The Human-in-the-Loop Trap

Here is a test. If you left for a week starting tomorrow, would the AI-assisted work in your business keep moving, or would it quietly pile up waiting for your approval?

If it is the second, don’t dismay. It is a common problem, and it catches the most conscientious leaders first. Here’s how things usually unfold. An AI tool makes a mistake. A responsible leader starts reviewing more closely. The more they review, the more they find, because looking hard at anything reveals more to fix. Within weeks they are checking every output. The system runs at machine speed and the person runs at human speed, so the leader becomes the constraint in the very thing meant to relieve them.

Three forces drive this. The first is identity. Many managers advanced precisely because they were competent enough in their jobs to catch the errors other people missed, so stepping back feels like giving up the thing that made them valuable. The second is loss aversion, where one bad output outweighs fifty good ones. Third is that checking feels productive. It feels like control, even when it is slowing the business down.

Getting out of this rut is not about caring less. It is about separating oversight that manages real risk from oversight that manages your own discomfort. Ask what would happen if a particular output went out with an error in it. For a customer proposal, the answer may be serious. For an internal meeting summary, it may be nothing at all. Those two do not require the same level of review.

From there, extend trust in stages. Review everything for two weeks. If the system is working, then move to sampling one in five, then to reviewing only the exceptions that the system flags. Write down the categories where a person must always be in the loop. Let the others go.

One warning to keep in mind. Create a culture that welcomes staff that report AI’s errors. Be suspicious when a system runs flawlessly. A clean record over a long period is more likely to mean the feedback path is broken than that the work is flawless.

Source

The pattern described here is set out by Pascal Bornet in “The Supervision Trap: Why My Best Management Instincts Sabotaged My Own AI,” July 2026.