Stanford Study on AI and Entry-Level Jobs Is Being Widely Misread, Analysts Warn

A Stanford Digital Economy Lab paper by Brynjolfsson, Chandar, and Chen has been widely cited as proof that AI eliminated 16% of entry-level jobs, but researchers say that figure is being misrepresented. The 16% is a relative employment gap between young workers aged 22–25 in high-AI-exposure occupations and older colleagues at the same firms, not an absolute job-loss count. Raw data from the study shows that between late 2022 and September 2025, employment among 22-to-25-year-olds in the most AI-exposed roles fell 6%, while older workers in the same fields saw gains of 6–9%. The authors themselves caution that their findings are correlational, stating the results are 'consistent with' AI's influence but stopping short of establishing causation. The study also draws solely on ADP payroll data, which is not a national sample, and the paper's own authors acknowledge that contradicting datasets exist and that firmer causal analysis requires better firm-level AI adoption data.