Main Article Content
Abstract
This study explores the collection of research articles on AI in an accounting context, particularly on publications covering business, management, and accounting. We analyzed nearly 40 years of research history, attempting to identify relevant publications from the earliest to most recent in the data retrieved from the database and reviewed in this study. A systematic literature review is conducted to analyze 78 selected articles retrieved from the Scopus Database over the last four decades. Content analysis is applied to identify prospective future research avenues. The findings show a significant growth of articles in the last decade (2011 and after). This fact confirms that AI is becoming one of the main spotlights in accounting research. The results reveal that the current discussion of AI in the accounting literature is dominated by studies around the AI approach, with much conversation on auditing and financial accounting topics about AI technology. We suggest that future accounting studies be conducted more at the AI task and application levels. This study also marked topics in the accounting fields rarely discussed about AI, including public sector accounting and accounting education. This study clusters the literature into the accounting domains (auditing, finance, managerial, tax, and accounting information systems) and the AI technology domains (approach, tasks, and applications).
Keywords
Article Details
Copyright (c) 2026 Jurnal Akuntansi dan Auditing Indonesia

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
References
- Abukhader, S. M. (2021). Extent of artificial intelligence into accounting and auditing work - an analytical attempt of job and duties. International Journal of Business Process Integration and Management, 1(1), 1. https://doi.org/10.1504/IJBPIM.2021.10037973
- Ackerman, J. L. (2023, August 1). Artificial intelligence may be coming sooner than expected. The CPA Journal. https://www.cpajournal.com/2023/08/01/artificial-intelligence-may-be-coming-sooner-than-expected/
- Adekoya, O. B., Oliyide, J. A., Saleem, O., & Adeoye, H. A. (2022). Asymmetric connectedness between Google-based investor attention and the fourth industrial revolution assets: The case of FinTech and Robotics & Artificial intelligence stocks. Technology in Society, 68, 101925. https://doi.org/10.1016/j.techsoc.2022.101925
- Agustí, M. A., & Orta-Pérez, M. (2023). Big data and artificial intelligence in the fields of accounting and auditing: A bibliometric analysis. Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, 52(3), 412–438. https://doi.org/10.1080/02102412.2022.2099675
- Akerkar, R. (2019). Artificial intelligence for business. Springer International Publishing. https://doi.org/10.1007/978-3-319-97436-1
- Anggraini, P. G., & Sholihin, M. (2023). What do we know about managerial ability? A systematic literature review. Management Review Quarterly, 73(1), 1–30. https://doi.org/10.1007/s11301-021-00229-6
- Ardichvili, A. (2022). The impact of artificial intelligence on expertise development: Implications for HRD. Advances in Developing Human Resources, 24(2), 78–98. https://doi.org/10.1177/15234223221077304
- Armstrong, B., & Lee, G. J. (2021). Introduction to digital business. Silk Route Press.
- Arnaboldi, M., de Bruijn, H., Steccolini, I., & Van der Voort, H. (2022). On humans, algorithms and data. Qualitative Research in Accounting & Management, 19(3), 241–254. https://doi.org/10.1108/QRAM-01-2022-0005
- Arora, M., & Sharma, R. L. (2023). Artificial intelligence and big data: Ontological and communicative perspectives in multi-sectoral scenarios of modern businesses. Foresight, 25(1), 126–143. https://doi.org/10.1108/FS-10-2021-0216
- Atayah, O. F., & Alshater, M. M. (2021). Audit and tax in the context of emerging technologies: A retrospective analysis, current trends, and future opportunities. The International Journal of Digital Accounting Research, 95–128. https://doi.org/10.4192/1577-8517-v21_4
- Bakarich, K. M., & O’Brien, P. E. (2021). The robots are coming …but aren’t here yet: The use of artificial intelligence technologies in the public accounting profession. Journal of Emerging Technologies in Accounting, 18(1), 27–43. https://doi.org/10.2308/JETA-19-11-20-47
- Baldwin-Morgan, A. A. (1995). Integrating artificial intelligence into the accounting curriculum. Accounting Education, 4(3), 217–229. https://doi.org/10.1080/09639289500000026
