EVERYTHING
According to Finance, new data from the Stanford Digital Economy Lab indicates that employment in AI-vulnerable occupations is declining much faster among workers in their early 20s than among those in less automatable roles. The research utilizes a "canaries dashboard" which tracks anonymized ADP payroll data to identify specific labor market shifts caused by generative artificial intelligence.
Disproportionate impact on junior roles
The findings suggest that the integration of AI into the workplace is not affecting all demographics equally. While experienced professionals and those in low-exposure fields remain relatively unaffected, early-career workers are facing a more difficult landscape. The data shows that employment for workers aged 22 to 25 in highly exposed occupations contracted by 4.2% as of April compared to the previous year.
In contrast, workers of similar ages in less-exposed fields saw a much smaller decline of only 1.7%. When looking at the broader workforce across all age groups, the impact appears far more muted: employment in AI-exposed jobs dropped by just 0.2% in April, while employment in less exposed fields actually grew by 0.1%.
Sector-specific trends and growth
The disparity is most visible in specific industries where automation is becoming a standard practice. The report highlights several key trends regarding different job categories:
ADP chief economist Nela Richardson noted that these findings demonstrate how AI impacts labor at the task level rather than across entire industries. "You really have to have the microscope ready on data," Richardson told Yahoo Finance, suggesting that broad economic metrics often hide the specific struggles of junior developers. While early-career workers in automated fields face more muted increases or direct declines, the Stanford Digital Economy Lab noted that AI-based augmentation does not appear to be negatively impacting those who successfully integrate these tools into their existing workflows.