Chapter 7: The Evolution of Artificial Intelligence in Financial Reporting: A Bibliometric Analysis

This chapter reports on a bibliometric analysis of publications included in the Scopus database for the period 2015–2025, to map out the academic landscape of research on artificial intelligence (AI) in financial reporting. The total number of documents examined was 717 documents in order to have an evidence-based research account for the mapping of networks of collaboration, evolving themes of research and the intellectual structure. The data extraction uses a software program called VOSviewer to visualize and map networks. The data extraction and resulting analysis allows for the identification of leading authors, institutions, and lines of inquiry. The findings reveal a strong growth in publications starting in 2018, with the United States, China, and India emerging as the most prolific contributors. Key authors who published the most documents were mostly one-time authors but included M.M. Fouda, P. Hajek, and K. Hussainey, and the most popular themes of research included neural networks, financial markets, and forecasting. The findings also highlighted some structural weaknesses to international collaboration (e.g., fragmentation of authorship), and few researchers explored the ethical and regulatory dimensions. This information will assist academics, practitioners, and public policymakers to move beyond discussion to the strategic and responsible use of AI in financial reporting.