Machine identities now dwarf human ones by a staggering 82 to 1. This imbalance, confirmed by CyberArk research in late 2025, is overwhelming legacy Identity and Access Management (IAM) systems. These systems, designed for human users, struggle to manage the explosion of AI agents and other machine identities.

The surge is driven by rapid AI adoption. Microsoft Copilot Studio users created over 1 million AI agents in a single quarter of 2025, a 130% increase. These AI agents don't just authenticate; they act, creating new security risks.

Enterprises are scrambling to adapt. ServiceNow invested heavily in security acquisitions in 2025, signaling a shift towards identity-centric AI risk management. Gartner predicts that by 2028, 25% of enterprise breaches will originate from AI agent abuse.

Traditional IAM architectures are failing. Cloud IAM is often too slow, and security reviews don't align with AI agent workflows. This forces builders to prioritize speed, leading to shadow agents and over-permissioned service accounts.

The future demands a new approach to IAM. Experts believe identity, not models, must become the control plane for enterprise AI risk. The industry now faces the challenge of building IAM systems that can effectively govern the growing population of AI agents.