A bibliometric exploration of big data analytics and artificial intelligence in accounting research - Singh, Ashutosh; Pahwa, Manvinder Singh; Kumar, Pushpendra (International journal of economic perspectives, 2026)
This bibliometric study aims to map the intellectual structure and evolution of BDA and AI accounting research and analyze the current research trends and future developments in this domain. Furthermore, the goals of the current study were to conduct a global analysis of published research, provide an overview of top authors, countries, and journals, and outline the major themes in the literature to help identify important areas of inquiry moving forward. To conduct this exploratory bibliometric research design, we used PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) as our methodological framework. Using the Dimensions database, 1,181 open-access articles published between 2021 and 2025 were analyzed to identify, screen, and select studies. Citation analysis, co-authorship networks, keyword co-occurrence, and bibliographic coupling were performed using VOSviewer to identify the Conceptual and Intellectual Structures of Technology-Enabled Accounting (TEA). Bibliometric Trends by 2024 will indicate a massive growth in Academic Research for Technology-Enabled Accounting (TEA), as shown by a growing number of Academic Articles focused on Technology Enabled Accounting. The main areas discussed were: Automation of the Current Audit Process, Detection of Fraud, Predictive Analytics, and Ethical Issues Related to Artificial Intelligence. This Analysis suggests that Technology Enabled Accounting (TEA) is Changing the Way Accounting Function Will Occur in the Future, with a Greater Focus on Predicting Future Outcomes using data. Strong governance and ethical controls are essential as companies increase their use of BDA and AI technologies.