Generative AI in Accounting Publishing: A Bibliometric and Thematic Analysis of Author Guidelines with Governance and Ethical Considerations

Abstract

This study addresses a gap in accounting scholarship by examining how journals listed in the Australian Business Deans Council (ABDC) Journal Quality List approach the use of generative artificial intelligence (AI) tools in scholarly publishing. We employed a two-phase methodology: a structured bibliometric review to map journal characteristics and a thematic content analysis to interpret AI-related author guidelines. Ninety-one A*, A, and B-ranked journals classified under Accounting (FoR 3501) were examined. The findings revealed inconsistent expectations across the discipline due to fragmented journal policies on AI use. This fragmented policy landscape creates ethical ambiguities and challenges for authors, editors, and institutions seeking to ensure responsible and transparent research practices.

To address these gaps, the study proposes a governance-oriented framework for responsible AI use in accounting publishing. The framework includes: (1) standardised disclosure protocols for AI-assisted content, (2) criteria distinguishing acceptable from unacceptable AI applications, (3) procedures for identifying and managing potential misuse, and (4) integration of AI ethics into editorial and peer review practices. By aligning journal policies with principles of transparency, accountability, fairness, and integrity, the framework supports the development of coherent, discipline-specific standards. This research contributes to the advancement of ethical scholarship and informs broader discussions on AI governance in academic and professional contexts.