US Firms Accused of ‘AI Washing’ Job Cuts

Companies are being accused of 'AI washing' by citing AI as the cause for layoffs, while experts say tariffs, overhiring, and profits are the real drivers.

A new report from the Economic Policy Institute is accusing major U.S. corporations of engaging in "AI washing" by publicly attributing workforce reductions to artificial intelligence adoption, while internal data and economic factors suggest other causes are primarily to blame. The analysis finds that while AI is reshaping certain roles, recent waves of layoffs in the tech, retail, and finance sectors are more directly tied to post-pandemic course correction, geopolitical tariffs, and a strategic focus on profit maximization.

The term "AI washing" describes the practice of overstating the role of AI in business decisions for strategic optics in this case, using it as a publicly palatable rationale for cuts that may otherwise be viewed as harsh restructuring or a response to poor planning. Companies like IBM, Google, and several large retailers have recently cited "AI-driven efficiency" or "workforce rebalancing for the AI era" in layoff announcements.

Labor economists and AI researchers argue this narrative is misleading. "AI is a convenient scapegoat," stated the report's lead author. "Our analysis shows the primary drivers are the reversal of pandemic overhiring, pressure from tariffs on imported goods, and a relentless Wall Street demand for higher margins. Blaming AI allows companies to frame cuts as an inevitable, tech-driven trend rather than a corporate choice."

The practice risks distorting public understanding of AI's true economic impact, potentially fueling unnecessary workforce anxiety and deflecting scrutiny from executive decision-making. It may also provoke premature regulatory responses based on an inflated perception of AI's immediate disruptive power.

Experts urge stakeholders to scrutinize layoff disclosures, noting that genuine AI-driven displacement is currently concentrated in specific tasks rather than entire job categories. They recommend clearer regulatory guidance on corporate communications regarding technology and impacts on employment to ensure transparency and public trust.