. Gartner predicts 25% of enterprise breaches will stem from AI agent vulnerabilities by 2028.
The industry is responding. ServiceNow invested heavily in security acquisitions in 2025, signaling a move towards identity-centric AI risk management. However, developers often prioritize speed over security, leading to shadow agents and over-permissioned accounts. Current cloud IAM solutions and security review processes are too slow and cumbersome for the rapid deployment of AI agents.
Traditional IAM systems were built for a human-centric world. Active Directory, LDAP, and early PAM solutions weren't designed to manage the scale and complexity of modern machine identities.
The future requires a fundamental shift in how we approach identity management. Security teams must develop new strategies to govern AI agents and prevent breaches. The focus needs to shift from models to identity as the primary control plane for enterprise AI risk.
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