Goldman Sachs just dropped the receipts: artificial intelligence is starting to squeeze labor markets across the developed world, and the damage is uneven, targeted, and already measurable.
Employment in the most AI-exposed industries has fallen sharply below trend. Call centers, software publishing, management consulting, and advertising are bleeding jobs. Call centers alone are now 39% below trend in the U.S., 33% in Canada, and 27% in Germany. Information and communication services have slowed almost everywhere since late 2022.
The hit is hardest on people trying to break in. Across more than 800 occupations, AI-related headwinds hit entry-level workers hardest. A 10% exposure to AI costs only about 0.1 percentage points of annual headcount growth overall in places like the U.S., France, and Canada. For entry-level roles, that drag jumps to more than 0.2 points in the U.S. and over 0.6 points in Australia.
AI adoption itself is already mainstream: roughly 15–20% across major developed economies. France, the U.S., the Netherlands, and the U.K. lead. Italy, Japan, and New Zealand lag. Emerging markets sit a bit lower, at 10–15%.
Bottom line from Goldman: the AI job pressure is real and visible in the data — but still concentrated in a relatively narrow set of industries and workers. For now.
- High Application Volume, Low Yield: Grads report sending 450 to 500+ applications with minimal job offers.
- Elevated Unemployment: According to the New York Fed, unemployment for recent graduates (ages 22–27) reached 5.7%, notably higher than the overall national rate of 4.1%.
- Worker Sentiment: A ZipRecruiter survey reveals 47% of recent grads believe AI is already negatively affecting hiring in their fields.
Three Perspectives: What Is Really Driving the Trend?
- Expert: Erik Brynjolfsson (Stanford University)
- The Argument: Brynjolfsson’s research found a 16% relative drop in early-career employment (ages 22–25) in AI-exposed fields like software development and marketing since late 2022. Older workers and non-automatable roles (healthcare, construction) remain stable.
- Why Junior Roles Suffer: Large Language Models excel at "codified knowledge" (textbook data), which overlaps heavily with entry-level duties. Junior workers lack the "tacit knowledge" and experience that insulate senior employees from automation.
- Expert: David Deming (Harvard University)
- The Argument: The drop in junior hiring began roughly six months before ChatGPT launched. New York Fed data indicates that as remote work rose post-pandemic, companies grew hesitant to hire fresh grads because remote training is difficult and costly.
- The Shift: Employers prefer hiring experienced talent who can work productively from home without hands-on onboarding.
- Expert: Anders Humlum (University of Chicago)
- The Argument: Data from Ramp and Revelio Labs analyzing 21,000+ U.S. firms shows that companies spending the most on AI tools (like OpenAI and Anthropic) increased entry-level headcount by 12% over two years post-adoption. Heavy AI implementation correlates with business expansion, not layoffs.
Key Takeaway
| Factor | Primary Impact on Entry-Level Hiring |
| AI Automation | Replaces basic entry-level tasks based on written data; disproportionately affects early-career workers. |
| Remote Work | Discourages junior hiring due to high remote-onboarding costs; shifts preference toward senior hires. |
| AI Adoption | Drives growth at top-performing tech firms, creating new opportunities for early-career hires. |
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