The purpose of this study is to synthesize the rapidly expanding and fragmented literature on the role of artificial intelligence (AI) in sustainable development by mapping its intellectual structure and emerging research trajectories.
This is secondary research using bibliometric techniques. This study analyses 3,175 journal articles from the Scopus database (1991–2025). To account for the temporal dynamics of the field, co-citation analysis is applied to mature literature (1991–2022) to identify foundational knowledge structures, while co-word analysis is used for recent literature (2023–2025) to capture emerging themes and research directions.
The analysis reveals four major thematic clusters: predictive intelligence for sustainability, AI-driven decision systems, smart cities and urban intelligence and governance and ethics of AI. Additionally, emerging themes highlight the growing importance of technological innovation, environmental sustainability, analytical methodologies and development economics. The findings of this study indicate a shift in the literature from a technology-centric perspective toward a socio-technical view-point of AI in sustainability.
This study reconceptualizes AI as a multi-level, integrative capability embedded within organizational, ecological and institutional systems, thereby advancing existing theory through its linkage with resource-based, dynamic capabilities, institutional and socio-technical systems perspectives. The findings provide actionable insights for managers and policymakers by highlighting the role of AI in enabling data-driven decision-making, sustainable innovation and adaptive governance frameworks aligned with sustainable development goals.
By integrating co-citation and co-word analyses across a large data set, this study offers a comprehensive understanding of both the intellectual foundations and evolving research directions in AI-driven sustainability.
