Canaries in the Coal Mine: AI's Impact on Employment Trends

Labor Markets & EmploymentEconomic Development & IndicatorsAI & Machine Learning

The Canaries Dashboard is a powerful tool for understanding the labor market impacts of AI. By analyzing employment trends in a large sample of firms, we can gain insights into the effects of AI on different age groups and occupations.

TL;DR
• The Canaries Dashboard measures the labor market impacts of AI using a large sample of firms.
• Employment trends vary by age group and AI exposure.
• Men and women experience different employment trends in AI-exposed occupations.

Summary
The Canaries Dashboard, developed by Stanford Digital Economy Lab and ADP Research, tracks real‑time labor market shifts linked to AI exposure using a balanced sample of 25,000 firms and 4.6 million workers across 730 occupations. It offers monthly updates, enabling early detection of AI‑driven employment trends.
• Early‑career workers in highly AI‑exposed roles, such as software developers and customer service representatives, experience the steepest employment declines, while less exposed occupations like home health aides see gains.
• Automation intensity correlates with slower growth; augmentation shows weaker impact, suggesting collaborative AI models may preserve jobs.
• Gender disparities arise mainly from occupational composition, with early‑career women disproportionately represented in exposed roles, leading to modestly higher contraction rates.
• The dashboard’s low‑latency data and occupational granularity complement national surveys, providing a timely, granular signal of AI’s heterogeneous labor effects.

The methodology relies on a five‑year rolling window, excluding firm entry/exit to isolate employment dynamics within firms. Workers are matched to SOC codes and weighted equally across occupations, ensuring exposure metrics reflect task characteristics rather than employment size.

Findings highlight that AI’s impact is uneven: early‑career workers in high‑automation sectors face the greatest risk, while older workers and those in low‑automation roles remain relatively stable. These insights underscore the need for targeted workforce development, continuous monitoring of AI deployment, and policies that support skill transitions and equitable labor outcomes.

The Canaries Dashboard provides a unique perspective on the labor market impacts of AI. By continuing to monitor employment trends and AI exposure, we can better understand the effects of AI on different age groups and occupations.