- Birnberg, J. G., & Shields, M. D. (1984). The role of attention and memory in accounting decisions. Accounting, Organizations and Society, 9(3–4), 365–382. https://doi.org/10.1016/0361-3682(84)90020-5
- Bose, S., Kumar Dey, S., & Bhattacharjee, S. (2023). Big data, data analytics and artificial intelligence in accounting: An overview. In Handbook of Big Data Research Methods (pp. 32–51). Edward Elgar Publishing. https://doi.org/10.4337/9781800888555.00007
- Boussabaine, A. H., & Kaka, A. P. (1998). A neural networks approach for cost flow forecasting. Construction Management and Economics, 16(4), 471–479. https://doi.org/10.1080/014461998372240
- Bracci, E. (2023). The loopholes of algorithmic public services: An “intelligent” accountability research agenda. Accounting, Auditing & Accountability Journal, 36(2), 739–763. https://doi.org/10.1108/AAAJ-06-2022-5856
- Caner, S., & Bhatti, F. (2020). A conceptual framework on defining businesses strategy for artificial intelligence. Contemporary Management Research, 16(3), 175–206. https://doi.org/10.7903/cmr.19970
- Chang, Y.-T., & Stone, D. N. (2019). Why does decomposed audit proposal readability differ by audit firm size? A Coh-Metrix approach. Managerial Auditing Journal, 34(8), 895–923. https://doi.org/10.1108/MAJ-02-2018-1789
- Choi, S. U., Lee, K. C., & Na, H. J. (2022). Exploring the deep neural network model’s potential to estimate abnormal audit fees. Management Decision, 60(12), 3304–3323. https://doi.org/10.1108/MD-07-2021-0954
- Chukwuani, V. (2025). The ethical dilemma of AI-driven accounting: Balancing automation and professional judgment. International Journal of Financial Economics and Accounting, 5(2), 1–9. https://doi.org/10.5281/zenodo.15141882
- Cooper, H. B., Ewing, M. T., & Mishra, S. (2022). Text-mining 10-K (annual) reports: A guide for B2B marketing research. Industrial Marketing Management, 107, 204–211. https://doi.org/10.1016/j.indmarman.2022.10.001
- Damerji, H., & Salimi, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting. Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
- De Villiers, R. (2021). Seven principles to ensure future-ready accounting graduates – a model for future research and practice. Meditari Accountancy Research, 29(6), 1354–1380. https://doi.org/10.1108/MEDAR-04-2020-0867
- Deloitte. (2023). Discover applications and benefits for AI in the public sector.
- Diab, A., Abdelazim, S. I., & Metwally, A. B. M. (2023). The impact of institutional ownership on the value relevance of accounting information: Evidence from Egypt. Journal of Financial Reporting and Accounting, 21(3), 509–525. https://doi.org/10.1108/JFRA-05-2021-0130
- Elliot, V. H., Paananen, M., & Staron, M. (2020). Artificial intelligence for decision-makers. Journal of Emerging Technologies in Accounting, 17(1), 51–55. https://doi.org/10.2308/jeta-52666
- Elliott, R. K. (1986). Auditing in the 1990s: Implications for education and research. California Management Review, 28(4), 89–97. https://doi.org/10.2307/41165218
- Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27(3), 938–985. https://doi.org/10.1007/s11142-022-09697-x
- Goldwater, P. M., & Fogarty, T. J. (2007). Protecting the solution: A ‘High-Tech.’ method to guarantee individual effort in accounting classes. Accounting Education, 16(2), 129–143. https://doi.org/10.1080/09639280701234344
- Grüning, M. (2011). Artificial Intelligence Measurement of Disclosure (AIMD). European Accounting Review, 20(3), 485–519. https://doi.org/10.1080/09638180.2011.585792
- Haenlein, M., & Kaplan, A. (2021). Artificial intelligence and robotics: Shaking up the business world and society at large. Journal of Business Research, 124, 405–407. https://doi.org/10.1016/j.jbusres.2020.10.042
- Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. https://doi.org/10.1016/j.accinf.2022.100598
- Holmes, A. F., & Douglass, A. (2022). Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. Journal of Emerging Technologies in Accounting, 19(1), 53–68. https://doi.org/10.2308/JETA-2020-054
- Hossain, M. A., Agnihotri, R., Rushan, M. R. I., Rahman, M. S., & Sumi, S. F. (2022). Marketing analytics capability, artificial intelligence adoption, and firms’ competitive advantage: Evidence from the manufacturing industry. Industrial Marketing Management, 106, 240–255. https://doi.org/10.1016/j.indmarman.2022.08.017
