Gen Z facing disproportionate losses in AI economy, Goldman warns trend will continue

(SeaPRwire) –   The net number of monthly jobs being eliminated by AI is shrinking. That sounds like good news on the surface — but it is not, at least not for Gen Z.

Two months ago, Goldman Sachs economists estimated that artificial intelligence was cutting roughly 16,000 net U.S. jobs per month, with entry-level and young white-collar workers bearing the heaviest impact. Goldman’s latest AI Adoption Tracker, released Friday, places that net monthly job loss figure at around 11,000. That looks like progress on paper. But the reason the number has improved has almost nothing to do with AI slowing its advance across white-collar work. Instead, it ties back to blue-collar construction work, represented by hard hats and conduit wire — and this offsetting growth may not be permanent.

Data center construction — the physical infrastructure needed to run the AI systems that replace office workers — has added 212,000 jobs since 2022 and currently creates roughly 9,000 new positions each month, according to Goldman economists Sarah Dong and Joseph Briggs. These new roles are filled primarily by electrical contractors, HVAC specialists, and utility and commercial building construction workers.

Experts who research the data center labor market, however, warn these are likely not long-lasting jobs: once the wave of data center buildout is complete, employment in the sector will fall. The American Edge Project estimates the data center boom will create roughly 4.7 million temporary construction jobs, but only around 697,000 permanent operations roles. After a facility is up and running, it only needs a small ongoing workforce: technicians to monitor servers, facility engineers to manage cooling systems, plus security and maintenance staff.

If you remove construction job gains from the equation, the outlook in industries where AI has already become established — marketing, graphic design, customer service, document processing, software — looks worse than the top-line headline suggests. Corporate layoff announcements explicitly tied to AI cut approximately 21,900 jobs in April, the highest single-month total Goldman has tracked since it began counting these layoffs in 2023. Total AI-attributed layoffs over the past three years now stand at 136,000. And discussions of AI’s impact on labor are growing in corporate boardrooms: 24% of Russell 3000 companies mentioned AI and labor together on Q1 2026 earnings calls, a figure that has climbed sharply and shows no sign of leveling off.

A generational tilt, still taking shape

Across this overall landscape, Goldman’s tracker is starting to show a pattern worth monitoring: a small positive correlation between AI adoption rates and unemployment for workers under 30, when measured across all industries. This is not yet a clear permanent structural shift — in fact, Goldman’s own data shows unemployment among young tech workers has recently fallen back in line with the broader tech workforce — but the cross-industry signal is consistent enough that Goldman says it will continue to watch the trend closely.

Academic studies compiled by Goldman show generative AI delivers a 23% average productivity boost, and these gains flow disproportionately to senior workers who can leverage the technology, not to workers whose core value was completing the routine tasks AI now handles.

Across the entire economy, the labor market remains resilient. In a note published Thursday, UBS economists project nonfarm payrolls added around 95,000 jobs in May and the unemployment rate held near 4.33%. Their conclusion matches Goldman’s: AI’s broad impact is unlikely to appear as a simple or sustained rise in overall unemployment. UBS describes a race between “rising job destruction” and “strong job creation and stable unemployment,” with the outcome dependent on how quickly new roles and new industries emerge. The most likely result, the bank adds, is “significant occupational churn and periodic workforce dislocation.” For now, blue-collar job gains are offsetting the decline in entry-level hiring.

AI adoption at the firm level is progressing slowly. Census Bureau data compiled by Goldman shows 19.5% of U.S. business establishments now use AI for regular business operations, a 0.3 percentage point drop from the last tracker reading, with 22.7% of establishments expected to adopt AI within six months. Where AI has been adopted, however, Goldman cites “academic studies” pointing to a 23% average productivity uplift, and a 33% boost based on anecdotal reports from companies.

Chemical manufacturing and electrical equipment firms are reporting the largest expected increases in AI adoption in the near future — marking the next frontier of job displacement, expanding beyond knowledge work into industrial settings.

For now, the race between AI-driven job displacement and new job creation is tightening. The workers pulling ahead right now are those pouring concrete for new data centers. The workers falling behind are the people those data centers were built to replace. And once all the construction is complete, the core question will still remain: what comes next?