99% of CEOs Expect AI-Driven Layoffs in the Next Two Years

A Mercer report reveals 99% of CEOs anticipate AI-driven layoffs within two years, prioritizing automation for ROI while 32% doubt human-machine workforce integration. Early-career workers face the brunt of cuts, with studies showing a grim job market for 22-to-27-year-olds and growing AI skepticism across generations, including Gen Z and older demographics.
A recent Mercer Global Talent Trends report found that 99% of CEOs expect AI initiatives to lead to layoffs within the next two years. Executives view automation as the highest return on investment, though only 32% believe current workforces can effectively combine human and machine capabilities. The trend is particularly impacting early-career roles, as AI excels at automating simpler tasks typically handled by junior employees during on-the-job training. The corporate push for AI-driven efficiency has intensified in Silicon Valley, with companies citing productivity gains as justification for mass layoffs. However, experts remain divided on whether these layoffs translate to meaningful productivity improvements or are merely a tactic to drive AI adoption. A separate survey highlights that most AI-related job cuts will target younger workers, as their roles are seen as more easily automated. Studies confirm the negative impact on early-career hiring, with the job market for 22-to-27-year-olds at its worst since the pandemic. Disillusionment among young professionals is rising, as Gen Z’s engagement with AI plateaus and anxiety about the technology grows. A recent NBC News poll found AI unpopular across age groups, even less favored than the Immigration and Customs Enforcement Agency (ICE). While CEOs emphasize AI’s cost-saving potential, workers face real consequences, including stagnant hiring and diminished career prospects. The disconnect between executive optimism and workforce struggles underscores broader concerns about AI’s role in reshaping labor markets. Younger generations, in particular, express frustration with a system prioritizing automation over training and development.
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