{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T02:07:02Z","timestamp":1768961222571,"version":"3.49.0"},"reference-count":58,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Systems"],"abstract":"<jats:p>The emergence of artificial intelligence as a transformative force in the field of information technology has exerted a significant impact on the development of renewable energy. In-depth analysis of the impact of AI on renewable energy development is crucial for promoting energy transition and facilitating sustainable development. This research utilizes a dataset comprising 30 provincial panels spanning from 2010 to 2023. This study found that AI technology can promote renewable energy development, a conclusion that still holds after robustness and endogeneity tests. An examination of the mechanism reveals that AI technology facilitates the advancement of renewable energy through the enhancement of trade openness and the concentration of manufacturing activities. The analysis of the moderating effect indicates that environmental regulation and environmental protection expenditures positively moderated the relationship between AI technology and renewable energy development and climate policy uncertainty negatively moderated the relationship between AI technology and renewable energy development. Further analysis revealed that AI technology has the potential to substantially improve the development of local renewable energy resources while also facilitating the advancement of renewable energy in adjacent areas, exhibiting spatial spillover effects. This study verifies the positive effects of AI technology on renewable energy development and enriches existing research perspectives in the field of energy economics.<\/jats:p>","DOI":"10.3390\/systems14010107","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T13:02:07Z","timestamp":1768914127000},"page":"107","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How Artificial Intelligence Technology Enables Renewable Energy Development: Heterogeneity Constraints on Environmental and Climate Policies"],"prefix":"10.3390","volume":"14","author":[{"given":"Xian","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Public Administration, South China University of Technology, Guangzhou 510220, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jincheng","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Public Policy, South China University of Technology, Guangzhou 510220, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"105715","DOI":"10.1016\/j.eneco.2021.105715","article-title":"Is Smart Transportation Associated with Reduced Carbon Emissions? 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