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Article

How Does AI Technology Innovation Boost Carbon Productivity? Evidence from China

1
School of Economics, Peking University, Beijing 100871, China
2
Postdoctoral Research Station, China CITIC Financial Asset Management Co., Ltd., Beijing 100033, China
3
School of Statistics, University of International Business and Economics, Beijing 100029, China
4
Civil Aviation Authority, Muscat 00968, Oman
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sustainability 2026, 18(10), 4984; https://doi.org/10.3390/su18104984 (registering DOI)
Submission received: 26 March 2026 / Revised: 6 May 2026 / Accepted: 13 May 2026 / Published: 15 May 2026

Abstract

As a key indicator of low-carbon economic transformation, the influencing factors of carbon productivity (CP) have attracted considerable academic attention. However, the study of the role of artificial intelligence (AI) technology innovation is comparatively confined. Using China’s prefecture-level-and-above cities as the sample, this study measures regional AI technology innovation based on AI patent stocks and empirically examines its impact on carbon productivity. The principal findings of this paper are as follows: (1) AI technology innovation boosts urban carbon productivity through three channels: enhancing green innovation, reducing transaction costs, and increasing AI attention. (2) The regional heterogeneity analysis shows that this positive impact of AI technology innovation on carbon productivity exerts a stronger facilitating effect on eastern regions, resource-dependent cities, and central cities. The heterogeneity analysis at the technological level further provides evidence of the effect of AI technology innovation on carbon productivity varying along different tiers of technological development, innovation mode, and innovation role. (3) The analysis identifies the energy structure as a pivotal threshold variable governing the efficacy of AI innovation in bolstering carbon productivity. Notably, crossing the threshold of clean energy penetration triggers an escalating positive feedback loop between AI innovation and carbon productivity. (4) Estimation of temporal effect dynamics via non-parametric panel model shows that the impact of AI technology innovation on CP exhibits phased characteristics. The coefficient became significantly positive in 2010 and peaked in 2015, after which its effect gradually weakened. This study provides comprehensive empirical evidence for understanding the relationship between AI technology innovation and CP and provides policy references for the use of AI technology to promote the coordinated achievement of economic growth and carbon reduction.
Keywords: carbon productivity; AI technology innovation; mechanism analysis; heterogeneity analysis; time-varying effect carbon productivity; AI technology innovation; mechanism analysis; heterogeneity analysis; time-varying effect

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MDPI and ACS Style

Du, Z.; Luo, S.; Alhidi, A.M.; Zhao, L. How Does AI Technology Innovation Boost Carbon Productivity? Evidence from China. Sustainability 2026, 18, 4984. https://doi.org/10.3390/su18104984

AMA Style

Du Z, Luo S, Alhidi AM, Zhao L. How Does AI Technology Innovation Boost Carbon Productivity? Evidence from China. Sustainability. 2026; 18(10):4984. https://doi.org/10.3390/su18104984

Chicago/Turabian Style

Du, Zhihui, Shuang Luo, Amal Mubarak Alhidi, and Liuyan Zhao. 2026. "How Does AI Technology Innovation Boost Carbon Productivity? Evidence from China" Sustainability 18, no. 10: 4984. https://doi.org/10.3390/su18104984

APA Style

Du, Z., Luo, S., Alhidi, A. M., & Zhao, L. (2026). How Does AI Technology Innovation Boost Carbon Productivity? Evidence from China. Sustainability, 18(10), 4984. https://doi.org/10.3390/su18104984

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