- Indarti, N., Lukito-Budi, A. S., & Islam, A. M. (2020). A systematic review of halal supply chain research: To where shall we go? Journal of Islamic Marketing, 12(9), 1930–1949. https://doi.org/10.1108/JIMA-05-2020-0161
- Johnson, B. G., Phillips, F., & Chase, L. G. (2009). An intelligent tutoring system for the accounting cycle: Enhancing textbook homework with artificial intelligence. Journal of Accounting Education, 27(1), 30–39. https://doi.org/10.1016/j.jaccedu.2009.05.001
- Juszczyk, M., Zima, K., & Lelek, W. (2019). Forecasting of sports fields construction costs aided by ensembles of neural networks. Journal of Civil Engineering and Management, 25(7), 715–729. https://doi.org/10.3846/jcem.2019.10534
- Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2023). Artificial intelligence and HRM: Identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 73(2), 455–493. https://doi.org/10.1007/s11301-021-00249-2
- Keding, C. (2021). Understanding the interplay of artificial intelligence and strategic management: four decades of research in review. Management Review Quarterly, 71(1), 91–134. https://doi.org/10.1007/s11301-020-00181-x
- Kend, M., & Nguyen, L. A. (2020). Big data analytics and other emerging technologies: The impact on the Australian audit and assurance profession. Australian Accounting Review, 30(4), 269–282. https://doi.org/10.1111/auar.12305
- Kim, K. S. (2005). Examining corporate bankruptcy: An artificial intelligence approach. International Journal of Business Performance Management, 7(3), 241–254.
- 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
- Kokina, J., Pachamanova, D., & Corbett, A. (2017). The role of data visualization and analytics in performance management: Guiding entrepreneurial growth decisions. Journal of Accounting Education, 38, 50–62. https://doi.org/10.1016/j.jaccedu.2016.12.005
- Kommunuri, J. (2022). Artificial intelligence and the changing landscape of accounting: A viewpoint. Pacific Accounting Review, 34(4), 585–594. https://doi.org/10.1108/PAR-06-2021-0107
- Korhonen, T., Selos, E., Laine, T., & Suomala, P. (2020). Exploring the programmability of management accounting work for increasing automation: An interventionist case study. Accounting, Auditing & Accountability Journal, 34(2), 253–280. https://doi.org/10.1108/AAAJ-12-2016-2809
- Korol, V., Dmytryk, O., Karpenko, O., Riadinska, V., Basiuk, O., Kobylnik, D., Moroz, V., Safronova, O., Alisov, E., & Mishchenko, T. (2022). Elaboration of recommendations on the development of the state internal audit system when applying the digital technologies. Eastern-European Journal of Enterprise Technologies, 1(13(115)), 39–48. https://doi.org/10.15587/1729-4061.2022.252424
- Le Guyader, L. P. (2020). Artificial intelligence in accounting: GAAP’s “FAS133.” Journal of Corporate Accounting & Finance, 31(3), 185–189. https://doi.org/10.1002/jcaf.22407
- Lee, C. S., & Tajudeen, F. P. (2020). Usage and impact of artificial intelligence on accounting: Evidence from Malaysian organisations. Asian Journal of Business and Accounting, 13(1), 213–240. https://doi.org/10.22452/ajba.vol13no1.8
- Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Artificial intelligence based decision-making in accounting and auditing: Ethical challenges and normative thinking. Accounting, Auditing & Accountability Journal, 35(9), 109–135. https://doi.org/10.1108/AAAJ-09-2020-4934
- Leitner-Hanetseder, S., & Lehner, O. M. (2023). AI-powered information and Big Data: Current regulations and ways forward in IFRS reporting. Journal of Applied Accounting Research, 24(2), 282–298. https://doi.org/10.1108/JAAR-01-2022-0022
- Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201
- Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911–926. https://doi.org/10.1016/j.jbusres.2020.11.001
- Mahroof, K. (2019). A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse. International Journal of Information Management, 45, 176–190. https://doi.org/10.1016/j.ijinfomgt.2018.11.008
- Mancini, D., Lombardi, R., & Tavana, M. (2021). Four research pathways for understanding the role of smart technologies in accounting. Meditari Accountancy Research, 29(5), 1041–1062. https://doi.org/10.1108/MEDAR-03-2021-1258
- McCarthy, J., Minsky, M., Rochester, N., & Shannon, C. (1995). A proposal for the Dartmouth summer research project on Artificial Intelligence. AI Magazine, 27, 12–14.
