While AI targets corner offices, hourly workers are left behind

"We have reached the moment white collar workers have feared for months. Has AI finally come for my job? Companies like Salesforce claim they need fewer human employees to do the work AI can tackle, after laying off thousands. Klarna claims the company was able to shrink its headcount by about 40%, in part because of AI. Duolingo said last spring it will stop using contractors for work that AI can handle. Overall, companies have announced a staggering 700,000 job cuts in the first five months of 2025, an 80% jump from the previous year."

"The irony is almost poetic. For years, the tech industry assumed robots would come for factory workers first. Amazon's leaked documents once suggested the company could replace half a million warehouse jobs with automation. Instead, just weeks ago, Amazon laid off 14,000 middle managers while planning to hire 250,000 seasonal warehouse workers for the holidays. The AI revolution, it turns out, is hollowing out the corporate ladder before it touches the warehouse floor."

"We are currently in an AI application bubble. The last few years of AI innovation have focused almost entirely on white-collar productivity: workplace efficiency tools, revenue-optimization platforms, and communication automation. Many of the major AI innovations from the past two years have been designed for someone working a 9-5 desk job from a laptop."

AI-driven automation has accelerated major white-collar layoffs as companies claim fewer human employees are needed for tasks AI can perform. Large firms reported steep headcount reductions and hundreds of thousands of job cuts in early 2025, disproportionately affecting middle-management and desk roles. The pattern contrasts with earlier expectations that automation would hit factory and warehouse work first. Most recent AI products prioritize office productivity, revenue optimization, and communication tools for 9-to-5 workers. Meanwhile, a large share of the workforce continues to rely on manual, fragmented processes for scheduling, onboarding, and timekeeping that current AI innovations largely ignore.

Read at Fast Company