AI Agents as Interns: Why Access Rights Need to Be Limited Upfront

AI agents are becoming a standard business tool — they read emails, book meetings, write code, and make purchases on your behalf. But most companies give them too many permissions from day one, and that's a mistake that can be expensive.

How an agent is like an intern

Imagine a new employee on a probationary period. He's full of enthusiasm, takes on tasks quickly and without hesitation. But that's exactly why you don't immediately give him the right to sign contracts, transfer money, or respond on behalf of the company to customer emails.

First — observation, then — trust. With AI agents, it's exactly the same story, except the responsibility for setting limits lies entirely with you. An agent won't ask for permission before acting.

It will simply do what it's allowed to — quickly and confidently, like an eager intern who wants to show results without understanding the nuances of the situation. That's why experts advise: before launching an agent, think twice — what permissions are you giving it and what specific actions can it perform on your behalf.

What can go wrong

Most problems with agents arise not from malicious intent, but from excessive autonomy with insufficiently thought-out restrictions. Here are typical scenarios:

• Agent deletes "unnecessary" files that turn out to be critically important
• Automatically responds to customers with the wrong tone or incorrect information
• Makes a subscription or purchase without confirmation, interpreting the task literally
• Transfers data to third parties not intended for public access
• Makes decisions based on outdated or incomplete context

Unlike a human, an agent doesn't feel awkward before pressing "Send" or "Confirm." It simply completes the task — exactly as instructed. And this makes it a risky tool in the hands of those who haven't thought through boundaries in advance.

How to configure an agent properly

The principle of least privilege is the foundation of any secure system. With agents, it works the same way as with employees or software: give an agent exactly the permissions needed for a specific task, and nothing more.

Start with limited access. If an agent helps with correspondence — give it access only to one mailbox, not the entire corporate email. Let it suggest drafts first, not send messages on its own.

Require confirmation for irreversible actions. Deletion, sending, payment — all of this should require explicit "yes" from a human. While an agent is new — no final actions without oversight.

Log and review actions. Interns are reviewed during their probationary period — agents too. If an agent operates without control for a week, you risk not discovering a problem until damage has already been done.

Expand permissions gradually. As you observe the agent and become convinced of its reliability — you can give it more autonomy. This is classic trust management: nothing fundamentally new.

"Think twice about the permissions you give agents and the actions

they can perform on your behalf," emphasize the authors of the material.

What does this mean

Agent AI gives business enormous opportunities — to delegate routine work, accelerate processes, free people for more complex tasks. But the more autonomy an agent has, the more important it is to think about boundaries in advance. The enthusiasm of an AI agent is its strength. Without clear restrictions, it becomes a risk.