IAM programs rely on a few basic assumptions that have made sense for a long time. Identities are people. Authentication happens when someone enters a password, while access is granted based on a role or job title. Somewhere, there’s a directory that serves as a source of truth. Shadow machines break all of these assumptions. They come and go quickly. A script creates a service account in the middle of the night, it runs a task, and a few days later, it disappears. There’s no onboarding request, manager sign-off, login screen, or MFA either, just credentials baked into environment variables or configuration files. These identities aren’t stored in one tidy system, either; they’re spread across cloud platforms and often a slew of SaaS tools the business may not even realize it’s using (the connection between shadow identities and shadow IT is more visible than ever). Who owns them? Is it the developer who wrote the script? The platform team? The app owner? Usually, nobody knows, or everyone assumes someone else is handling it. Lifecycles become moot because some of these identities exist for a few hours, while others have been running for years, and nobody remembers why. More often than not, these identities remain active long after their original purpose has been fulfilled. What is often overlooked is that non-human identities are a connective tissue that holds supply chains together, acting on behalf of vendors, platforms, and AI systems. These are identities that are trusted and deeply embedded in systems, yet rarely visible at a business or governance level. Unfortunately, a compromised machine identity can move laterally across systems, access sensitive data, or trigger automated processes at scale. This shouldn’t be seen as a failure on the part of IAM teams or security programs, as these were designed for a different reality. It is rather a mismatch between the design assumptions of traditional IAM and the realities of modern systems. Treating machine identities as a special case of human identity has reached its limits. Without visibility into the machine identities in your business, including what they can access and how they are used, risk management becomes a matter of guesswork.