We have a classification problem in enterprise IT, and it is quietly laying the groundwork for the next generation of insider security threats.
For decades, digital security teams have operated under a simple, two-sided framework: you either protect human users, or you secure software applications. Humans require onboarding, background checks, behavioural monitoring, and strict departure processes. Software applications require regular updates, security testing, and fixed, unchanging access configurations.
Now enter artificial intelligence agents
These are not standard software applications. Unlike traditional tools, AI agents do not wait for a human to click a button, type a command, or trigger a script. They operate continuously, make autonomous choices, access diverse data environments, and interact directly with both humans and external business systems. They do not just execute code; they make real business decisions.
By any logical definition, an AI agent is not an application. It is a digital employee
Yet, organisations still treat these highly privileged, autonomous entities like disposable pieces of software. They deploy them, configure them once, and walk away. This fundamental mismatch between what AI agents actually do and how we secure them is rapidly turning into one of the most severe business vulnerabilities of the decade.
If we are going to invite digital workers into our networks, we must stop treating them like simple software packages. We must start treating them like new hires. It is time to apply the exact same human resources lifecycle and checks and balances to AI agents as we do to our human staff: we must hire them, manage them, and fire them with the same security rigour.
Phase 1: “Hiring” an AI Agent
When you hire a human employee, you do not skip due diligence. You conduct background checks, verify credentials, call professional references, and strictly limit their initial access to sensitive files. No rational chief information security officer would hand a new junior recruit the keys to the entire corporate database on their first day.
Yet, when deploying an AI agent, this is exactly what happens. The technology industry has spent more than a decade preaching the gospel of a “never trust, always verify” approach to security, only to throw those principles out of the window the second a shiny new AI agent is introduced. In a rush to make these tools functional, teams routinely grant these digital agents broad, unchecked permissions, giving them read-and-write access to critical company databases.
To secure this initial hiring phase, organisations must run the equivalent of background checks on their digital recruits:
- Verify the supply chain: Where did the underlying technology model originate? Where did its training data come from? If you do not know what information went into the model, you cannot predict how it will behave.
- Define strict boundaries: A digital agent must be deployed with a hardcoded list of things it is absolutely never allowed to do, regardless of the instructions or prompts it receives from users.
- Enforce strict access limits: Treat the digital agent as an unverified external contractor. Grant only the bare minimum permissions required for its specific task. If a marketing agent only needs to read drafts, do not give it the technical ability to write directly to your content management system.
Without these foundational checks, you are onboarding a highly privileged insider with unknown biases, zero loyalty, and the potential to cause enormous organisational damage.
Phase 2: “Working with” an Artificial Intelligence Agent
Human employees are not blindly trusted after their first week. They are managed, they receive performance reviews, their access to systems is periodically audited, and managers look out for signs of unusual or erratic behaviour.
AI agents require the exact same continuous discipline, but they rarely get it. Instead, they are left to operate in an unmonitored black box.
Unlike static applications, AI agents are dynamic. They accumulate context, adapt to input, and evolve over time. They can also fail quietly and with absolute confidence. If a human employee starts making thousands of erratic, unauthorised decisions, someone in management notices within hours. A digital agent can make thousands of disastrous, compromised decisions in milliseconds before a human ever looks at the activity records.
To manage an AI agent effectively, organisations must treat them like active team members:
- Establish human ownership: Every single AI agent running on a company network must have a designated manager, a human owner responsible for its output, its access levels, and its ongoing behaviour.
- Audit the training curriculum: We expect digital agents to learn from new data, but who is feeding them this information? How are we validating its accuracy? Without continuous testing, incorrect data or biased inputs will quietly warp the agent’s behaviour.
- Monitor for unusual behaviour: Security teams must log agent actions and actively hunt for behavioural shifts. If an AI scheduling assistant suddenly attempts to search financial databases, it should trigger an immediate security alert.
When a compromised AI agent makes a catastrophic decision, telling a regulator or a board of directors that “the model did it” is not a defence. Legally and operationally, the responsibility stops with the human manager.
Phase 3: “Firing” an Artificial Intelligence Agent
When a human employee leaves a company, the departure process is swift and non-negotiable: building passes are confiscated, network accounts are disabled, and automated access links are revoked.
With AI agents, this departure process is practically non-existent.
When a project ends or a tool is replaced, the underlying agent is often abandoned, but its digital connections remain. Their credentials stay active, their security keys do not expire, and their links remain plugged directly into sensitive databases.
This is how unmonitored, forgotten AI tools escalate from a minor technology nuisance into an active security crisis. These abandoned tools become “ghost employees”, holding legitimate, highly privileged access credentials with absolutely zero human oversight. They represent a dream scenario for cybercriminals: pre-authorised, undetected, and unmonitored entry points into the heart of the corporate network. Because these credentials belong to non-human identities, they are notoriously difficult to spot during routine security audits.
If an AI agent’s project is discontinued, it must be formally fired:
- Maintain an active list: Security teams must maintain a centralised, real-time list of all active AI agents, their business purposes, and their human sponsors.
- Enforce hard expiry dates: All digital credentials and access keys assigned to AI agents must have strict, short-term expiration dates that require manual renewal.
- Execute clean departures: When an agent is retired, technical teams must run a dedicated checklist to ensure every software connection is severed, every password is deleted, and its access is permanently blocked.
The New Security Mandate
AI agents are transforming business productivity, but our security mindsets have not kept pace. If we continue to treat autonomous digital workers like passive, static software applications, we are voluntarily inviting high-risk, unvetted insiders into our most sensitive digital spaces.
It is time to close the gap. If an AI agent has the power to act like an employee, it is time to start securing it like one.
