Leaders shouldn't toss around the 'AI' buzzword in layoffs. Here's why

"Layoffs used to be something that made a company's stock tank. But after Block announced layoffs recently, its stock went up. And they weren't the only ones: Snap did the same thing a few months earlier, as did Meta and Amazon. The common thread? They all cited AI as their reason for cuts. For CEOs staring down investor pressure, the playbook has become clear: invoke AI, slash headcount, and watch the ticker go up."

"A recent Goldman Sachs survey found that only 11% of clients were reportedly cutting jobs due to AI, while LinkedIn's hiring data signals that AI isn't directly leading to the hiring slowdown... yet. Some of the cuts we're watching this year are mostly about overhiring in 2021 and 2022, a cooling economy, softer consumer demand, and product bets that haven't paid off. But those reasons don't sound all that glamorous on an earnings call; AI does."

"Pointing to AI makes a better blog post. Or it at least doesn't make you seem as much the bad guy who just wants to cut people for cost-effectiveness. It's hard to tell today where AI is the root cause of layoffs and where it's basically a nice narrative wrapper."

"Having personally experienced a layoff, I know how painful and disruptive an involuntary exit can be. And, as a CEO who reports to a board every quarter, I still have to make hard calls like any executive. But how you make them and what you say about them is the part that matters. With that in mind, this is what leaders need to keep in mi"

Several companies have announced layoffs while citing AI, and their stock prices rose afterward. This pattern suggests a new investor-facing playbook: attribute workforce reductions to AI and expect a positive market reaction. Evidence indicates AI may not be the primary driver of most layoffs, with surveys showing a small share of clients cutting jobs due to AI and hiring data suggesting AI is not directly causing hiring slowdowns. Other factors include overhiring during 2021–2022, economic cooling, weaker consumer demand, and product bets that failed to deliver. Leaders are cautioned to avoid using AI as a convenient narrative wrapper without examining underlying causes and consequences.

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