90% of Executives See No AI Benefits, Layoff Logic Spreads

Investment in artificial intelligence (AI) is increasing among U.S. companies, but the gap between productivity improvement and employment adjustments is widening. Many executives still believe that AI has not yet boosted their company's productivity, while some companies are using AI as a justification for organizational restructuring and layoffs.

Fortune reported on the 23rd, citing a contribution from Mark Ma, a professor at the University of Pittsburgh, and research from the Atlanta Federal Reserve Bank, that about 90% of executives believe AI has not yet increased their company's productivity. Professor Ma noted that while companies are investing more funds into AI, the expected productivity improvements are not clearly reflected in the numbers.

Professor Ma's research team analyzed over 21 million employee reviews from Glassdoor and about 10,000 executive call transcripts. They claimed that employee sentiment towards AI sharply deteriorated after announcements of AI-related layoffs, and that employee sentiment towards AI showed a strong positive correlation with company productivity.

On the other hand, the research team explained that optimistic statements from executives had no significant relationship with productivity. This suggests that the outcomes of AI implementation are more closely aligned with actual on-site acceptance than with executive messaging.

Corporate messaging is also at the center of the debate. There has been a pattern of simultaneous increases in announcements of AI investments and AI-related layoffs. The research team believes there is pressure to quickly demonstrate cost-saving effects through workforce reductions following AI implementation.

However, the stock market reaction to layoff announcements was, on average, close to zero, with more than half being negative or showing little movement, according to Fortune. This indicates that even if AI layoffs are presented to investors as a signal of efficiency, the market response has not consistently been favorable.

There were exceptions. Reuters reported that Block ($XYZ) saw its stock rise by more than 16% after announcing on February 26 that it would reduce its workforce by over 4,000 as part of an organizational restructuring to implement AI tools across its operations. Block stated that it expects to increase its adjusted operating profit margin from 20% in 2025 to 26% in 2026.

Brett Horn, a Morningstar analyst, commented, "The long-term impact of significantly reducing staff in anticipation of AI productivity improvements is uncertain." While cost reductions may help short-term profitability, there are concerns that organizational capabilities may decline during the technology adoption process.

The debate over AI-related layoffs is not limited to Block. Reuters reported that Amazon ($AMZN) eliminated some roles in its artificial general intelligence (AGI) organization on July 22. An Amazon spokesperson stated that while developing large AI models is a critical task, some roles were eliminated to focus on important customer challenges.

AGI refers to the concept of AI aimed at achieving human-level general intelligence and autonomy. Companies often establish separate AGI organizations to target long-term research and productization simultaneously, but as investment burdens increase, adjustments in organizational priorities also emerge.

Other Federal Reserve surveys reached different conclusions. The Richmond Federal Reserve Bank reported on March 25 that in a survey of over 700 corporate executives, companies reported improvements in productivity alongside increased AI investments and anticipated further improvements by 2026.

The same data suggested that there is still weak evidence that AI has significantly reduced overall employment. However, large companies expected some job reductions, while small businesses anticipated an increase in hiring technical personnel. This implies that the employment effects of AI implementation may vary depending on company size and job structure.

U.S. labor market indicators do not provide a singular conclusion either. Reuters reported on August 6 that U.S. non-farm labor productivity increased at an annual rate of 1.4% in the second quarter. However, it is difficult to conclude that AI has led to a widespread leap in productivity based solely on this figure.

Employee anxiety has also been captured in public opinion indicators. In a survey released by Reuters and Ipsos in June, 53% of Americans responded that AI could threaten their jobs or those of household members. Axios reported that some CEOs are reducing expressions that directly link AI to layoffs, shifting their messaging towards "organizational transformation" and "capability restructuring."

The debate over AI productivity is shifting from the scale of investment to issues of measurement and organizational trust. There are calls for companies to create an environment where employees can embrace technology to connect AI implementation with productivity improvements, alongside survey results indicating that productivity enhancements are already occurring. With only confirmed data, it is difficult to determine whether AI has increased productivity or whether layoffs have amplified that effect.

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