As organizations scale Artificial Intelligence (AI) and cloud automation, there is exponential growth in Non-Human Identities (NHIs), including bots, AI agents, service accounts and automation scripts. In fact, 51% of respondents in ConductorOne's 2025 Future of Identity Security Report said the security of NHIs is now just as important as that of human accounts. Yet, despite their presence in modern organizations, NHIs often operate outside the scope of traditional Identity and Access Management (IAM) systems.
As enterprises refine their strategies for handling Non-Human Identities (NHIs), Robotic Process Automation (RPA) has become a powerful tool for streamlining operations and enhancing security. However, since RPA bots have varying levels of access to sensitive information, enterprises must be prepared to mitigate a variety of challenges. In large organizations, bots are starting to outnumber human employees, and without proper identity lifecycle management, these bots increase security risks.
Identity security fabric (ISF) is a unified architectural framework that brings together disparate identity capabilities. Through ISF, identity governance and administration (IGA), access management (AM), privileged access management (PAM), and identity threat detection and response (ITDR) are all integrated into a single, cohesive control plane. Building on Gartner's definition of " identity fabric," identity security fabric takes a more proactive approach, securing all identity types (human, machine, and AI agents) across on-prem, hybrid, multi-cloud, and complex IT environments.
Every enterprise today runs on more than users. Behind the scenes, thousands of non-human identities, from service accounts to API tokens to AI agents, access systems, move data, and execute tasks around the clock. They're not new. But they're multiplying fast. And most weren't built with security in mind. Traditional identity tools assume intent, context, and ownership. Non-human identities have none of those.
In today's hyper-connected world, businesses are scaling faster than ever before. Cloud infrastructure, AI-driven automation, APIs, IoT ecosystems, and containerized applications have become the norm. This acceleration is reshaping digital environments into complex, interdependent systems where machines routinely interact with other machines, often without human oversight. But in this machine-first reality, most organizations are still looking in the wrong direction when it comes to securing their systems.
The rapid increased adoption of AI technologies, particularly LLMs, has significantly amplified the number of non-human identities across corporate clouds, leading to serious secrecy breaches.