- Mishra, S., Ewing, M. T., & Cooper, H. B. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 50(6), 1176–1197. https://doi.org/10.1007/s11747-022-00876-5
- Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. The British Accounting Review, 51(6), 100833. https://doi.org/10.1016/j.bar.2019.04.002
- Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
- Mosteanu, N. R., & Faccia, A. (2020). Digital Systems and New Challenges of Financial Management – FinTech, XBRL, Blockchain, and Cryptocurrencies. Quality - Access to Success, 21, 159–166.
- Muehlmann, B. W., Chiu, V., & Liu, Q. (2015). Emerging technologies research in accounting: JETA’s first decade. Journal of Emerging Technologies in Accounting, 12(1), 17–50. https://doi.org/10.2308/jeta-51245
- Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using Artificial Intelligence in Auditing. Journal of Business Ethics, 167(2), 209–234. https://doi.org/10.1007/s10551-019-04407-1
- Mushtaq, R., Gull, A. A., Shahab, Y., & Derouiche, I. (2022). Do financial performance indicators predict 10-K text sentiments? An application of artificial intelligence. Research in International Business and Finance, 61, 101679. https://doi.org/10.1016/j.ribaf.2022.101679
- Najem, R., Amr, M. F., Bahnasse, A., & Talea, M. (2022). Artificial Intelligence for Digital Finance, Axes and Techniques. Procedia Computer Science, 203, 633–638. https://doi.org/10.1016/j.procs.2022.07.092
- Nelson, K. M., Kogan, A., Srivastava, R. P., Vasarhelyi, M. A., & Lu, H. (2000). Virtual auditing agents: The EDGAR Agent challenge. Decision Support Systems, 28(3), 241–253. https://doi.org/10.1016/S0167-9236(99)00088-3
- Newman, J., Mintrom, M., & O’Neill, D. (2022). Digital technologies, artificial intelligence, and bureaucratic transformation. Futures, 136, 102886. https://doi.org/10.1016/j.futures.2021.102886
- Ng, C., & Alarcon, J. (2020). Artificial Intelligence in Accounting. Routledge. https://doi.org/10.4324/9781003003342
- Nielsen, S. (2022). Management accounting and the concepts of exploratory data analysis and unsupervised machine learning: a literature study and future directions. Journal of Accounting & Organizational Change, 18(5), 811–853. https://doi.org/10.1108/JAOC-08-2020-0107
- Nouraldeen, R. M. (2023). The impact of technology readiness and use perceptions on students’ adoption of artificial intelligence: The moderating role of gender. Development and Learning in Organizations: An International Journal, 37(3), 7–10. https://doi.org/10.1108/DLO-07-2022-0133
- Petkov, R. (2020). Artificial intelligence (AI) and the accounting function—a revisit and a new perspective for developing framework. Journal of Emerging Technologies in Accounting, 17(1), 99–105. https://doi.org/10.2308/jeta-52648
- Phillips, F., & Johnson, B. G. (2011). Online homework versus intelligent tutoring systems: Pedagogical support for transaction analysis and recording. Issues in Accounting Education, 26(1), 87–97. https://doi.org/10.2308/iace.2011.26.1.87
- Qasim, A., & Kharbat, F. F. (2020). Blockchain technology, business data analytics, and artificial intelligence: Use in the accounting profession and ideas for inclusion into the accounting curriculum. Journal of Emerging Technologies in Accounting, 17(1), 107–117. https://doi.org/10.2308/jeta-52649
- Rahman, M. J., & Zhu, H. (2023). Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China. Accounting & Finance, 63(3), 3455–3486. https://doi.org/10.1111/acfi.13044
- Rahman, M. J., & Ziru, A. (2023). Clients’ digitalization, audit firms’ digital expertise, and audit quality: Evidence from China. International Journal of Accounting & Information Management, 31(2), 221–246. https://doi.org/10.1108/IJAIM-08-2022-0170
- Roszkowska, P. (2021). Fintech in financial reporting and audit for fraud prevention and safeguarding equity investments. Journal of Accounting & Organizational Change, 17(2), 164–196. https://doi.org/10.1108/JAOC-09-2019-0098
- Sage. (2018). Accountants adoption of Artificial Intelligence expected to increase as clients’ expectations shift.
