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How artificial intelligence drives industrial digitalization and greening synergies? Evidence from China's AI innovation and development pilot zones

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  • Kang, Shikang
  • Shang, Yu

Abstract

Artificial intelligence (AI) is increasingly emerging as a pivotal engine for promoting intelligent industrial production and facilitating regional industrial transformation and upgrading. Deep integration of AI with the industrial economy has been accelerated by the establishment of the National New Generation Artificial Intelligence Innovation and Development Pilot Zones (NewAI). However, it remains unclear how NewAI impacts industrial digitization and greening. This study assesses the impact of NewAI policies on industrial digitalization and greening synergy (IDG) with a dual machine learning model based on panel data from 30 provinces in China from 2010 to 2022. Some results are found as follows: (1) IDG increased overall from 0.357 to 0.559 in 30 Chinese provinces; (2) IDG is greatly impacted by NewAI, which is enhanced by 2.6 % on average; (3) NewAI can boost IDG by increasing the information enterprise density, reducing the degree of innovation resource mismatch, and enhancing the technological complexity of manufacturing exports. The role of NewAI is more evident in areas outside of Northeast China, high energy consumption and decarbonization regions, and areas with high green innovation resilience; and (4) advancements in AI technology can have a significant spatial spillover effect on IDG of this province and a favorable spillover effect on IDG of neighboring regions as well. This study confirms that AI plays a positive role in improving IDG and provides policy support for employing AI to promote new industrialization.

Suggested Citation

  • Kang, Shikang & Shang, Yu, 2025. "How artificial intelligence drives industrial digitalization and greening synergies? Evidence from China's AI innovation and development pilot zones," Technology in Society, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:teinso:v:83:y:2025:i:c:s0160791x25002015
    DOI: 10.1016/j.techsoc.2025.103011
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