Demis Hassabis, CEO of Google DeepMind, made an argument this week that cuts against the dominant narrative of 2026: the wave of tech layoffs reshaping the industry is driven by imitative behavior, not AI efficiency gains. “Layoffs are the result of imitative behavior,” Hassabis said, describing companies cutting jobs because other companies are doing it. Calling the pattern a “lack of imagination,” he flagged the cascade effect as “super worrying,” particularly as consistent headlines linking AI advancement to job cuts cause organizations to view the two as necessarily interconnected.
Industry analyst Josh Bersin and Wharton professor Peter Cappelli have both pushed back on the standard narrative. Bersin argues companies are miscalculating by prioritizing cost reduction over performance improvement. Cappelli notes that most layoffs are funding data centers or addressing financial pressures, not capturing AI productivity gains. The efficiency rationale, in that reading, is largely post-hoc.
IBM’s CHRO Nickle LaMoreaux is the most cited counterexample in the sector. IBM’s approach has been to layer early-career HR talent atop chatbots, using the pairing to train AI systems while simultaneously building employee skills and engagement. The model rejects the replacement frame entirely: AI handles routine query volume, junior employees handle judgment calls and edge cases, and the system improves through the interaction. The result is a workforce that grows alongside the technology rather than being displaced by it. For CHROs navigating the confidence gap that is slowing AI deployment across most organizations, the IBM model is an existence proof that the tradeoff between AI scale and workforce investment is not as forced as current headlines imply.
Source: HR Executive