- Samanthi, D., & Gooneratne, T. (2023). Bean counter to value-adding business partner: The changing role of the accountant and situated rationality in a multinational firm. Journal of Accounting & Organizational Change, 19(3), 513–535. https://doi.org/10.1108/JAOC-04-2022-0063
- Schweitze, B. (2024). Artificial Intelligence (AI) ethics in accounting. Journal of Accounting, Ethics & Public Policy, 25(1). https://doi.org/10.60154/jaepp.2024.v25n1p67
- SCImago. (2010). SCImago Journal & Country Rank.
- Sherif, K., & Mohsin, H. (2021). The effect of emergent technologies on accountant`s ethical blindness. The International Journal of Digital Accounting Research, 61–94. https://doi.org/10.4192/1577-8517-v21_3
- Shimamoto, D. C. (2018). Is artificial intelligence a threat to government accountants and auditors? Journal of Government Financial Management, 67(4), 12–16.
- Siladjaja, M., Anwar, Y., & Djan, I. (2022). The impact of real manipulation and tax management on future market value: An artificial intelligence simulation of high earnings quality. ACRN Journal of Finance and Risk Perspectives, 11(1), 33–54. https://doi.org/10.35944/jofrp.2022.11.1.003
- Silva de Souza, M. J., Almudhaf, F. W., Henrique, B. M., Silveira Negredo, A. B., Franco Ramos, D. G., Sobreiro, V. A., & Kimura, H. (2019). Can artificial intelligence enhance the Bitcoin bonanza. The Journal of Finance and Data Science, 5(2), 83–98. https://doi.org/10.1016/j.jfds.2019.01.002
- Sun, T. S. (2019). Applying deep learning to audit procedures: An illustrative framework. Accounting Horizons, 33(3), 89–109. https://doi.org/10.2308/acch-52455
- Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73. https://doi.org/10.1016/j.accinf.2016.07.005
- Tiwari, K., & Khan, M. S. (2020). Sustainability accounting and reporting in the industry 4.0. Journal of Cleaner Production, 258, 120783. https://doi.org/10.1016/j.jclepro.2020.120783
- Türegün, N. (2019). Impact of technology in financial reporting: The case of Amazon Go. Journal of Corporate Accounting & Finance, 30(3), 90–95. https://doi.org/10.1002/jcaf.22394
- Wagner, W. P., Otto, J., & Chung, Q. B. (2002). Knowledge acquisition for expert systems in accounting and financial problem domains. Knowledge-Based Systems, 15(8), 439–447. https://doi.org/10.1016/S0950-7051(02)00026-6
- Wang, D., Chen, Z., Florescu, I., & Wen, B. (2023). A sparsity algorithm for finding optimal counterfactual explanations: Application to corporate credit rating. Research in International Business and Finance, 64, 101869. https://doi.org/10.1016/j.ribaf.2022.101869
- Wessels, T., & Jokonya, O. (2022). Factors affecting the adoption of big data as a service in SMEs. Procedia Computer Science, 196, 332–339. https://doi.org/10.1016/j.procs.2021.12.021
- White, C. E. (1995). An analysis of the need for ES and AI in accounting education. Accounting Education, 4(3), 259–269. https://doi.org/10.1080/09639289500000029
- Wilson, R. L., & Sharda, R. (1994). Bankruptcy prediction using neural networks. Decision Support Systems, 11(5), 545–557. https://doi.org/10.1016/0167-9236(94)90024-8
- Zemánková, A. (2019). Artificial intelligence and blockchain in audit and accounting: Literature review. WSEAS Transactions on Business and Economics, 16, 568–581.
