Mark Ma, a professor of business administration at the University of Pittsburgh, warns that the rush to cut jobs in the name of artificial intelligence is backfiring. A recent Federal Reserve survey of senior leaders revealed that about 90% of executives believe AI has not yet boosted productivity at their firms.
Executive survey reveals AI productivity gap
The study, conducted by the Atlanta Federal Reserve, highlights a growing disconnect between the billions of dollars poured into AI tools and the modest gains in output that companies expected. Analysts suggest that the broader rise in productivity since 2021 is more likely linked to remote-work arrangements and sector-wide downsizing, rather than AI itself.
Layoffs linked to AI investments
Ma and his colleagues examined millions of employee-satisfaction reviews, thousands of corporate financial reports and hundreds of AI investment announcements from U.S. public companies over the past five years. They identified a clear pattern: as AI announcements increase, so do layoff notices attributed to AI.
Publicly listed firms often judge new projects on short-term profitability and share-price impact. After spending heavily on AI, managers feel pressure to demonstrate a quick return, which frequently translates into reducing headcount to lower labour costs.
Stock-market reactions to these layoff announcements were largely muted, with average returns close to zero. A few outliers, such as the fintech platform Block, saw a share-price rise when it announced staff cuts tied to AI, but the overall trend was neutral or slightly negative.
Employee sentiment as a hidden cost
Analysis of reviews on the workplace site Glassdoor showed that AI-related comments are markedly more negative than the overall tone of employee feedback. Workers expressed fears about job security, insufficient training, and doubts over AI's real impact on productivity.
These concerns are not merely emotional; the research found a strong correlation between negative employee sentiment toward AI and lower firm productivity, based on financial data. In contrast, management's optimistic language in earnings-call transcripts did not translate into measurable productivity gains.
Implications for managers and investors
Ma argues that using AI as a justification for workforce reductions is a strategic miscalculation. Companies that treat AI as a cost-cutting tool risk demoralising staff and undermining the technology's potential.
To unlock AI's benefits, firms should focus on building employee confidence: invest in upskilling, share productivity gains, and create a culture where AI is seen as a collaborative partner rather than a threat.
Businesses that address job-security concerns and foster positive sentiment are more likely to realise a return on their AI investments.