The Economist says AI has created 1M new jobs in America — fear of the apocalypse officially postponed

AI Job Creation Outpaces Cuts by Orders of Magnitude

The apocalypse narrative around AI and employment has met its first real counterweight. The Economist's analysis finds that AI has created roughly 1 million new jobs in America, easily overwhelming the roughly 200,000 layoffs attributed to AI since mid-2023. The data suggests what productivity economics would predict: a technology that enhances output and attracts massive capital investment tends to hire, not devastate.

The math is stark. Companies announced roughly 16,000 AI-related job cuts per month so far this year. But that represents less than 1% of total job churn in the US economy, where roughly 1.7 million jobs disappear each month while 1.8 million are added. The layoffs are noise in the signal.

Infrastructure Build-Out Drives Blue-Collar Hiring

The scale of capital deployed into data centers and power systems explains much of the job creation. Spending on AI infrastructure—chips, servers, data centers, cooling, power—has risen by roughly $500 billion annually above 2022 levels, according to Goldman Sachs calculations. Data center construction alone is running at more than $75 billion annually, nearly 60% higher than a year ago.

This building spree requires electricians, HVAC specialists, grid engineers, and technicians. Employment in five core data center industries—electrical contracting, equipment manufacturing, and related trades—has risen by roughly 320,000 positions beyond what broader construction trends would suggest since 2023.

The labor shortage is real enough that employers are paying premiums. Installation and maintenance jobs at data centers advertise wages about 40% higher than comparable work elsewhere. Official wage data show average hourly earnings rose more than 13% in electrical equipment manufacturing and nearly 8% among electrical contractors in the year to June. Even with those gains, hiring managers report difficulty filling positions.

White-Collar Roles Emerging and Scaling

AI is simultaneously creating entirely new professional roles. Data annotators, forward-deployed engineers, judges evaluating model outputs, and heads of AI positions barely existed three years ago. Job postings for heads of AI, AI engineers, and directors of AI have roughly doubled since 2023.

Economist Gad Levnon at the Burning Glass Institute estimates that roughly 1% of professional jobs in America are now AI-specific positions, totaling around 1 million roles. In computer occupations and life sciences, the share reaches 4 to 5%. LinkedIn's analysis identifies roughly 640,000 new AI-specific jobs created between 2023 and 2024. Employment in professional occupations closest to the AI boom—engineers, software developers, mathematicians, data scientists—has added roughly 730,000 positions above trend in recent years.

Productivity Gains Create Secondary Demand

A less direct but potentially larger mechanism is at work: productivity improvements lower service costs, which can expand demand enough to create net job growth. AI allows lawyers to draft contracts faster and analysts to comb through financial filings in minutes. If lower costs drive higher demand, more work materializes.

This dynamic mirrors the credit card effect—a quiet but powerful lubrication of commerce. Credit cards did not revolutionize how purchases worked; they simply made transactions slightly more trustworthy and frictionless, which accelerated deal velocity across the economy. Similarly, AI tools that reduce friction in decision-making or visualization can increase the velocity of projects and purchases, creating downstream work.

Young workers, often cast as AI's first victims, show no sign of distress. The unemployment gap between 20-to-24-year-olds and the overall rate sits near a multi-decade low.

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The caveat: Some sectors are being displaced. Hiring in professional and business services is running 10% below the 2015-2019 average. Tech giants like Microsoft and Meta are trimming headcounts as they reorganize around AI. But these disruptions are sector-specific, not economy-wide, and the jobs created far exceed those destroyed. The productivity story remains the prior: new technologies that enhance output while attracting investment typically expand labor demand, not contract it.