One-Third of Companies That Cut Jobs for AI Are Hiring Those Roles Back

Nearly one-third of U.S. hiring managers whose organizations eliminated roles because of AI have since added some of those positions back. That figure, highlighted in a new Entrepreneur contributor analysis, captures the cost of the AI urgency trap: companies moving fast, then paying to reverse course.

The piece, which argues the business case for slowing down when everyone is rushing, lands as the pressure on leaders intensifies. Nearly two-thirds of CEOs say their boards are rushing AI transformation, according to the report. That pressure can push leaders to start projects before they understand what effective implementation actually requires.

The consequences aren't symmetric. Some decisions are easy to adjust later. Others create costs, dependencies and organizational complexity that take months or even years to unwind.

Why can't leaders slow down?

The author traces the problem to career formation. Most leaders begin as individual contributors, measured by output and results. They learn to solve problems quickly and seize opportunities, and consistency builds a reputation as a high performer.

That bias toward action works when a problem is straightforward. The equation changes when people, processes, technology, systems and information must all work together — which is precisely what AI transformation demands.

The report cites another figure: only two in five leaders say they reflect weekly. When the goal is minimizing wasted investments and unnecessary course corrections, leaders sometimes need to override urgency and make room to think.

The author writes from experience: "Over the course of my career, I've had to become much more comfortable saying, 'I don't know yet.'"

What does reflection actually look like?

The author describes a moment with a mentor, a former Navy SEAL, during a difficult business situation. The mentor asked one question: "Did anybody die?" Nobody had — which was the point. The question forced a separation between what felt urgent and what was genuinely important.

The piece offers several practical techniques:

• Open the aperture: ask what the issue is, how you got there, and what else needs attention.
• Use investor Charlie Munger's inversion technique — instead of asking how to succeed, ask "What would guarantee that this fails?"
• Take a "thinking espresso shot": a short, concentrated burst that interrupts doing and creates an aerial view of an issue.
• Step away as a team. Three or four times a year, the author's leadership group works on the business rather than in it.

Every one of those group sessions, the author notes, improved velocity on at least a few core issues — including some the team had wrestled with for months.

Where's the limit?

Reflection has a stopping point. "There is also a point at which reflection stops improving a decision and indecision starts holding the organization back," the author writes. The personal test: if returning to an issue, pressure-testing assumptions and actively trying to reach a different conclusion lands in the same place, it's time to move.

Does reflection pay off in numbers?

McKinsey research cited in the piece found that 30% of the most reflective leaders said their organizations could adapt quickly to changing circumstances, versus 17% of the least reflective leaders.

Reflection also helps separate activity from impact. A relatively small number of decisions drive a disproportionate share of results; the piece points to identifying that "vital 20%" rather than simply doing more.

As AI commoditizes access to similar tools and agents across companies, the differentiator becomes discernment — knowing which problems deserve those tools and when their output can be trusted.

The takeaway is blunt: the faster organizations can move, the more important it becomes to choose the right direction.