Artificial intelligence, green innovation, and regional carbon inequality

Evidence from Chinese provincial data

Bibliographic Data

ID17832174
AuthorsXiangjun Fan (Nanjing University, corresponding author)
Year2026
Publication date2026-03-30
Open AccessYes
TypeARTICLE
VenueHumanities and Social Sciences Communications (JOURNAL)
Journal identifiersISSN: 2662-9992 • E-ISSN: 2662-9992
PublisherPalgrave Macmillan (PUBLISHER • GB)
DOI10.1057/s41599-026-07053-x
OpenAlexW7143326024
LanguageEN
References cited40

China’s pursuit of carbon peaking and carbon neutrality has heightened the urgency of addressing regional differences in carbon emissions. While artificial intelligence (AI) is increasingly regarded as a transformative force for industrial upgrading and environmental management, its impact on the spatial distribution of carbon emissions remains insufficiently understood. This study empirically examines how AI development and green innovation affect carbon inequality using a provincial panel dataset spanning 2003–2021. Carbon inequality is measured using both the Gini index and the Theil index to capture different dimensions of regional disparities. The results reveal three main findings. First, AI development significantly reduces carbon inequality, particularly when measured by the Gini index. This effect operates primarily through improved energy efficiency, enhanced environmental monitoring, and more efficient resource allocation, thereby disproportionately benefiting lagging regions and helping narrow interprovincial emission gaps. However, the inequality-reducing impact of AI is weaker when assessed using the Theil index, suggesting that deep-rooted structural divides between advanced and less developed regions remain difficult to overcome. Second, green innovation does not yet significantly reduce carbon inequality, largely because innovative activities are concentrated in coastal provinces and have not effectively diffused to inland areas. Overall, this study provides new insights into the mechanisms through which digital technologies shape environmental inequality and highlights the importance of coordinated digital green development strategies to promote a more balanced and inclusive transition toward China’s dual-carbon goals

Carbon fibers · Gini coefficient · Green growth · Greenhouse gas · Inequality · Lagging · Theil index · Energy, Environment, Economic Growth · Environmental Impact and Sustainability · Land Use and Ecosystem Services

Tools

Open DOIOpen Access