- Zide, O., & Jokonya, O. (2022). Factors affecting the adoption of Data Management as a Service (DMaaS) in Small and Medium Enterprises (SMEs). Procedia Computer Science, 196, 340–347. https://doi.org/10.1016/j.procs.2021.12.022
- Zotti, J., Socci, C., Severini, F., & Infantino, G. (2023). Scenarios of technological progress in Italy: What can we expect? Industry and Innovation, 30(8), 1029–1059. https://doi.org/10.1080/13662716.2022.2152313
References
Abukhader, S. M. (2021). Extent of artificial intelligence into accounting and auditing work - an analytical attempt of job and duties. International Journal of Business Process Integration and Management, 1(1), 1. https://doi.org/10.1504/IJBPIM.2021.10037973
Ackerman, J. L. (2023, August 1). Artificial intelligence may be coming sooner than expected. The CPA Journal. https://www.cpajournal.com/2023/08/01/artificial-intelligence-may-be-coming-sooner-than-expected/
Adekoya, O. B., Oliyide, J. A., Saleem, O., & Adeoye, H. A. (2022). Asymmetric connectedness between Google-based investor attention and the fourth industrial revolution assets: The case of FinTech and Robotics & Artificial intelligence stocks. Technology in Society, 68, 101925. https://doi.org/10.1016/j.techsoc.2022.101925
Agustí, M. A., & Orta-Pérez, M. (2023). Big data and artificial intelligence in the fields of accounting and auditing: A bibliometric analysis. Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad, 52(3), 412–438. https://doi.org/10.1080/02102412.2022.2099675
Akerkar, R. (2019). Artificial intelligence for business. Springer International Publishing. https://doi.org/10.1007/978-3-319-97436-1
Anggraini, P. G., & Sholihin, M. (2023). What do we know about managerial ability? A systematic literature review. Management Review Quarterly, 73(1), 1–30. https://doi.org/10.1007/s11301-021-00229-6
Ardichvili, A. (2022). The impact of artificial intelligence on expertise development: Implications for HRD. Advances in Developing Human Resources, 24(2), 78–98. https://doi.org/10.1177/15234223221077304
Armstrong, B., & Lee, G. J. (2021). Introduction to digital business. Silk Route Press.
Arnaboldi, M., de Bruijn, H., Steccolini, I., & Van der Voort, H. (2022). On humans, algorithms and data. Qualitative Research in Accounting & Management, 19(3), 241–254. https://doi.org/10.1108/QRAM-01-2022-0005
Arora, M., & Sharma, R. L. (2023). Artificial intelligence and big data: Ontological and communicative perspectives in multi-sectoral scenarios of modern businesses. Foresight, 25(1), 126–143. https://doi.org/10.1108/FS-10-2021-0216
Atayah, O. F., & Alshater, M. M. (2021). Audit and tax in the context of emerging technologies: A retrospective analysis, current trends, and future opportunities. The International Journal of Digital Accounting Research, 95–128. https://doi.org/10.4192/1577-8517-v21_4
Bakarich, K. M., & O’Brien, P. E. (2021). The robots are coming …but aren’t here yet: The use of artificial intelligence technologies in the public accounting profession. Journal of Emerging Technologies in Accounting, 18(1), 27–43. https://doi.org/10.2308/JETA-19-11-20-47
Baldwin-Morgan, A. A. (1995). Integrating artificial intelligence into the accounting curriculum. Accounting Education, 4(3), 217–229. https://doi.org/10.1080/09639289500000026
Birnberg, J. G., & Shields, M. D. (1984). The role of attention and memory in accounting decisions. Accounting, Organizations and Society, 9(3–4), 365–382. https://doi.org/10.1016/0361-3682(84)90020-5
Bose, S., Kumar Dey, S., & Bhattacharjee, S. (2023). Big data, data analytics and artificial intelligence in accounting: An overview. In Handbook of Big Data Research Methods (pp. 32–51). Edward Elgar Publishing. https://doi.org/10.4337/9781800888555.00007
Boussabaine, A. H., & Kaka, A. P. (1998). A neural networks approach for cost flow forecasting. Construction Management and Economics, 16(4), 471–479. https://doi.org/10.1080/014461998372240
Bracci, E. (2023). The loopholes of algorithmic public services: An “intelligent” accountability research agenda. Accounting, Auditing & Accountability Journal, 36(2), 739–763. https://doi.org/10.1108/AAAJ-06-2022-5856
Caner, S., & Bhatti, F. (2020). A conceptual framework on defining businesses strategy for artificial intelligence. Contemporary Management Research, 16(3), 175–206. https://doi.org/10.7903/cmr.19970
Chang, Y.-T., & Stone, D. N. (2019). Why does decomposed audit proposal readability differ by audit firm size? A Coh-Metrix approach. Managerial Auditing Journal, 34(8), 895–923. https://doi.org/10.1108/MAJ-02-2018-1789
Choi, S. U., Lee, K. C., & Na, H. J. (2022). Exploring the deep neural network model’s potential to estimate abnormal audit fees. Management Decision, 60(12), 3304–3323. https://doi.org/10.1108/MD-07-2021-0954
Chukwuani, V. (2025). The ethical dilemma of AI-driven accounting: Balancing automation and professional judgment. International Journal of Financial Economics and Accounting, 5(2), 1–9. https://doi.org/10.5281/zenodo.15141882
Cooper, H. B., Ewing, M. T., & Mishra, S. (2022). Text-mining 10-K (annual) reports: A guide for B2B marketing research. Industrial Marketing Management, 107, 204–211. https://doi.org/10.1016/j.indmarman.2022.10.001
Damerji, H., & Salimi, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting. Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
De Villiers, R. (2021). Seven principles to ensure future-ready accounting graduates – a model for future research and practice. Meditari Accountancy Research, 29(6), 1354–1380. https://doi.org/10.1108/MEDAR-04-2020-0867
Deloitte. (2023). Discover applications and benefits for AI in the public sector.
