AI Displacement Hits Entry-Level Workers Hardest: Employment Down 19% in Most Exposed Fields

AI Is Hitting Entry-Level Jobs with Unprecedented Force

AI is reshaping labor markets in ways that disproportionately harm younger workers trying to start their careers. Stanford University economists released updated research in August 2026 revealing that employment for workers aged 22 to 25 in AI-exposed occupations has fallen 19% below their peers in less-affected fields1

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. This marks a significant increase from the 13% gap measured just one year earlier, signaling an accelerating trend that threatens to fundamentally alter how younger workers enter the workforce.

The Stanford study, titled "Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence," analyzed anonymized payroll data from HR management company ADP to track employment patterns across different age groups and occupations1

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. While economy-wide employment shows relatively muted effects from AI adoption, the picture changes dramatically when examining entry-level workers specifically. Since 2022, employment in the top 40% of AI-impacted jobs for workers aged 22-25 has dropped approximately 11%, while employment in the 60% least-impacted jobs grew by 10% over the same period1

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Goldman Sachs Confirms Global Pattern of AI Displacement

Goldman Sachs corroborated these findings with its own analysis of over 800 occupations across developed economies2

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. The investment bank found that industries with greater exposure to AI automation have experienced slower job openings growth since the second half of 2022, with the relationship particularly pronounced in Germany, Australia and the United States2

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. Employment in information and communication services has slowed across nearly all major developed economies since 2022, though it remains near or above long-run trends outside the U.S.2

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For entry-level workers, Goldman's research revealed a more severe impact. A 10% occupational exposure to AI was associated with only a 0.1 percentage point drag on annual headcount growth across the broader labor market in France, Canada and the United States2

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. However, for entry-level workers, the impact ranged between more than 0.6 percentage points in Australia and over 0.2 percentage points in the U.S.2

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. This disparity underscores how AI-driven automation concentrates its effects on those just entering the workforce.

Call Centers and Software Publishing See Steepest Declines

Specific industries show even more dramatic employment losses. Call centers stand out with employment now 39% below trend in the United States, 33% lower in Canada, and 27% below trend in Germany2

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. Software publishing, management consulting and advertising services have also fallen sharply below historical trends across developed markets2

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. These patterns indicate that AI-related employment pressures appear first in industries where automation tools are already available and actively deployed.

The Stanford research differentiated between "automative" AI uses that fully replace human work and "augmentative" uses that help workers be more effective1

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. Jobs like accountants, auditors, receptionists and information clerks were among those most susceptible to AI automation, while positions such as chief executives and registered nurses more commonly used AI augmentation1

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. Unsurprisingly, jobs where AI automation is prevalent show the worst relative employment levels for entry-level workers, while occupations using augmentative AI present a much more mixed picture1

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Reduced Hiring Rather Than Mass Layoffs Drives the Trend

The mechanism behind declining entry-level employment appears to be reduced hiring rates rather than increased firings or employee departures1

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. Companies in AI-exposed industries are simply choosing not to fill positions that AI can now handle, creating a barrier to entry for younger workers seeking their first professional roles. Earlier Goldman Sachs research estimated AI was reducing U.S. payroll growth by 16,000 jobs per month3

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Data from Challenger, Gray & Christmas showed 33,429 job cuts in July, the lowest monthly total in two years, yet AI was cited as the top reason for layoffs for a fifth straight month, accounting for 10,970 cuts or 33% of the total3

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. Through July, employers cited AI in 112,713 layoff announcements in 2026, representing about 24% of all announced cuts3

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. The technology sector alone accounted for 149,023 layoff announcements through July, up 67% from a year earlier3

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AI Adoption Reaches Critical Mass Across Developed Economies

AI adoption has reached 15% to 20% across major developed markets, according to Goldman Sachs analysis of 11 surveys measuring AI adoption across countries2

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. France, the United States, the Netherlands and the United Kingdom are leading AI adoption, while Italy, Japan and New Zealand lag at the lower end among developed economies2

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. Major emerging markets show estimated adoption rates between 10% and 15%2

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This widespread adoption matters because it represents a threshold where AI impact on global labor markets becomes measurable and significant. PYMNTS Intelligence research on "Labor Economy" workers earning up to $25 per hour found that 37% of these employees reported their company had introduced new AI or automation tools in the last 12 months5

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. The research revealed that AI's impact is moving beyond corporate offices into warehouses, restaurants, hospitality, logistics and caregiving jobs that constitute a large share of everyday consumer spending5

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What This Means for Career Pathways and Economic Mobility

The concentration of AI displacement among entry-level workers raises serious questions about how younger workers will gain the experience needed to advance in their careers. Traditional career ladders often depend on entry-level positions where workers learn industry fundamentals before progressing to more complex roles. If AI eliminates these stepping stones, it could create a generation of workers struggling to break into professional fields despite having relevant education and training.

Recent research from Harvard Business School and INSEAD found that AI-native startups were about 25% smaller than comparable startups, employed roughly 15% fewer entry-level workers and managers, and had a share of senior workers about 20% higher4

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. These companies use AI both to make employees more productive and to build AI directly into their products, allowing them to operate with smaller teams while maintaining similar valuations to traditional startups4

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Goldman Sachs concluded that AI-related hiring headwinds are clearly visible in employment data globally but remain limited to a relatively narrow set of industries and workers2

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. However, the speed at which the entry-level employment gap has widened from 13% to 19% in just one year suggests this narrow impact could broaden rapidly as AI adoption continues to accelerate across developed economies.