How to manage the employees that dont clock in

Date:
Mon, 06 Apr 2026 09:06:52 +0000

Description:
AI agents are joining the workforce, so how should organizations manage and secure them?

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now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Explore An account already exists for this email address, please log in. Subscribe to our newsletter AI is rapidly shifting from a technology organizations experiment with to one theyre expected to use.

In many businesses, its already part of day-to-day operations, built into the tools employees depend on and embedded within background systems. What sets this moment apart isnt only the speed at which AI is being adopted, but the extent to which its becoming fundamental to how employees work. Article continues below You may like The leadership dilemma: Governing the Agentic AI workforce How businesses can stop their AI agents from running amok AI isnt just a focus for your CEO now heres why everyone from your CISO to your security guard should be getting involved

Theres plenty of reason for optimism. A recent KPMG study found that among
the 85% of organizations already integrating AI into their operations, productivity has increased by an average of 35% following the introduction of AI agents into the workforce. David McNeely Social Links Navigation

CTO, Delinea. Teams are unlocking new opportunities to accelerate workflows, automate repetitive tasks, and surface insights that previously took far longer to uncover.

However, as AI becomes more deeply embedded across the enterprise, organizations must take a more intentional approach to its management .

This is especially true when it comes to keeping identities secure, where decisions made today will determine how securely AI can scale in the future. Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over. Securing the AI workforce So far, most of the conversation has focused on humans using AI. Assistants and copilots that sit alongside employees have dominated headlines, and for good reason. They are changing how people writecontent,developcode, analyze data, and communicatewith others.But that is only part of the story.

A quieter shift is underway where AI is no longer just supporting theworkforce,butbecominga distinctpart of it.Werein theearly stagesof autonomous AI agentstakingon tasks independently, accessing applications, pulling data, and making decisions with little or no human involvement.

While it is tempting to see themsimplyas the next evolution of assistants, they are something fundamentally different. These agentsoperateas independent actors inside the environmentand should be usingtheir own credentials and permissions, which means they behave far more like digital employees than tools. What to read next Your employees are using AI, whether you like it or not - but are they using AI securely? From Black Box to White Box: why AI agents shouldnt be a mystery to enterprises The mobile app traffic your security team can't see and AI agents are generating it

This shift matters because most organizations are still treating these agents like software , even as they take on responsibilities that look a lot like human work. For example, many AI agents take the easy way out and ask the human to reuse their existing credentials and permissions. Why identity systems are playing catch up For decades, identity and access management(IAM)has been designed around a simple assumption: the primary user is human.

Even when organizations extended IAM to cover service accounts and machine identities, those identities were tied to predictable systems performing narrow, repetitive tasks.

Autonomous agentsdisruptthat model. They are adaptive,work through tasks in flexible andnon-uniformways,operateat machine speed, and may touch far more systems than any single employee ever would.

Despite this,many environments are trying to squeeze them into frameworks
that were never built for independent, decision-making digital workers.

A recent2025 data and AI security research reportshows that only 16% of organizations treat AI as its own identity class with dedicated policies.

The result is a growing gap between how these agentsbehave and how their identity management , creating blind spots that attackersareready to exploit. There is no HR system for AI That gapbeginsthe moment an organization tries
to onboard an autonomous agent. When a new employee joins, HR software triggers identitycreation,roles are assigned, access is provisioned, and ownership is clear. There is a record of who the person is, what theyare responsible for, and who manages them.

Autonomous agents arrive with none of that structure. They arecreatedby developers , embedded into workflows, or introduced through new platforms, often without any central visibility or consistent process. There is no HR system for AI, no default manager, and no guarantee that anyone is
accountable for what that agent can access or do.

This is where identity governancemustevolve. Organizationsneed todiscover these agents, register them, and give them distinct identities tied to clear business ownership.

Every autonomous agent should have aclear ownerwho understands why it exists, what it is meant to do, and which systems it should touch. Without that foundation, it becomes difficult to answer even basic questions about how
many agents exist, whoownsthem, and whether their access is still justified.

Given estimationsthatnearly 3in 4 companies plan to deploy agentic AI in the next two years, withjust 1 in 5 having a mature governance model for these autonomous agents accordingtoDeloittethese challenges are only set to
expand. The challenge of governance at machine speed Onboarding is only the beginning. Once agents are in the environment, the realdifficulty liesingoverning what they can doand when.Itseasy to focus on securing models or code, but governance isultimately aboutmanaging identities and privileges in line with business intent.

If an agent can act on behalf of the organization, its identity should be governedwiththe same rigoras a human employee . In many cases, it should be governed even more tightly,asAIagentsoperateautonomously,continuously, and across trust boundaries at machine speed and scale.That makes over-privileged access particularly dangerous.

AI has fundamentally altered the identity security paradigm. Privileged actions are being increasingly performedacross hybrid ecosystems from
on-prem and cloud to databases and SaaS and organizations have lost the centralized point of control over privileged access they once relied on.

Organizations can no longerdependonstanding,always-onaccess. Theymust shifttowarddynamicandephemeralmodels. Short-lived credentials,just-in-time access,tightly scoped permissions, and continuous monitoring help ensure agents can complete specific tasksat the momentof actionwithout holding more power than they need.

This kind of approach supports innovation while reducing the blast radius if something goes wrong. Managing offboarding risks Just as important as onboarding and governance is offboarding. When a human leaves the organisation, access is revoked and accounts are closed. With autonomous agents, there is often no clear lifecycle event that triggers that same cleanup.

An agent maybe retiredquietly, replaced by something new, or simply
forgotten. If no one iswatching,that identity can remain in place with access it no longer needs. An unmanaged agent with lingering privileges becomes an easytargetand a hidden entry point into critical systems.

Extending discovery and lifecycle processes toidentifyidle ororphaned agents, and removing them promptly, is essential to keeping the environment clean and reducing long-term risk. Human oversight is still key Even in a world of autonomous systems, humansremaincentral. Every agent shouldultimately betied back to a person or team responsible foritsbehaviour. Sensitive actions
should require human approval. Activity should beclearlyvisible
andauditableso teams can understand not just what happened, but why.

Autonomy does not remove accountability. If anything, it raises the bar for oversight, because the pace and scale of machine-driven activity leave less room for error. Organizations that build clear ownership and
human-in-the-loop controls into their identity programs will be far better positioned to earn trust in how they use AI. IAM for an always-on workforce The future of work isnt simply about humans using AI. Its about a blended workforce in which people and AI-native agents work alongside one another, each contributing to how the organization operates. With 62% of organizations already experimenting with AI agents, that future is rapidly becoming
reality.

Those that thrive will move beyond viewing autonomous agents as background software and begin managing them as digital employees. Theyll establish onboarding processes aligned with HR, implement governance frameworks that
can keep pace with machine-speed operations, and enforce offboarding
practices that ensure no access points are left exposed.

Now is the time to ready identity and access programs for a workforce that doesnt clock in, and to acknowledge that in the era of autonomous AI,
identity and authorization extend far beyond people alone. Read our list of the best employee management software .



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