The Cross Section of AI and Sustainability: Extensive Topic Modeling of Ten Years of Research

The rapid advancements in artificial intelligence (AI) are driving innovation and providing new tools to enhance sustainable practices across various domains. However, the swift progression of AI also presents new sustainability challenges, particularly concerning its carbon footprint and resource consumption. To explore the complex research landscape at the intersection of AI and sustainability, this study utilized topic modeling on research papers in the field. Using an AI-based topic modeling tool, 4,541 research abstracts published from 2015 to 2024 were processed. This approach identified 67 distinct topics, each characterized by unique keywords and associated publications. The findings illustrate a consistent expansion in research areas and a significant recent surge in publications, particularly in topics such as ‘Large Language Models’ and ‘Generative Art and Design.’ By organizing topics into the quadrants of a BCG-like matrix considering both topic size and growth, the study offers balanced insights into the dynamic landscape of the field. Furthermore, hierarchical clustering was applied to the 67 topics to reveal the interrelationships among them and identify broader and major research themes. This study advances our understanding of the relationship between AI and sustainability by highlighting both established and emerging areas of research and elucidating the evolving nature of the field.