ARTIFICIAL INTELLIGENCE IN ACCOUNTING: TECHNOLOGICAL INNOVATION, PROFESSIONAL TRANSFORMATION, AND HUMAN–AI INTERACTION
Keywords:
Artificial Intelligence, Accounting, Bibliometric Analysis, Digital Transformation, Human–AI Collaboration, Generative AIAbstract
Artificial Intelligence (AI) is rapidly reshaping the accounting profession, yet research in this domain remains fragmented across technical, organizational, and behavioral perspectives. This study provides a structured synthesis of AI-related accounting research by integrating bibliometric analysis and qualitative content analysis. Using research articles indexed in Scopus between 2017 and 2026, keyword co-occurrence mapping was conducted using VOSviewer, followed by in-depth thematic examination of representative studies aligned with identified clusters. The findings reveal three dominant research streams: (1) analytical and predictive applications of AI, emphasizing machine learning and decision-support systems; (2) professional and organizational transformation, focusing on digital transformation, governance, and role reconfiguration; and (3) education and human–AI interaction, driven by generative AI and large language models. Overlay visualization further demonstrates a temporal evolution from AI as computational infrastructure toward AI as an interactive collaborator embedded within professional and educational contexts. The study shows that AI augments rather than replaces accounting professionals, while trust, transparency, and capability development emerge as critical determinants of sustainable integration. By combining structural mapping with theory-driven synthesis, this review advances a multilevel sociotechnical understanding of AI in accounting and proposes a research agenda to guide future inquiry
References
Abbas, K. (2025). Management accounting and artificial intelligence: A comprehensive literature review and recommendations for future research. British Accounting Review. https://doi.org/10.1016/j.bar.2025.101551
Alles, M. G. (2015). Drivers of the use and facilitators and obstacles of the evolution of big data by the audit profession. Accounting Horizons, 29(2), 439–449. https://doi.org/10.2308/acch-51067
Appelbaum, D., Kogan, A., Vasarhelyi, M., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44. https://doi.org/10.1016/j.accinf.2017.03.003
Aziki, A., Khinibilla, H., Ilahiane, N., Ourrani, A., & Fadili, M. H. (2025). A theoretical exploration of how AI anthropomorphism influences chartered accountants’ acceptance. Procedia Computer Science, 257, 1067–1072. https://doi.org/10.1016/j.procs.2025.03.139
Aziki, A., Ourrani, A., & Fadili, M. H. (2024). Trust or Rust: The crucial role of trust in AI acceptance by professional accountants. Procedia Computer Science, 251, 186–191. https://doi.org/10.1016/j.procs.2024.11.100
Brynjolfsson, E. , & M. A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton.
Davenport, T. H., & Ronanki, R. (2018). Artificial Intelligence for the real world. Harvard Business Review.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. In Source: MIS Quarterly (Vol. 13, Number 3).
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Glikson, E., & Woolley, A. W. (2020). HumanTrust in Artificial Intelligence: Review Of Empirical Research. Academy of Management Annals. https://doi.org/https://doi.org/10.5465/annals.2018.0057
Grosu, V., Cosmulese, C. G., Socoliuc, M., Ciubotariu, M. S., & Mihaila, S. (2023). Testing accountants’ perceptions of the digitization of the profession and profiling the future professional. Technological Forecasting and Social Change, 193. https://doi.org/10.1016/j.techfore.2023.122630
Januszewski, A., & Pietrysiak, A. (2025). Impact of Digital Transformation on Accounting Profession in the Opinions of Accounting Firms’ Employees. Procedia Computer Science, 270, 2386–2397. https://doi.org/10.1016/j.procs.2025.09.360
Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122. https://doi.org/10.2308/jeta-51730
Krippendorff, Klaus. (2004). Content analysis : an introduction to its methodology. Sage.
Maulana, A., Fenitra, R. M., Sutrisno, S., & Kurniawan. (2025). Artificial intelligence, job seeker, and career trajectory: How AI-based learning experiences affect commitment of fresh graduates to be an accountant? Computers and Education: Artificial Intelligence, 8. https://doi.org/10.1016/j.caeai.2025.100413
Mayring, P. (2014). Qualitative Content Analysis Theoretical Foundation, Basic Procedures and Software Solution. Klagenfurt. www.beltz.de
Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. British Accounting Review, 51(6). https://doi.org/10.1016/j.bar.2019.04.002
Murphy, B., Feeney, O., Rosati, P., & Lynn, T. (2024). Exploring accounting and AI using topic modelling. International Journal of Accounting Information Systems, 55. https://doi.org/10.1016/j.accinf.2024.100709
Orlikowski, W. J. (1992). The Duality Of Technology : Rethinking The Concept Of Technology In Organizations. Organization Science, 3 (3), 398–247.
Orlikowski, W. J., & Scott, S. V. (2008). 10 Sociomateriality: Challenging the Separation of Technology, Work and Organization. The Academy of Management Annals, 2(1), 433–474. https://doi.org/10.1080/19416520802211644
Rai, A. (2020). Explainable AI: from black box to glass box. In Journal of the Academy of Marketing Science (Vol. 48, Number 1, pp. 137–141). Springer. https://doi.org/10.1007/s11747-019-00710-5
Rautiainen, A., Scapens, R. W., Järvenpää, M., Auvinen, T., & Sajasalo, P. (2024). Towards fluid role identity of management accountants: A case study of a Finnish bank. British Accounting Review, 56(4). https://doi.org/10.1016/j.bar.2024.101341
Russell, S., & Norvig, P. (2022). Artificial Intelligence A Modern Approach Fourth Edition Global Edition. Pearson.
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Sun, T. & V. M. A. (2017). Deep learning and the future of auditing. The CPA Journal. https://www.cpajournal.com/2017/06/19/deep-learning-future-auditing/
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review *. British Journal of Management, 14(3), 207–222.
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. In Source: MIS Quarterly (Vol. 27, Number 3).
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. In Journal of Strategic Information Systems (Vol. 28, Number 2, pp. 118–144). Elsevier B.V. https://doi.org/10.1016/j.jsis.2019.01.003
Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