Diab, A., Abdelazim, S. I., & Metwally, A. B. M. (2023). The impact of institutional ownership on the value relevance of accounting information: Evidence from Egypt. Journal of Financial Reporting and Accounting, 21(3), 509–525. https://doi.org/10.1108/JFRA-05-2021-0130
Elliot, V. H., Paananen, M., & Staron, M. (2020). Artificial intelligence for decision-makers. Journal of Emerging Technologies in Accounting, 17(1), 51–55. https://doi.org/10.2308/jeta-52666
Elliott, R. K. (1986). Auditing in the 1990s: Implications for education and research. California Management Review, 28(4), 89–97. https://doi.org/10.2307/41165218
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27(3), 938–985. https://doi.org/10.1007/s11142-022-09697-x
Goldwater, P. M., & Fogarty, T. J. (2007). Protecting the solution: A ‘High-Tech.’ method to guarantee individual effort in accounting classes. Accounting Education, 16(2), 129–143. https://doi.org/10.1080/09639280701234344
Grüning, M. (2011). Artificial Intelligence Measurement of Disclosure (AIMD). European Accounting Review, 20(3), 485–519. https://doi.org/10.1080/09638180.2011.585792
Haenlein, M., & Kaplan, A. (2021). Artificial intelligence and robotics: Shaking up the business world and society at large. Journal of Business Research, 124, 405–407. https://doi.org/10.1016/j.jbusres.2020.10.042
Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. https://doi.org/10.1016/j.accinf.2022.100598
Holmes, A. F., & Douglass, A. (2022). Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. Journal of Emerging Technologies in Accounting, 19(1), 53–68. https://doi.org/10.2308/JETA-2020-054
Hossain, M. A., Agnihotri, R., Rushan, M. R. I., Rahman, M. S., & Sumi, S. F. (2022). Marketing analytics capability, artificial intelligence adoption, and firms’ competitive advantage: Evidence from the manufacturing industry. Industrial Marketing Management, 106, 240–255. https://doi.org/10.1016/j.indmarman.2022.08.017
Indarti, N., Lukito-Budi, A. S., & Islam, A. M. (2020). A systematic review of halal supply chain research: To where shall we go? Journal of Islamic Marketing, 12(9), 1930–1949. https://doi.org/10.1108/JIMA-05-2020-0161
Johnson, B. G., Phillips, F., & Chase, L. G. (2009). An intelligent tutoring system for the accounting cycle: Enhancing textbook homework with artificial intelligence. Journal of Accounting Education, 27(1), 30–39. https://doi.org/10.1016/j.jaccedu.2009.05.001
Juszczyk, M., Zima, K., & Lelek, W. (2019). Forecasting of sports fields construction costs aided by ensembles of neural networks. Journal of Civil Engineering and Management, 25(7), 715–729. https://doi.org/10.3846/jcem.2019.10534
Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2023). Artificial intelligence and HRM: Identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 73(2), 455–493. https://doi.org/10.1007/s11301-021-00249-2
Keding, C. (2021). Understanding the interplay of artificial intelligence and strategic management: four decades of research in review. Management Review Quarterly, 71(1), 91–134. https://doi.org/10.1007/s11301-020-00181-x
Kend, M., & Nguyen, L. A. (2020). Big data analytics and other emerging technologies: The impact on the Australian audit and assurance profession. Australian Accounting Review, 30(4), 269–282. https://doi.org/10.1111/auar.12305
Kim, K. S. (2005). Examining corporate bankruptcy: An artificial intelligence approach. International Journal of Business Performance Management, 7(3), 241–254.
