AI interns in the office: Preparing to work with digital employees

Kim Byoung-pil

The author is a professor of technology management at KAIST.

The office environment is changing rapidly. AI is now drafting business plans, designing marketing campaigns and even handling customer service and bookkeeping. Such multitasking capabilities are particularly useful for small organizations, where the work force is often limited. Startups and small business owners are increasingly dividing work among AI systems, assigning them roles in sales, marketing, accounting and customer support.

Yet these digital employees also create serious security vulnerabilities. One example is OpenClaw, an open-source AI assistant released in November of last year that quickly attracted global attention. Cisco described it as a “security nightmare.” OpenClaw can delete files from a user’s computer and even run malicious software. The moment such tools are connected to a company’s internal network, the entire corporate security system may be exposed to risk.

That helps explain why many companies restrict the use of outside AI programs within their organizations. Without adequate control systems, it is difficult to allow AI to operate autonomously inside a company. At the same time, those restrictions can slow the development of AI capabilities. According to Cisco’s 2025 survey, only 8 percent of Korean companies were classified as “leaders” in AI readiness, below the global average of 13 percent.

Still, companies cannot simply block AI adoption while competitors use it to widen productivity gaps. The question is how to resolve this dilemma. One practical approach may be to treat AI like an intern or probationary employee.

When a new recruit first joins a company, every task is unfamiliar. Senior employees supervising the newcomer often struggle to decide what responsibilities to assign. Yet once entrusted with smaller jobs, probationary workers often prove capable. Today’s AI resembles that stage of development.

Managing AI so that it does not threaten corporate security is remarkably similar to establishing rules for supervising new employees. First, just as workers enter the office using identification cards, AI systems should also be given clear identities. Uber created a framework that assigns verifiable identities to internal AI systems and tracks the work they perform. In effect, the company issued digital employee IDs for AI.

Second, companies should not open all internal information to AI at once, just as probationary employees are not granted unrestricted access to all company resources. AI systems should operate in isolated environments with limited access to data. Their workspaces should remain separated from core company networks, and they should only be able to use authorized tools. The authority granted to AI should never exceed that of the human employee supervising it.

Third, there must be a control mechanism equivalent to managerial approval. A probationary employee may prepare a purchase order, but cannot place the order independently. Final approval still comes from a responsible manager. The same principle should apply to AI. Human oversight must remain embedded in important procedures.

Finally, just as probationary workers gain more important responsibilities as they build trust and accumulate positive evaluations, AI systems should gradually receive more autonomy as they prove reliable. Current AI technology is beginning to develop the ability to accumulate work experience independently. The recently introduced Hermes agent documents successful work processes and refers to them later when handling similar tasks.

Just as probationary employees can eventually become permanent staff members, companies that accumulate experience assigning work to AI and reviewing its results may gradually entrust it with more critical responsibilities. Greater AI capability alone, however, does not automatically accelerate adoption. Risks involving data leaks, malfunctions and auditing difficulties also increase alongside AI’s growing power.

For that reason, waiting until AI performance improves further before introducing it more broadly may prove to be a mistake. Companies that delay adoption are likely to lack practical management experience while competitors continue widening the gap.

What matters most is beginning now to prepare properly for working alongside AI. Organizations need systems for AI identity verification and authentication, isolated workspaces, behavioral records and human supervision. Only by assigning AI the role of a probationary employee can companies gradually move toward entrusting it with more responsible positions. The era of working alongside digital employees has already arrived. The challenge now is deciding what tasks to assign them, and under what rules and procedures. Preparation should begin before it is too late.

This article was originally written in Korean and translated by a bilingual reporter with the help of generative AI tools. It was then edited by a native English-speaking editor. All AI-assisted translations are reviewed and refined by our newsroom.