The Effect of Artificial Intelligence (AI) on Firm Labor Structure

Xue, Mei
Cao, Xing
Feng, Xu
Gu, Bin
Zhang, Yongjie
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This paper aims to study the effect of AI on firm labor structure. Using a unique panel data of over 1300 publicly listed companies in China from 2007 to 2018, we study the effect of AI on firms’ labor composition measured by labor force’s education levels. We further compare the effect of AI on firms in the manufacturing sector to the effect on firms in the service sector. Our analysis generates two major findings. First, the use of AI leads to a larger labor demand increase for jobs requiring lower education levels than those requiring higher education levels. Second, the effect is stronger in the service sector than in the manufacturing sector. These findings contradict predictions of the “skill-biased technological change” (SJTB) and U-shaped “job polarization” effects proposed in the prior literature. We propose that “technology-enabled deskilling” effect is driving the effect of AI on labor structure.
Strategy, Information, Technology, Economics, and Society (SITES), artificial intelligence, labor structure, technology-enabled deskilling
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