By Julia Parker — JBizNews Desk

New federal labor data is offering the clearest statistical evidence yet that artificial intelligence is beginning to reshape segments of the U.S. workforce in measurable ways — even as policymakers, economists, and corporate leaders remain divided over how quickly the disruption will spread.

The U.S. Bureau of Labor Statistics reported Friday that a group of 18 occupations previously identified by the agency as highly exposed to AI technologies experienced a combined 0.2% employment decline between May 2024 and May 2025, while overall U.S. employment grew 0.8% during the same period.

Excluding medical secretaries — a category still benefiting from strong healthcare-sector demand — employment across the remaining 17 AI-exposed occupations fell 1.6% for the second consecutive year, according to the Bureau’s Occupational Employment and Wage Statistics release.

The figures represent one of the first broad federal datasets suggesting that AI-related disruption may already be materializing inside the labor market rather than remaining purely theoretical.

The largest losses occurred in exactly the types of occupations economists have long warned could face automation pressure.

Customer service representative positions declined by approximately 130,180 jobs, a 4.8% drop over the year. Secretaries and administrative assistants outside executive, legal, and medical roles lost roughly 31,000 positions, while wholesale and manufacturing sales representatives declined by nearly 29,000.

Longer-term declines are even more striking. Since May 2022 — shortly before OpenAI’s launch of ChatGPT accelerated the generative-AI boom — employment among credit authorizers and clerks has fallen more than 26%, according to BLS data. Broadcast announcers and radio DJs are down roughly 21%, while sales engineer positions have declined more than 13%.

Private-sector labor tracking firms are now reporting similar patterns.

Challenger, Gray & Christmas, the Chicago-based outplacement firm that monitors corporate layoffs, said employers attributed roughly 21,490 planned layoffs in April directly to AI-related restructuring, accounting for about 26% of all announced job cuts during the month.

Year-to-date, the firm estimates approximately 49,135 announced layoffs have been tied to AI-driven restructuring or investment shifts.

“Technology companies continue to announce large-scale cuts and are leading all industries in layoff announcements,” said Andy Challenger, the firm’s chief revenue officer. “They are also often citing AI spend and innovation. Regardless of whether individual jobs are being replaced by AI, the money for those roles is.”

Corporate America has increasingly begun speaking openly about the workforce implications.

Amazon CEO Andy Jassy announced another 16,000 layoffs in January following earlier reductions last year and warned employees that generative AI and autonomous software agents would likely reduce portions of the company’s corporate workforce over time.

Block, the financial-technology company led by Jack Dorsey, has eliminated roughly 40% of its staff during a restructuring heavily centered on AI adoption. Snap Inc. cut approximately 16% of its global workforce in April, while Meta Platforms CFO Susan Li told analysts the company expected additional staffing reductions tied partly to operational efficiency initiatives.

The broader labor market is also beginning to show signs of softening beneath the headline unemployment rate.

The Bureau of Labor Statistics’ Job Openings and Labor Turnover Survey showed openings standing at 6.9 million in March, far below the 10.3 million peak reached in early 2023. Hiring rates remain near lows last seen during the pandemic recovery period.

Young workers appear especially vulnerable.

A 2026 study from the Federal Reserve Bank of New York found that recent college graduates between ages 22 and 27 faced a 5.6% unemployment rate at the end of last year, above the national average of 4.2% at the time.

Researchers at Stanford University’s Digital Economy Lab, led by economist Erik Brynjolfsson, found workers between ages 22 and 25 employed in highly AI-exposed occupations experienced a 16% relative employment decline since late 2022, while workers over 30 in the same categories saw gains ranging between 6% and 12%.

Federal officials are increasingly acknowledging the disruption publicly.

Outgoing Federal Reserve Chair Jerome Powell, who is being succeeded this month by Kevin Warsh, told economics students at Harvard in March that large companies “can take out a lot of jobs that can be automated by a very smart large language model. They just can and they will, because their competitors are doing it.”

Powell urged younger workers to adapt by learning to work alongside AI technologies rather than attempting to avoid them.

At Goldman Sachs, economist Joseph Briggs estimates that approximately 6% to 7% of U.S. workers could ultimately face displacement during a decade-long AI transition period. Briggs projects unemployment could rise toward 4.5% before stabilizing as productivity gains spread through the economy.

Washington has begun moving toward a policy response, though slowly.

Senators Mark Warner and Mike Rounds introduced bipartisan legislation in March creating an “Economy of the Future Commission” tasked with developing recommendations on retraining, unemployment insurance, workforce transition policy, and tax reform tied to AI disruption. The proposal has received support from companies including Microsoft and Google.

Additional legislation from Senators Josh Hawley and Jim Banks would require the federal government to formally model AI-related labor-market impacts, while a separate unemployment-insurance overhaul proposed by Senator Ron Wyden remains stalled in the Senate Finance Committee.

Not all economists agree the labor-market deterioration is being driven primarily by AI.

Stephanie Aliaga, global market strategist at JPMorgan Asset Management, argues AI-linked layoffs still account for a relatively small share of overall workforce reductions and says much of the productivity acceleration seen over the past year may stem more from pandemic-era restructuring than from AI itself.

Others disagree sharply.

Ed Yardeni, president of Yardeni Research, points to rising layoffs in professional and business-services sectors — industries considered among the most exposed to AI automation — as evidence that the transition is already underway.

The political stakes are beginning to rise heading into the midterm election cycle.

Acting Labor Secretary Keith Sonderling, who replaced Lori Chavez-DeRemer in April, now oversees what the Trump administration describes as a “worker-first AI agenda” centered on skills training, workforce adaptation, and AI literacy initiatives launched earlier this year.

At the same time, state-level attempts to regulate algorithmic hiring and AI-driven employment decisions increasingly face possible federal preemption under a December executive order, creating uncertainty over how labor protections will ultimately be enforced.

For now, the labor market is sending mixed signals simultaneously: low headline unemployment, slowing hiring activity, weaker entry-level opportunities, and mounting federal evidence that AI-driven restructuring is beginning to reshape portions of the white-collar workforce.

The economic transition has started. The policy response remains unfinished.

JBizNews Desk

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