The role of AI in reshaping productivity: A skill-based analysis from China

Norhanishah Mohamad Yunus ()

International Journal of Asian Social Science, 2026, vol. 16, issue 1, 18-28

Abstract: This study explores recent trends in artificial intelligence (AI) and labour economics by analysing how various AI applications affect labour productivity across different skill levels in China. Using data from 23 provinces between 2000 and 2020, the research employs three AI proxies: AI patent applications, investment in information transmission, computer services and software industries, and the intensity of scientific research funding. The study applies Ordinary Least Squares (OLS) estimation to assess the impact of these indicators on high-, medium-, and low-skilled occupations. Results show that all three AI proxies significantly and positively influence labour productivity across all skill groups. This challenges earlier research that largely focused on benefits to high-skilled workers, suggesting instead that AI-related investments also enhance productivity in medium- and low-skilled roles. These outcomes are likely driven by regional policy support and strategic investments in technology and innovation. The findings have important policy implications, particularly for designing targeted reskilling and upskilling programmes based on occupational skill levels. By identifying the specific AI investments that improve labour productivity, the study contributes valuable insights for fostering inclusive growth in an AI-driven economy, ensuring that technological benefits are distributed more equitably across the labour force.

Keywords: Artificial intelligence; ICT investment; Labour productivity; Panel data; Patent; Scientific research fund; Skill levels (search for similar items in EconPapers)
Date: 2026
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