Artificial Intelligence in Accounting Research: A Bibliometric Mapping and the Positioning of Sustainability and ESG Reporting

Abstract

This paper examines how artificial intelligence has entered the accounting literature on sustainability and ESG reporting. It maps that literature by identifying the major research themes, conceptual relationships, and theoretical gaps, drawing on 277 articles indexed in Scopus between 2000 and 2026 and analyzed through bibliometric performance analysis and science mapping in Bibliometrix and VOSviewer. Citation analysis, keyword co-occurrence networks, and thematic clustering are used to trace the direction of the field's growth. The analysis shows that publication activity has accelerated sharply since 2021, concentrated on auditing, generative AI and large language model applications, blockchain, and machine learning. On the other hand, research on sustainability and ESG reporting including greenwashing detection, disclosure quality, and carbon reporting, remains almost absent from the field's citation structure. The literature's theoretical base rests heavily on institutional theory and legitimacy theory. These findings are limited by the database coverage and search string used. Standard-setters should recognize the role of AI in sustainability assurance, and practitioners should consider how far to trust automated ESG reporting tools. Unlike prior bibliometric reviews of AI in accounting, this study focuses on sustainability and ESG reporting.