During a recent interview on CNBC’s Mad Money at GTC 2026, Jim Cramer asked Jensen Huang, CEO of NVIDIA, why companies keep announcing layoffs while crediting AI as the reason. Huang’s response was blunt:

“For companies with imagination, you will do more with more. For companies where the leadership is just out of ideas, they have nothing else to do. They have no reason to imagine greater than they are. When they have more capability, they don’t do more.”

He’s not talking about technology. He’s talking about leadership.

Let me be clear: companies lay people off for all kinds of legitimate reasons. Market shifts, restructuring, financial pressure, strategic pivots, poor performance. There are probably a dozen or more valid reasons a company might need to reduce headcount. That’s not what this article is about.

This is about the growing trend of CEOs pointing at AI and saying, “This is why we’re cutting people.” According to one industry compilation, more than 100,000 employees were impacted in 2025 by layoffs where AI or automation was cited as a driver. The trend appears to be continuing in 2026. And I’d argue that in most of these cases, AI is either the excuse, the misunderstanding, or the tell that imagination ran out.

Here are five reasons why AI should almost never be your justification for laying people off.

1. There was never enough capacity to begin with

I’ve spent 25 years leading engineering organizations. Not once have I worked at a company where the backlog was empty. Product management is always frustrated. Legal wants compliance work done yesterday. Security has a list of critical gaps nobody’s getting to. Every department thinks engineering isn’t moving fast enough.

So AI comes along and increases output for certain tasks. That should be the best news a product organization has ever heard. Instead, some leaders look at that gain and say, “Great, we can do the same work with fewer people.” That tells you everything about where the ambition stops.

2. Your company’s value is in people, not tools

Even if AI becomes better than most engineers at producing code quickly, it still doesn’t know why your system works the way it does. The regulatory constraint that shaped an API. The customer behavior that drove a UX decision. The safety requirement behind a seemingly over-engineered architecture. That context lives in people, built over years inside a specific system, market, and regulatory environment. Fire them and you don’t just lose headcount. You lose the map to your own codebase.

3. The data already suggests you’ll regret it

This isn’t theoretical. Orgvue reported that among business leaders who made redundancies because of AI, 55% said they made the wrong decisions. Gartner predicts that by 2027, half of companies that attributed headcount reductions to AI will rehire for similar functions. And Klarna, after loudly touting AI’s customer-service gains, resumed human hiring after concluding customers still need access to real people and that the company had gone too far in prioritizing automation.

These aren’t edge cases. They’re signals that replacing people is often a much messier decision than the AI narrative suggests.

4. You’re betting on capabilities that don’t exist yet

A lot of companies are making workforce decisions based not on what AI reliably does today, but on what they hope it will do soon. That’s a dangerous way to run an organization. In many environments, the tools still need human review, human context, and human judgment to produce usable outcomes at scale.

And when the technology fails to deliver, those roles don’t always come back in the same form. Sometimes they’re quietly refilled later. Sometimes they’re shifted to contractors or lower-cost markets. Sometimes the company just absorbs the damage in slower delivery, lower quality, and institutional confusion. So for many companies, “AI layoffs” aren’t really about AI at all. They’re cost-cutting dressed up as innovation.

5. It tells everyone exactly who you are as a leader

If your response to the most powerful productivity multiplier in a generation is to shrink, you’re telling the market, your employees, and your customers that you had no ambition beyond your current output.

The way I see it, there are only three explanations for using AI to justify layoffs: you lack the imagination Jensen is talking about, you lack honest information about where AI actually delivers value in your organization, or you’re cynically using AI as convenient cover for cuts you wanted to make regardless. None of those are technology problems. They’re all leadership problems.

The bottom line

None of this means AI will never eliminate roles. In some workflows, it will. But that is different from using AI as a blanket justification for broad layoffs before the work, the systems, and the customer outcomes have actually changed.

AI is a tool. And the companies that win with it won’t be the ones that used it to cut headcount first. They’ll be the ones that kept their workforce focused on higher-value problems and pointed AI at everything they couldn’t get to before. They’ll release new products faster. They’ll clear the backlog that’s been piling up for years. They’ll raise quality and responsiveness materially. They’ll enter markets they never had the capacity to compete in.

So can we do more with more? Absolutely. But only if you have the imagination to see it.