Trends and insights from bibliometric analysis for mapping artificial intelligence and machine learning in sustainable development

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Use this study to identify leading institutions and emerging research clusters in AI for sustainability.

🏢実務担当者:Gain insights into proven AI/ML applications in energy, agriculture, and water management for corporate sustainability initiatives.

🏛政策担当者:Note the evidence for investing in digital infrastructure and international cooperation to accelerate sustainable development.

Abstract Rapid population growth, environmental degradation and persistent urgency of climate change have intensified the global search for sustainable development solutions. Governments, researchers and institutions alike face the challenge of balancing economic progress with social equity and environmental protection. In response, recent scholarships have increasingly turned to digital technologies as potential enablers of sustainable transformation. This study addresses the need to understand how artificial intelligence (AI) and machine learning (ML) are being incorporated into sustainable development strategies, with a particular focus on mapping knowledge trends and research patterns. Using bibliometric analysis of SCOPUS data spanning 2015 to 2024, the study uncovers the evolution of research topics, highlights influential authors and institutions, and traces the diffusion of ideas across disciplines. The findings reveal that AI and ML are emerging as key drivers of sustainability, with strong applications in energy and emission management, environmental monitoring, climate change mitigation, precision agriculture and water resource management. Research in this area has grown rapidly over the past decade, shifting from theory to real applications. It also highlights that China's and the United States dual dominance in both publication volume and citation impact, while also recognizing the contributions of other countries like India, the United Kingdom and Australia in shaping global research landscapes. Three main implications arise from these results. For policymakers, the evidence underscores the urgency of designing inclusive policies, investing in digital infrastructure, and fostering global cooperation to ensure the equitable distribution of technological benefits. For the research community, the study points to opportunities for cross-disciplinary collaborations that link technological innovation with real-world sustainability challenges. From a broader societal perspective, the findings emphasize the importance of knowledge sharing and technology transfer, enabling both developed and developing countries to advance collectively toward achieving the Sustainable Development Goals.

• openalex https://doi.org/10.1007/s43621-026-02611-4first seen 2026-05-17 04:37:44 · last seen 2026-05-27 04:29:54