AI 投資増でも生産性向上せず、レイオフが原因か

Business leaders and investors face a deepening paradox: Companies are pouring more money into artificial intelligence than ever, but they’re not seeing the gains in productivity that they expect.

Even CEOs are starting to admit this disconnect. One Atlanta Federal Reserve study found that about 90% of executives believe AI has not yet boosted productivity at their companies. Other evidence suggests that the broader increase in productivity seen since 2021 is more likely due to remote work or factors other than AI, like downsizing in sectors such as technology.

I study how technology is changing the way businesses operate, and the research I’ve conducted with colleagues offers an important explanation for why these expected gains don’t materialize: AI-driven layoffs and the resulting job insecurity are actively destroying the very conditions needed for AI to make workers more efficient. In fact, these job cuts damage employee sentiment toward AI – which is one of the strongest predictors of firm productivity when AI is used.

Managers and investors should take note. Laying off employees in the name of AI investment is a self-defeating strategy that offsets any expected productivity increase.

When layoffs are the strategy

U.S. companies have poured billions of dollars into AI adoption in the hope of goosing productivity. But our research suggests that managers should treat the AI hype with caution.

My colleagues and I analyzed millions of job satisfaction reviews and thousands of reports of corporate financial performance, as well as hundreds of AI investments and layoff announcements made by U.S. public companies over the past five years. We discovered a clear pattern: As the frequency of AI investment announcements rises, so too do announcements of job cuts caused by AI.

This correlation is unlikely to be coincidental. Instead, it reflects a corporate strategy that sees workforce reduction as an integral part of their AI strategy.

Managers at publicly traded firms typically make decisions based on whether a new investment improves short-term profitability and share price. So after investing heavily in AI, managers face pressure to show a strong financial return. The expectation is that if AI makes employees more efficient, the company will need fewer of them to complete the same work.

As a result, a quick way for managers to help businesses realize that anticipated return is by cutting headcount and lowering labor costs. Some of the companies we studied even started to lay off employees before pouring money into AI, as a way to free up capital for future AI investments.

Managers expect that both AI investment and job cuts will enhance the company’s value. Yet when we examined stock market reactions to these layoff announcements, the average return was close to zero. This is in line with our earlier research that showed proclamations of AI investment don’t consistently boost a company’s share price.

That said, there are some companies, such as the financial tech platform Block, that saw stock prices jump on the news it would trim staff due to AI. But overall, the market reaction was negative or close to zero for more than half of these events.

Such a muted response suggests that these decisions carry significant hidden costs that undermine the gains of the AI adoption.

Why employee sentiment matters

We found that one of the biggest of these hidden costs is that it makes employees fear for their jobs. On one hand, workers are at the center of this AI revolution and must adopt AI in their daily routines to improve their efficiency. On the other hand, AI is threatening their careers and job security.

To see how employees perceive and react to AI adoption, we analyzed millions of employee-satisfaction reviews on the workplace review site Glassdoor.com. By identifying and analyzing AI-related comments, we found them to be much more negative than the overall tone of employee reviews.

This negativity reflects widespread concerns over corporate AI adoption and anti-AI sentiment among workers. At the same time, there’s a strong association between employee sentiment toward AI and firm productivity based on the employer’s financial information. This suggests that anti-AI sentiment among workers actually lowers productivity and offsets the potential efficiency gains caused by AI.

To uncover what drives this hostility, we took a close look at employee reviews. Along with fears over losing their jobs due to AI, they cited the lack of appropriate training, few chances to upgrade skills, and poor corporate AI leadership, as well as doubts over whether AI actually improves productivity. Among those topics, comments about job security concerns were the most critical by far.

To confirm this negative effect of these fears, we then tested how AI sentiment changes when companies announce layoffs due to AI – and discovered a sharp decline in sentiment. In effect, many employees are resisting AI because they have watched their colleagues lose jobs to it or fear they will be next. This is in line with a recent Reuters/Ipsos poll that found half of Americans fear AI could put someone in their household out of work.

We found a different picture when it comes to management’s sentiment. We analyzed the tone of management discussions related to AI in about 10,000 earnings-call transcripts and found it to be consistently optimistic. At the same time, that sunny outlook bore no significant relationship to productivity outcomes.

In short, employee sentiment plays a more important role in unlocking the benefit of AI than any optimism among managers.

A guide for managers

Our findings should deliver a clear and urgent message to managers and investors: Using AI to justify cutting jobs is, in our view, a strategic miscalculation that cuts against the benefits of AI. For too many companies, riding the AI wave has become an AI hunger game that spreads fear rather than engagement.

Because employees are encouraged to use AI tools while their companies cite those same innovations as grounds for cuts, the touted benefits of AI often work against themselves. And companies find themselves left with a demoralized workforce and an underwhelming return on AI investment.

What businesses need to understand, I believe, is that managing how employees feel is key to unlocking AI’s benefits. In turn, that means creating an environment where workers feel that AI is working with them, not against them. Managers can do so by making a genuine commitment to share AI gains with their employees – investing in skills and expanding opportunity rather than simply laying them off.

Companies that take this approach and understand the great cost of job insecurity are the ones most likely to profit from their AI investment.