Corporate investment in artificial intelligence has surged, but the anticipated productivity boosts have largely failed to materialize. According to research from the Atlanta Federal Reserve, about 90% of executives report that AI has not yet enhanced productivity within their organizations. Meanwhile, many companies continue cutting jobs, often attributing layoffs to AI adoption.

This paradox arises in part because layoffs and job insecurity may undermine the positive effects AI could have on workforce efficiency. Studies analyzing millions of employee reviews and corporate financial outcomes reveal a strong connection between announcements of AI investments and AI-related job cuts. Far from being unrelated, these trends reflect a prevalent corporate strategy that combines AI deployment with workforce reductions to achieve short-term financial goals.

Executives and investors often pursue AI adoption under the belief that smarter technology will enable smaller teams to maintain or increase output, justifying layoffs as a cost-saving measure. Some firms have even reduced headcount before committing substantial capital to AI, aiming to free up resources for future technology spending. However, stock market responses to such layoffs have been neutral on average, indicating that investors do not view these moves as clear value creators.

Additional analysis suggests that the modest productivity improvements observed since 2021 likely owe more to factors like remote work trends or sector-specific downsizing rather than AI itself. Moreover, the negative impact of layoffs on employee sentiment toward AI is significant. A workforce anxious about job security tends to resist or be less effective at integrating AI tools, which in turn stifles potential productivity gains.

The findings call for a reassessment of AI strategies focused mainly on workforce cuts. Instead, companies might benefit from fostering stable work environments that encourage employee collaboration with AI technologies, as positive employee attitudes remain a key predictor of productivity in AI-augmented workplaces.