Purpose – This study aims to examine the integration of Artificial Intelligence (AI) in Sustainability Reporting through bibliometric analysis. Design/methodology/approach – This study applies bibliometric analysis on 3,690 Scopus-indexeddocumentspublishedbetween1981and2025.UsingVOSviewerand Biblioshiny, the research maps publication trends, influential sources, collaboration networks, and thematic developments in AI and sustainability reporting. Findings – The analysis identified five distinct research clusters: operational sustainability,socialresponsibility,managementtheory,accountingframeworks,and strategic economics. A critical finding reveals that AI-related keywords remain peripheral within the sustainability reporting literature, indicating that the integration of AI in this field is still at a nascent stage of development.Originality/value – This study offers a comprehensive bibliometric mapping of the intersection between AI and sustainability reporting—an area that remains underexplored. By visualizing thematic structures and highlighting the marginal presence of AI-related concepts, the research provides novel insights into the intellectual gaps and sets a foundation for future empirical and theoretical developments in this emerging field. Research limitations/implications – This study is limited to publications indexed in the Scopus database and focuses on journal articles written in English, which may exclude relevant contributions from other sources or languages. Despite this limitation, the findings offer valuable implications for guiding future empirical research, supporting the development of standardized AI frameworks in sustainability reporting, and advancing theoretical discourse in this emerging interdisciplinary field. Keywords: Artificial Intelligence, Sustainability Reporting, Bibliometric Analysis, Knowledge Mapping,ArticleType:BibliometricReview