Machine identities are rapidly outnumbering humans in today’s digital landscape, with AI agents taking the lead as the fastest-growing and least-governed class of machine identities. These agents not only authenticate but also act, posing a significant challenge to traditional identity and access management (IAM) systems designed for human users.
Research from CyberArk and Gartner confirms the exponential growth of machine identities, with Microsoft reporting a substantial increase in the creation of AI agents by Copilot Studio users. As a result, Gartner predicts that a quarter of enterprise breaches by 2028 will be attributed to AI agent abuse.
Legacy IAM architectures are struggling to keep up with the scale and complexity of machine identities, leading to the creation of shadow agents and over-permissioned service accounts. Traditional IAM approaches, meant for human users, are ill-equipped to handle the unique requirements of machines, such as devices and workloads.
The governance gap is glaring, as organizations continue to define only human identities as “privileged users,” leaving machine identities with higher rates of sensitive access. The lack of visibility into machine identities poses a significant security risk, with orphaned credentials and abandoned automation workflows becoming prime targets for cyber attackers.
The emergence of agentic AI further complicates the identity management landscape, introducing a category of machine identity that legacy systems were not designed to handle. Gartner highlights the importance of dynamic service identities, which are ephemeral, tightly scoped, and policy-driven credentials that reduce the attack surface.
To address these challenges, security and AI builders must collaborate to implement just-in-time access, zero standing privileges, and auditable delegation chains for machine identities. Continuous monitoring, posture management, and agent lifecycle management are essential components of a robust machine identity strategy.
In 2026, the gap between what AI builders deploy and what security teams can govern is expected to widen, with organizations facing increasing pressure to adapt their IAM strategies to accommodate the proliferation of machine identities. Embracing dynamic service identities and unified platforms over point solutions will be key to mitigating the risks associated with machine identity attacks.
Ultimately, organizations must recognize that traditional perimeter-based IAM architectures are no longer sufficient to secure their digital assets in the face of machine-on-machine attacks. By proactively addressing the challenges posed by machine identities, organizations can strengthen their security posture and effectively combat the evolving threat landscape.
