AI is rapidly changing from research by technology organizations to one that they are expected to use.
In many businesses, it is already part of daily operations, built into the tools that employees rely on and embedded within back-end systems.
What makes this era different is not just the speed at which AI is being adopted, but the degree to which it is becoming fundamental to the way employees work.
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There are many reasons for optimism. A recent study by KPMG found that among the 85% of organizations that have already integrated AI into their operations, productivity increased by an average of 35% following the introduction of AI agents into the workplace.
Teams open up new opportunities to speed up workflow, automate repetitive tasks, and uncover more insights that took a long time to uncover.
However, as AI becomes more central to the entire business, organizations must take a proactive approach to its management.
This is especially true when it comes to keeping identities secure, where decisions made today will determine how safely AI can scale in the future.
Protecting AI workers
So far, most of the discussion has focused on humans using AI. The flight attendants and pilots who sit next to the crew are grabbing the headlines, and for good reason. They are changing the way people write content, develop code, analyze data, and communicate with others. But that’s only part of the story.
A peaceful transition is underway where AI no longer just supports the workforce, but becomes a distinct part of it. We are in the early stages of autonomous AI agents that take on tasks independently, access applications, pull data, and make decisions with little or no human involvement.
While it’s tempting to see them as the next evolution of assistants, they’re something very different. These agents operate as independent actors within the environment and must use their own credentials and permissions, meaning they behave more like digital workers than tools.
This change is important because many organizations still treat these agents as software, as they take on responsibilities that look like human work. For example, many AI agents take the easy way out and ask the human to reuse existing credentials and permissions.
Why identity systems are playing catch-up
For decades, identity and access management (IAM) has been built around a simple assumption: the primary user is the human.
Even when organizations expand IAM to include service accounts and machine identities, those identities are tied to predictable systems that perform small, repetitive tasks.
Independent agents disrupt that model. They are adaptable, perform tasks in flexible and non-standard ways, operate at machine speed, and can affect more systems than any single task.
Despite this, many places are trying to squeeze themselves into structures that were never designed for independent, decision-making digital workers.
The latest 2025 data and AI security research report shows that only 16% of organizations treat AI as an identity category with dedicated policies.
The result is a growing gap between how these agents behave and how their identities are managed, creating blind spots that attackers are ready to exploit.
There is no HR system for AI
That gap starts when the organization tries to onboard an independent agent. When a new employee joins, HR software initiates identity creation, roles are assigned, access is granted, and ownership is clear. There is a record of who a person is, what they are responsible for, and who is in charge of them.
Independent agents come with none of that structure. They are created by developers, embedded in workflows, or introduced through new platforms, often without centralized visibility or consistent process. There is no AI HR system, no automated manager, and no guarantee that anyone is responsible for what that agent can achieve or do.
This is where ownership governance must improve. Organizations need to find these agents, register them, and give them a unique identity that matches the corporate identity.
Every independent agent should have a clear owner who understands why it exists, what it is meant to do, and what programs it should affect. Without that foundation, it becomes difficult to answer even basic questions about how many agents there are, who owns them, and whether their reach is still appropriate.
Considering estimates that almost 3 out of 4 companies plan to use agent AI in the next two years, and 1 out of 5 have a mature management model for these private companies -– according to Deloitte––these challenges are only set to increase.
A challenge to dominate at machine speed
The ride is just the beginning. Once the agents are in the environment, the real difficulty lies in controlling what they can do and when. It’s easy to focus on getting models or code, but governance is ultimately about managing ownership and rights in line with business purpose.
If an agent can act on behalf of an organization, their identity should be treated as strictly as that of a human employee. In many cases, it must be governed more tightly, as AI agents operate automatically, continuously, and break the boundaries of trust at machine speed and scale. That makes privileged access more dangerous.
AI has radically changed the paradigm of identity protection. Privileged actions are increasingly performed across hybrid ecosystems — from on-prem and cloud to database and SaaS — and organizations have lost the centralized access control they once relied on.
Organizations will no longer depend on static, always-on access. They must switch to flexible and ephemeral models. Short-term authentication, timely access, limited permissions, and continuous monitoring help ensure that agents can complete certain tasks during execution without holding more power than they need.
This type of approach supports innovation while reducing the radius of the explosion if something goes wrong.
Managing outsourcing risk
The most important thing is that the ride and the rule does not work. When an individual leaves the organization, access is revoked and accounts are closed. With independent agents, there is often no clear life-cycle event that triggers uniform purification.
An agent may quietly retire, be replaced, or simply be forgotten. If no one is watching, that identity can always be there and no longer needed. An unmanaged agent with long-lasting privileges becomes an easy target and a hidden entry point for sensitive systems.
Extending detection processes and lifecycles to identify inactive or orphan agents, and remove them quickly, is essential to keeping the environment clean and reducing long-term risks.
Human oversight is still key
Even in the world of private programs, people are always in the middle. Every agent must ultimately be bound to the person or team responsible for his conduct. Sensitive actions should require human approval. Work must be clearly visible and auditable so teams understand not only what happened, but why.
Independence does not eliminate accountability. If anything, it raises the bar for oversight, because the speed and scale of machine-driven work leaves little room for error. Organizations that build clear identity and human-centered controls into their identity systems will be in the best position to gain trust in how they use AI.
IAM for permanent employees
The future of work isn’t just about humans using AI. It’s about a blended workforce where humans and native AI agents work together, each contributing to the way the organization works. With 62% of organizations already experimenting with AI agents, that future is quickly becoming a reality.
Those who succeed will move beyond viewing private agents as background software and begin treating them as digital workers. They will establish HR-friendly onboarding processes, implement governance structures that can keep pace with machine speed operations, and implement exit processes that ensure no access points are left exposed.
Now is the time to get ready for identity and access systems for a seamless workforce, and acknowledge that in the era of AI autonomy, identity and authorization go beyond humans alone.
Read our list of the best employee management software.
