ARTIFICIAL INTELLIGENCE IN ACCOUNTING EDUCATION: A BIBLIOMETRIC ANALYSIS OF GLOBAL RESEARCH TRENDS (2000–2025)
DOI:
https://doi.org/10.21512/jafa.v12i2.13441Keywords:
Bibliometric Analysis, Artificial Intelligence, Accounting Education, VOSviewer, ScopusAbstract
Artificial Intelligence (AI) applications are changing the structure of many professions, including accounting. The use of AI technologies has become a topic of great interest in relation to the teaching of accounting, as it fuels the accounting profession's need for innovations. This shift has not escaped the attention of academicians who have recognized its potential for further study, particularly from the perspective of the effectiveness of computer-aided learning. In this regard, the present study attempts to explore how this line of research has progressed by utilizing bibliometric methods, which a technique that quantitatively maps literature domains, identifiesinsightful patterns, and analyzes relationships across published works. The approach uses a multitude of documents published by various authors in a select range of years to modulate data trends. The research is motivated by the relative scarcity of knowledge on the metrics of AI-induced transformations in accounting education. It further seeks to develop a comprehensive description of global research on the relationship of AI and accounting education as it pertains to automated systems of accounting and management from the scope of international research from 2000 to 2025. From the Scopus database, the authors applied a sequence of well-defined keywords, which yielded 52 journal articles that were analyzed with VOSviewer software. They evaluated changes in the number of publications, recognized leading contributors, primary journals, research institutions, and new pillars of research. The data shows that there has been a consistent increase in academic productivity since 2021, with a noteworthy escalation over the last five years. This understanding is pertinent to stakeholders in research and teaching and emphasizes the value of integrated approaches in course planning and pedagogy for AI in accounting education. The elaborated dataset’s small size, however, does limit its scope, but serves as a preliminary framework for activity in this novel cross-disciplinary domain, and illustrates important gaps in knowledge which can be addressed later.References
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