CNBC: In recent layoffs, AI’s role may be bigger than companies are letting on

The Hidden Impact of Artificial Intelligence on the Modern Workforce: What Companies Aren’t Saying

In recent months, widespread layoffs have become a common feature of the corporate landscape, even amid a robust stock market and resilient economy. However, an intriguing pattern is emerging: many companies are reluctant to explicitly attribute job reductions to advancements in artificial intelligence (AI). Instead, they often use vague terminology such as “reorganization,” “restructuring,” or “optimization” to mask underlying changes driven by automation technology.

Notably, IBM has publicly acknowledged replacing hundreds of human resources employees with AI-powered chatbots, while also maintaining an overall increase in staffing through reinvestment. Similarly, fintech pioneer Klarna has been transparent about cutting nearly 40% of its workforce—dropping from about 5,000 to 3,000 employees—primarily attributing these reductions to AI-driven efficiencies.

Industry experts suggest these examples are just the tip of the iceberg. Many firms prefer to conceal the true motivation behind layoffs, fearing backlash from employees, regulators, and the public. The common practice is to frame workforce reductions as part of strategic restructuring or cost-saving initiatives, even when they are closely tied to automation advancements.

According to analysts, the use of euphemistic language acts as a shield, allowing companies to avoid uncomfortable truths about displacement by AI. “Organizations often shy away from admitting they’re replacing human labor with intelligent systems,” explains Harvard University instructor Christine Inge. “This tendency to obscure the role of AI serves both to preserve morale and to mitigate reputational risks.”

Furthermore, many companies are wary of overcommitting to AI solutions, recognizing that current technology still requires human oversight. While automation can handle a significant portion of tasks in fields like customer service, content creation, and operational management, complete reliance on AI often proves premature. For instance, the last stages of many processes—such as quality assurance and nuanced judgment—still demand human involvement.

This cautious approach leads to scenarios where organizations initially promote AI adoption but later shift to outsourcing or re-hiring globally when AI solutions fall short. Such strategic shifts are often kept under wraps to maintain a positive external image and avoid provoking employee unrest.

On the HR and communications front, this veil of silence is a deliberate strategy. As Inge notes, “Explicit acknowledgment of AI-driven layoffs invites criticism and regulatory scrutiny. Keeping language vague helps companies manage internal morale and external perceptions while navigating the complex transition.”

The reluctance to openly discuss AI’s role in workforce changes is also