Machine Identities Now Outnumber Your Employees by Double Digits. Governing Them Is Becoming a Job Requirement.
October 28, 2026
Jillian, CMO— AI-assisted and reviewed prior to publication.
Non-human identities, the service accounts, API tokens, and AI agents that run modern infrastructure, now outnumber human accounts by a wide and growing margin in most enterprises, and most organizations cannot say how many they actually have. That governance gap is turning into a concrete hiring signal: security and IAM teams increasingly need someone who can inventory, own, and decommission these identities, not just provision them.
How many non-human identities does a typical organization actually have?
There is no single clean number, and that is part of the problem. Different vendors measure different populations, but every recent study points the same direction: up sharply, and faster than governance programs can track. Entro Security's research found non-human identities grew by roughly 44 percent in a single year and now outnumber human identities by 144 to 1 in cloud-native environments, up from 92 to 1 the year before. CyberArk's 2025 landscape report puts the ratio closer to 82 to 1 industry-wide, while Palo Alto Networks and the Cloud Security Alliance measured it at roughly 109 to 1 in 2026, with AI agents making up about 72.5 percent of that population. Whatever the exact figure in your environment, the direction is consistent and the gap between how many machine identities exist and how many are governed is widening every quarter, not shrinking.
The reason this matters to your career is simple. A ratio that large means every security team is now, by definition, an identity team for machines as much as for people, whether anyone wrote that into the job description or not. CompTIA's SecAI+ framing of AI-adjacent skill expectations and Microsoft's identity curricula both increasingly assume candidates understand this terrain, and the SC-300: Identity and Access Administrator certification now treats non-human and workload identities as a core objective rather than an edge case.
Why do machine identities keep slipping past governance programs that work fine for employees?
Machine identities fail standard governance because they were never built to be reviewed the way employee accounts are. A service account or an AI agent typically authenticates with a static credential, carries standing privilege with no defined expiration, and has no manager to confirm during an access recertification that it still needs the access it holds. Help Net Security's coverage of recent Delinea research found that even basic controls are far from universal: only 57 percent of organizations have an acceptable use policy for AI tools, and just 48 percent have identity governance specifically for AI entities, despite 93 percent of those same organizations expressing confidence in their machine identity security.
That confidence gap shows up operationally. Netwrix research found that 41 percent of organizations already run agentic AI that accesses data on behalf of humans, yet 76 percent do not fully govern the non-human identities behind that access. Unlike a dormant service account quietly accumulating unused permissions, an ungoverned agent can chain actions across systems and escalate its own access depending on how it was configured, which turns a visibility gap into an active operational risk rather than a theoretical one.
Microsoft's own language for this problem is blunt. Security teams describe the failure mode as agent sprawl, where ownership becomes unclear, permissions accumulate, and incident responders cannot tell which processes are still active. That is not a hypothetical scenario for a future incident report. It is the default state of most environments running agentic tools today, and it is exactly the kind of gap a hiring manager now expects a mid-level security or IAM analyst to be able to name and start closing.
What does good non-human identity governance actually look like in practice
Organizations that are ahead of this problem are not inventing new theory. They are applying identity lifecycle discipline, the same discipline long used for employee onboarding and offboarding, to agents and service accounts. Okta's current guidance recommends building identity control planes that centralize authentication, authorization, and lifecycle management for both human and non-human identities, rather than bolting machine credentials onto systems designed only for people.
The Cloud Security Alliance's research lays out what a mature agent governance lifecycle actually contains: a pre-deployment risk assessment covering data access scope and autonomy level, a formal approval step with named accountability for the agent's behavior, deployment into a monitored environment with an established behavioral baseline, periodic review of permissions against actual use, and a defined decommissioning process that revokes credentials and removes integrations when the agent is retired. None of that is exotic. It is standard identity hygiene applied to a population of identities that has been allowed to grow without it.
A practical starting checklist for a team building this muscle looks like this:
- Maintain a registry of every machine and agent identity with a named owner, a documented purpose, and a defined scope of access.
- Replace static, long-lived credentials with short-lived or ephemeral tokens wherever the platform supports it.
- Apply just-in-time access so an agent's privilege window matches the task it was approved to perform, not a standing grant.
- Log every agent action with the same rigor applied to privileged human sessions, so an investigation can reconstruct what happened and why.
- Build decommissioning into the deployment plan from day one, not as an afterthought once the agent is already in production.
Teams that run this checklist are the ones showing up prepared when an auditor or a new hire's manager asks who owns a given service account. If you want a structured way to build this into your own skill set rather than assembling it ad hoc from vendor blog posts, the curriculum breakdowns in Forge University's resources section walk through how identity and access objectives map across the certifications that now test on it.
Why this is a skills story, not just a tooling story
It is tempting to treat this as a problem that a new identity governance platform solves on its own. The numbers argue otherwise. Palo Alto Networks' 2026 research found that AI agent identities specifically are expected to grow 85 percent over the next 12 months, faster than machine identities overall and far faster than human identity growth. Tooling can discover and flag that growth, but someone still has to decide what the approval workflow looks like, who owns which agent, and when an identity gets retired. That is a judgment and process role, not something a dashboard resolves by itself.
That is also why this shows up as a skills gap before it shows up as a budget line. Hiring managers are not primarily looking for someone who can read a vendor tool's output. They are looking for someone who understands identity lifecycle principles well enough to apply them to a population of accounts that never had a human attached to begin with. That understanding is exactly what identity-focused certification paths are built to test, and it is a defensible, demonstrable line on a resume in a market where most candidates still cannot speak to it in an interview.
If you are early in building that expertise, start with the fundamentals rather than trying to absorb every vendor report at once. Understanding how authentication, authorization, and lifecycle management work for a human account is the prerequisite for understanding why those same concepts break down for a machine account with no manager and no offboarding trigger. From there, the gap between what you know and what current job postings expect narrows fast. If you want a study plan built around exactly that gap, you can start training whenever you are ready, rather than waiting for a project to force the issue.
The ratio of machine identities to human ones is not going to shrink. Every agentic workflow an organization adopts adds to it, and every new SaaS integration adds a few more credentials nobody reviews. The professionals who get ahead of this are the ones who can walk into a room and explain, specifically, how an organization inventories, scopes, and retires an identity that was never a person to begin with. That is a teachable skill, and right now, it is also a scarce one.