In an era increasingly defined by technological advancement, Artificial Intelligence (AI) has emerged as both a beacon of progress and, surprisingly, a convenient scapegoat. As U.S. companies navigate a challenging economic landscape, marked by a dramatic surge in layoffs, a new trend is taking hold in the C-suite: ‘AI-washing’. This phenomenon sees executives attributing job cuts to AI, even when the underlying reasons are far more conventional and, often, less flattering to leadership.
The Alarming Rise of Layoffs and the AI Blame Game
The start of 2026 painted a stark picture for the American workforce. Data from Challenger, Gray & Christmas revealed a staggering 205% increase in U.S. company layoffs from December 2025 to January 2026. While many corporations have been quick to point the finger at AI as the primary driver for these reductions, a growing number of observers are questioning the sincerity of these claims.
experts are coining this deceptive practice “AI-washing” – a term echoing “greenwashing,” where companies make unsubstantiated claims about environmental efforts. In this context, it refers to the act of blaming AI for workforce reductions that are, in reality, driven by more mundane, internal issues.
What Exactly is ‘AI-washing’?
Scott Dylan, founder at AI and tech fund NexaTech Ventures, offers a precise definition: “AI-washing, in the context of layoffs, is when companies attribute job cuts to artificial intelligence when the real drivers are far more mundane, such as over-hiring during the pandemic boom, margin pressure, slowing consumer demand, or plain old corporate restructuring.”
Dylan emphasizes that this tactic allows companies to “dress up an unpopular decision in the language of progress,” making difficult choices seem like an inevitable consequence of technological evolution rather than strategic missteps or market realities.
The Data Discrepancy: Unmasking the True Causes
While the January 2026 layoff numbers were grim, totaling 108,435 job cuts – the worst since 2009 – a closer look at the data reveals a significant disconnect. Dylan highlights that AI was explicitly cited in only about 7,600 of these cases. The overwhelming majority of layoffs were attributed to factors like contract losses, challenging market conditions, and internal restructuring.
Illustrative examples abound. UPS’s decision to cut 30,000 jobs, for instance, had “nothing to do with AI and everything to do with severing ties with Amazon,” Dylan noted. Even Amazon’s own Andy Jassy initially linked the company’s cuts to AI before retracting, citing over-hiring and excessive management layers instead. Such inconsistencies, Dylan argues, are precisely the problem, as they “distort the public’s understanding of what AI can do today” and “feed anxiety that isn’t grounded in reality.”
Why Executives Embrace the AI Narrative
So, why would C-suite leaders opt for the calculated risk of blaming AI rather than acknowledging internal challenges? Management experts suggest it’s a multi-faceted strategy designed to protect reputations and boost investor confidence.
Tamas Hevizi, Chief Strategy Officer at Tungsten Automation, explains, “When leadership blames AI for workforce reductions by saying ‘AI took your job,’ they offer a future-oriented narrative about innovation that investors have rewarded in the past.” This narrative paints a picture of an organization poised for higher margins, greater efficiency, and accelerated growth, all thanks to AI.
Beyond this favorable public relations spin, AI-washed explanations serve as a shield against reputational damage. “It’s easier to say AI is changing the way the world works and workforce reductions are a natural consequence than to admit they misread demand, overspent on AI pilots, or, more simply, hit hard times,” Hevizi adds.
Jason Schloetzer, an associate professor at Georgetown’s McDonough School of Business, concurs, noting that “The AI angle makes you look like a visionary instead of someone cleaning up their own mess.” He emphasizes the psychological ease of blaming technological change over leadership incompetence, especially given AI’s complex and often misunderstood impacts.
Ultimately, the market rewards this approach. As Dylan bluntly states, “No CEO wants to stand up and say, ‘We got it wrong.’ Blaming AI shifts responsibility onto an external, seemingly unstoppable force.” This depersonalizes the decision and positions the company as forward-looking, even when making deeply unpopular cuts. Forrester’s research further supports this, indicating that many companies announcing AI-related layoffs lack mature AI applications to genuinely replace those roles, instead acting on speculative future capabilities.
The Call for Transparency
The ‘AI-washing’ trend underscores a critical need for greater transparency in corporate decision-making. While AI undoubtedly holds transformative potential, its misuse as a convenient excuse for layoffs not only misleads the public and employees but also undermines genuine efforts to integrate AI responsibly. As the corporate world continues to evolve, distinguishing between genuine technological shifts and strategic blame-shifting will be paramount for fostering trust and accountability.
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