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Stanford Study: AI's Toll on Entry-Level Jobs Deepens

Stanford study: AI-driven entry-level job losses deepen, with employment for young workers in exposed fields falling 19% below peers.

AI News Feed · 2026-08-26 06:09

The August 2026 edition of "Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence" revises a paper published last year with fresh data. Researchers found that employment levels for workers aged 22 to 25 in the most "AI-exposed" occupations are now 19 percent below those of their peers in fields less exposed to AI disruption, compared with a 13 percent gap last year.

Digging into the data, the researchers found the effect mainly shows up in lower hiring rates for entry-level workers in AI-impacted fields, rather than increased firings or employees quitting. The labor market effects among this age group were mostly seen in lower overall employment, not reduced pay rates.

Not all jobs with AI disruption potential are equal, the researchers said, citing Anthropic's Economic Index that distinguishes between "automative" tasks (fully replacing human work) and "augmentative" tasks (helping workers be more effective). Jobs like "accountants and auditors" and "receptionists and information clerks" were most susceptible to AI automation, while "chief executive" and "registered nurse" were among those using AI augmentation most often.

Jobs where AI automation is prevalent show the worst relative employment levels for entry-level workers. "The findings are consistent with automation-oriented uses of AI substituting for labor while complementary uses are associated with flat or rising employment," the researchers wrote.

The impact is strongest in entry-level jobs built around "codified" knowledge—formal, documented skills AI can more easily replicate. Experienced workers in roles relying on tacit, practice-based knowledge have seen stronger employment growth.