Utilization of artificial intelligence in organizational sustainable development: bibliometric analysis and future research directions

The paper aims to conduct a bibliometric analysis to investigate the utilization of artificial intelligence in organizational sustainable development.Design/methodology/approach: This study uses bibliometric analysis to evaluate literature on artificial intelligence in organizational sustainable development.By applying quantitative and qualitative methods, it identifies key trends, influential works, and research gaps.Data were collected from the Scopus database using keywords like "artificial intelligence", "sustainability", and "organization" resulting in a dataset of 217 relevant journal articles and conference papers published up to March 11, 2025.Findings: The study highlights increasing scholarly interest in artificial intelligence's role in organizational sustainable development, with a significant rise in publications over the last decade.Geographical analysis shows the United States, China, and Germany as leading contributors.Keyword co-occurrence reveals prominent themes like AI-driven decisionmaking and predictive analytics, but also points to a lack of empirical studies on AI's long-term impacts.A conceptual model linking AI adoption factors to sustainability outcomes is proposed to guide future research.Research limitations/implications: This study exclusively utilizes the Scopus database, which, despite its comprehensiveness, excludes other significant sources such as Web of Science, Google Scholar, and specialized databases focused on sustainability and technology.This limitation may result in the omission of pertinent research.Furthermore, the search strategy's reliance on the specific keywords "artificial intelligence", "sustainability", and "organization" could have inadvertently excluded relevant studies addressing AI's role in sustainability that do not explicitly use these terms.Practical implications: The findings highlight the need for organizations to develop strategic approaches for integrating AI into sustainability initiatives, ensuring that technological advancements align with environmental, social, and economic goals.Social implications: AI-driven sustainability initiatives have the potential to enhance social well-being by promoting ethical labor practices, improving resource distribution, and fostering inclusive economic growth.However, the uneven adoption of AI across industries and regions may deepen existing inequalities, particularly for small businesses and developing economies with limited access to advanced technologies.Originality/value: This study provides a comprehensive bibliometric analysis of AI's role in organizational sustainable development, offering a structured overview of key research trends, influential studies, and emerging thematic areas.