AI May Be Hitting Young Workers First as Employment Gap Widens to 19%

AI may not be causing widespread job displacement, but a growing employment gap is emerging among young workers. An updated Stanford study found that workers ages 22 to 25 in highly AI-exposed occupations are increasingly falling behind their peers in less-exposed fields.

Their employment level is now about 19% below where it would have been had it kept pace with similarly aged workers in less-exposed occupations, up from a 15% shortfall at the July 2025 data vintage.

Young Workers Are Feeling the AI Pinch

The study, 'Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence,' analysed high-frequency ADP payroll data covering millions of US workers through June 2026.

Researchers found that the trend is not primarily being driven by widespread layoffs. Instead, the adjustment appears to be happening mainly through reduced hiring. The effect is concentrated among workers ages 22 to 25, while experienced employees show no comparable gap.

They also found no evidence of widespread, economy-wide job displacement associated with AI. Additionally, they caution that the data do not prove AI itself caused the employment shifts, with other labour-market factors potentially playing a role.

The key distinction appears to be whether AI substitutes for human work or complements workers. The researchers found that employment declines were concentrated in occupations where AI tends to automate human tasks. By contrast, employment in occupations where AI is used more to complement workers was flat or rising, particularly among experienced employees.

The Knowledge Gap May Matter

Stanford researchers suggest that codified knowledge may help explain the trend. It is the information that can be documented, taught through textbooks, or turned into clear, standard procedures.

More experienced workers often draw on tacit knowledge built through practice, mentoring, and handling situations that cannot easily be captured in a manual. That may help explain why employment has held up better for experienced workers in occupations that rely more heavily on experience.

To test the idea, the researchers used the required level of formal education in O*NET's occupational database as a proxy for how heavily a job relies on codified knowledge. When they broke down the employment data, they found that 'occupations with higher codified knowledge have slower entry-level employment growth, while occupations with higher tacit knowledge have faster employment growth for mid-career and senior workers.'

The findings suggest the issue may not simply be AI replacing workers. In some fields, the technology could be changing which skills employers value and who gets the opportunity to develop them in the first place.

AI's Impact May Be Milder in Jobs With More College Graduates

Higher education may also be associated with a smaller gap between AI-exposed and less-exposed occupations. The researchers found that occupations with more college graduates showed 'muted differences between more-exposed and less-exposed occupations.'

Erik Brynjolfsson, one of the study's authors, has raised concerns about what the trend could mean for younger workers. In an interview, he said that his concern is less about existing workers losing their jobs and more about fewer opportunities for people starting out. 'The entry-level effects we're measuring are real, persistent, and widening,' he said, 'and I'm more worried than I was about a labour market that keeps its overall employment level while quietly closing the on-ramp for people starting their careers.'