Artificial Intelligence Development and Carbon Emission Intensity: Evidence from Industrial Robot Application

Xinlin Yan and Tao Sun ()
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Xinlin Yan: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Tao Sun: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China

Sustainability, 2025, vol. 17, issue 9, 1-16

Abstract: The development of artificial intelligence as the core driving force for industrial upgrading in the era of smart manufacturing and its large-scale application are reshaping the pattern of urban industrial production and energy consumption, with far-reaching impacts on the realization of regional carbon emission reduction targets. To effectively measure the impact of Artificial Intelligence Development Level (AIDL) on the Carbon Emission Intensity (ICE) of Chinese cities, this study empirically examines the influence of AI development level on carbon emission intensity using panel data from 275 Chinese cities during the period from 2007 to 2019. Employing a Spatial Durbin Model and a Mediation Effect Model to conduct empirical testing, the results reveal that AI development level has a negative impact on carbon emission intensity, thereby suppressing the increase in carbon emission intensity. AI development level mitigates carbon emission intensity through two pathways: enhancing the level of technological innovation and optimizing industrial structure, exhibiting a reverse mediation effect with impact coefficients of −0.6216 and −0.5682, respectively, both statistically significant at the 1% level. Based on the empirical findings and the mediation effect analysis, this paper proposes corresponding policy recommendations. This study highlights the critical role of advancements in artificial intelligence and the application strategies of smart industrial robots in fostering sustainable smart cities. The findings support further exploration of AI’s impact on the environment and offer new perspectives for achieving urban sustainability.

Keywords: AI development level; industrial robot; carbon emission intensity; the Spatial Durbin Model; intermediation effect (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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