AUTHOR=Yuan Qi , Ma Shuo , Yao Shanji 

TITLE=How does artificial intelligence enhance carbon productivity?—Mechanism pathways and threshold effects from a multidimensional perspective

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2025.1603633

DOI=10.3389/fenvs.2025.1603633

ISSN=2296-665X

ABSTRACT=Artificial intelligence (AI) provides novel technological pathways and research perspectives to mitigate global carbon emissions. This study empirically examines the impact of AI on carbon productivity utilizing panel data from 286 prefecture-level cities in China, covering the period from 2003 to 2021. The results indicate that AI enhances urban carbon productivity (CP). Mechanism analysis reveals that AI indirectly improves carbon productivity via industrial optimization and innovation promotion impacts, with environmental regulation (ER) and internet penetration (IP) rates serving as positive moderating factors in this process. A subsequent study reveals that the influences of AI, human capital (HC), and financial development (Fin) on carbon productivity display threshold effects marked by escalating marginal returns. Heterogeneity research indicates that the impact of AI on carbon production differs markedly across various resource endowments, city sizes, regions, and urban agglomerations. This study’s conclusions provide novel theoretical frameworks for implementing AI technology in carbon emission reduction and furnish critical insights for advancing low-carbon transitions.