Decoding the Intellectual Landscape and Evolving Research Paradigm of Artificial Intelligence in Environmental Sustainability

Artificial intelligence has emerged as a transformative tool in the rapidly evolving landscape of environmental sustainability. It has enabled significant advancements in smart, data-driven decision-making across sectors such as sustainable agriculture, renewable energy systems, disaster management, and climate change mitigation. This study conducts a scientometric analysis of peer-reviewed publications indexed in the Scopus database from 2015 to 2024. Publication and citation analysis, document co-citation networks, and thematic clustering were employed to explore knowledge patterns and identify emerging research themes. Additionally, the study also analyzed highly cited articles in each domain to uncover key intellectual contributions that have shaped the field. Results indicate a substantial increase in AI-based research activity, particularly in the climate and energy sectors, reflecting strong interdisciplinary integration. We observed bursts in citation activity for AI-driven approaches like disaster detection, digital twins, explainable AI, generative models, and load forecasting. The analysis further identifies the growing role of AI-IoT integration in real-time environmental sensing, precision irrigation, disaster early warning systems, and adaptive energy forecasting signaling in emergence as a critical future direction. Additionally, the study highlights Quantum AI hybrid models as a promising pathway for solving high-complexity environmental challenges. Overall, the findings provide valuable insights into the intellectual structure, thematic evolution, and future research trajectories shaping AI’s contribution to sustainable environmental systems.