On September 29, 2025, Bharat Chandar, postdoctoral fellow at the Stanford Digital Economy Lab, and Ruyu Chen, research scientist at the Stanford Digital Economy Lab, will presented the findings on their recent paper “Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence.” Watch the seminar below!

This paper examines changes in the labor market for occupations exposed to generative artificial intelligence using high-frequency administrative data from the largest payroll software provider in the United States. We present six facts that characterize these shifts. We find that since the widespread adoption of generative AI, early-career workers (ages 22-25) in the most AI-exposed occupations have experienced a 13 percent relative decline in employment even after controlling for firm-level shocks.

In contrast, employment for workers in less exposed fields and more experienced workers in the same occupations has remained stable or continued to grow. We also find that adjustments occur primarily through employment rather than compensation. Furthermore, employment declines are concentrated in occupations where AI is more likely to automate, rather than augment, human labor. Our results are robust to alternative explanations, such as excluding technology-related firms and excluding occupations amenable to remote work.

These six facts provide early, large-scale evidence consistent with the hypothesis that the AI revolution is beginning to have a significant and disproportionate impact on entry-level workers in the American labor market.

Bharat is a postdoctoral researcher at the Stanford Digital Economy Lab and Institute for Human-Centered Artificial Intelligence. He received his PhD in economics from Stanford GSB. His focus is on labor economics and technology.

Ruyu Chen is a research scientist at the Digital Economy Lab and the Stanford Institute for Human-Centered Artificial Intelligence (HAI). Her research lies at the intersection of the economics of innovation, information systems, and business strategy.

She focuses on two main areas: information technology adoption and firm performance, where she examines the drivers of IT adoption within firms and its impact on innovation and market performance; and AI and the future of work, where she leverages large-scale payroll data to study how emerging technologies, particularly generative AI, are reshaping employment, wages, skill demands, and organizational structures. Her work has been published in leading academic journals, including the Strategic Management Journal.

Before joining Stanford, she earned her PhD in Managerial Economics from the SC Johnson College of Business at Cornell University, with a graduate minor in Computer Science. She also holds a bachelor’s degree from Renmin University of China and studied as an exchange student at the University of Copenhagen.