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Proceedings of the 4th International Conference on Image, Algorithms, and Artificial Intelligence, ICIAAI 2026, 22-24 May 2026, Singapore, Singapore

Research Article

The Application, Mechanisms, and Challenges of Artificial Intelligence in Sustainable Development

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  • @INPROCEEDINGS{10.4108/eai.22-5-2026.2365153,
        author={Shenrui  Li},
        title={The Application, Mechanisms, and Challenges of Artificial Intelligence in Sustainable Development},
        proceedings={Proceedings of the 4th International Conference on Image, Algorithms, and Artificial Intelligence, ICIAAI 2026, 22-24 May 2026, Singapore, Singapore},
        publisher={EAI},
        proceedings_a={ICIAAI},
        year={2026},
        month={8},
        keywords={Artificial Intelligence; Sustainable Development; Green Innovation; Energy Transition; Environmental Management},
        doi={10.4108/eai.22-5-2026.2365153}
    }
    
  • Shenrui Li
    Year: 2026
    The Application, Mechanisms, and Challenges of Artificial Intelligence in Sustainable Development
    ICIAAI
    EAI
    DOI: 10.4108/eai.22-5-2026.2365153
Shenrui Li1,*
  • 1: College of Electrical Engineering, Shanghai University of Electric Power, Shanghai, 201306, China
*Contact email: lishenrui07@gmail.com

Abstract

The global endeavor to advance sustainable development is confronted with formidable hurdles brought by climate change, environmental deterioration and resource depletion. Artificial intelligence has evolved into a pivotal transformative tool that propels sustainable transition across various core fields. This study synthesizes research findings to explore AI applications in corporate green technological innovation, energy system transformation, environmental functional material development, sustainable supply chain management and renewable energy optimization. It identifies the core mechanisms driving AI's sustainability effects, including financial facilitation, optimized resource allocation and predictive analytics. Meanwhile, the study reveals the differentiated impacts of AI adoption across diverse industries, regions and firm types, as well as critical challenges such as inferior data quality, sophisticated algorithm design and technological integration dilemmas. Future research directions centered on data standardization, explainable AI development and inclusive technology popularization are proposed to unlock the full transformative potential of AI for a more sustainable global future.

Keywords
Artificial Intelligence; Sustainable Development; Green Innovation; Energy Transition; Environmental Management
Published
2026-08-31
Publisher
EAI
http://dx.doi.org/10.4108/eai.22-5-2026.2365153
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