Half (50%) of security leaders reported security incidents or breaches linked to compromised machine identities in the last year, which led to delays in application launches (51%), outages impacting customer experience (44%) and unauthorized access to sensitive data or networks (43%).

Machine identities outnumber human identities by an overwhelming margin and continue to grow quickly. Seventy-nine percent of security leaders anticipate the number of machine identities in their organization to increase, by as much as 150% over the next year.

As AI systems become a growing target for cyberattacks, 81% of security leaders believe machine identity security will play a vital role in securing the future of AI. Seventy-nine percent say securing AI models from manipulation and theft means putting greater emphasis on the need for machine identity authentication and authorization.

While 92% of security leaders report some form of machine identity security program, many of these programs lack maturity. Respondents reveal the lack of a cohesive machine identity security strategy as their biggest concern (42%), followed by challenges adapting to shorter machine identity lifecycles (37%) and the possibility of adversaries exploiting stolen machine identities (37%).

Where multiple tools to secure machine identities exist within organizations, inefficiencies, risk and management challenges are created. For example, responsibilities for preventing machine identity-related compromises were found to be split among security (53%), development (28%) and platform (14%) teams.

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