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| Title | The Impact Of Artificial Intelligence On The Sustainability Of Regional Ecosystems: Current Challenges And Future Prospects |
|---|---|
| ID_Doc | 55684 |
| Authors | Pimenow S.; Pimenowa O.; Prus P.; Niklas A. |
| Year | 2025 |
| Published | Sustainability (Switzerland), 17, 11 |
| DOI | http://dx.doi.org/10.3390/su17114795 |
| Abstract | The integration of artificial intelligence (AI) technologies is reshaping diverse domains of human activity, including natural resource management, urban and rural planning, agri-food systems, industry, energy, education, and healthcare. However, the impact of AI on the sustainability of local ecosystems remains insufficiently systematized. This highlights the need for a comprehensive review that considers spatial, sectoral, and socio-economic characteristics of regions, as well as interdisciplinary approaches to sustainable development. This study presents a scoping review of 198 peer-reviewed publications published between 2010 and March 2025, focusing on applied cases of AI deployment in local contexts. Special attention is given to the role of AI in monitoring water, forest, and agricultural ecosystems, facilitating the digital transformation of businesses and territories, assessing ecosystem services, managing energy systems, and supporting educational and social sustainability. The review includes case studies from Africa, Asia, Europe, and Latin America, covering a wide range of technologies—from machine learning and digital twins to IoT and large language models. Findings indicate that AI holds significant potential for enhancing the efficiency and adaptability of local systems. Nevertheless, its implementation is accompanied by notable risks, including socio-economic disparities, technological inequality, and institutional limitations. The review concludes by outlining research priorities for the sustainable integration of AI into local ecosystems, emphasizing the importance of cross-sectoral collaboration and scientific support for regional digital transformations. © 2025 by the authors. |
| Author Keywords | agricultural sustainability; artificial intelligence; climate change adaptation; ecosystem services; environmental monitoring; machine learning; regional ecosystems; smart agriculture; smart cities and villages; sustainable development |
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