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
Kokina, J., Pachamanova, D., & Corbett, A. (2017). The role of data visualization and analytics in performance management: Guiding entrepreneurial growth decisions. Journal of Accounting Education, 38, 50–62. https://doi.org/10.1016/j.jaccedu.2016.12.005
Kommunuri, J. (2022). Artificial intelligence and the changing landscape of accounting: A viewpoint. Pacific Accounting Review, 34(4), 585–594. https://doi.org/10.1108/PAR-06-2021-0107
Korhonen, T., Selos, E., Laine, T., & Suomala, P. (2020). Exploring the programmability of management accounting work for increasing automation: An interventionist case study. Accounting, Auditing & Accountability Journal, 34(2), 253–280. https://doi.org/10.1108/AAAJ-12-2016-2809
Korol, V., Dmytryk, O., Karpenko, O., Riadinska, V., Basiuk, O., Kobylnik, D., Moroz, V., Safronova, O., Alisov, E., & Mishchenko, T. (2022). Elaboration of recommendations on the development of the state internal audit system when applying the digital technologies. Eastern-European Journal of Enterprise Technologies, 1(13(115)), 39–48. https://doi.org/10.15587/1729-4061.2022.252424
Le Guyader, L. P. (2020). Artificial intelligence in accounting: GAAP’s “FAS133.” Journal of Corporate Accounting & Finance, 31(3), 185–189. https://doi.org/10.1002/jcaf.22407
Lee, C. S., & Tajudeen, F. P. (2020). Usage and impact of artificial intelligence on accounting: Evidence from Malaysian organisations. Asian Journal of Business and Accounting, 13(1), 213–240. https://doi.org/10.22452/ajba.vol13no1.8
Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Artificial intelligence based decision-making in accounting and auditing: Ethical challenges and normative thinking. Accounting, Auditing & Accountability Journal, 35(9), 109–135. https://doi.org/10.1108/AAAJ-09-2020-4934
Leitner-Hanetseder, S., & Lehner, O. M. (2023). AI-powered information and Big Data: Current regulations and ways forward in IFRS reporting. Journal of Applied Accounting Research, 24(2), 282–298. https://doi.org/10.1108/JAAR-01-2022-0022
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201
Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911–926. https://doi.org/10.1016/j.jbusres.2020.11.001
Mahroof, K. (2019). A human-centric perspective exploring the readiness towards smart warehousing: The case of a large retail distribution warehouse. International Journal of Information Management, 45, 176–190. https://doi.org/10.1016/j.ijinfomgt.2018.11.008
Mancini, D., Lombardi, R., & Tavana, M. (2021). Four research pathways for understanding the role of smart technologies in accounting. Meditari Accountancy Research, 29(5), 1041–1062. https://doi.org/10.1108/MEDAR-03-2021-1258
McCarthy, J., Minsky, M., Rochester, N., & Shannon, C. (1995). A proposal for the Dartmouth summer research project on Artificial Intelligence. AI Magazine, 27, 12–14.
Mishra, S., Ewing, M. T., & Cooper, H. B. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, 50(6), 1176–1197. https://doi.org/10.1007/s11747-022-00876-5
Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. The British Accounting Review, 51(6), 100833. https://doi.org/10.1016/j.bar.2019.04.002
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
Mosteanu, N. R., & Faccia, A. (2020). Digital Systems and New Challenges of Financial Management – FinTech, XBRL, Blockchain, and Cryptocurrencies. Quality - Access to Success, 21, 159–166.
Muehlmann, B. W., Chiu, V., & Liu, Q. (2015). Emerging technologies research in accounting: JETA’s first decade. Journal of Emerging Technologies in Accounting, 12(1), 17–50. https://doi.org/10.2308/jeta-51245
Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using Artificial Intelligence in Auditing. Journal of Business Ethics, 167(2), 209–234. https://doi.org/10.1007/s10551-019-04407-1
Mushtaq, R., Gull, A. A., Shahab, Y., & Derouiche, I. (2022). Do financial performance indicators predict 10-K text sentiments? An application of artificial intelligence. Research in International Business and Finance, 61, 101679. https://doi.org/10.1016/j.ribaf.2022.101679
Najem, R., Amr, M. F., Bahnasse, A., & Talea, M. (2022). Artificial Intelligence for Digital Finance, Axes and Techniques. Procedia Computer Science, 203, 633–638. https://doi.org/10.1016/j.procs.2022.07.092
Nelson, K. M., Kogan, A., Srivastava, R. P., Vasarhelyi, M. A., & Lu, H. (2000). Virtual auditing agents: The EDGAR Agent challenge. Decision Support Systems, 28(3), 241–253. https://doi.org/10.1016/S0167-9236(99)00088-3
Newman, J., Mintrom, M., & O’Neill, D. (2022). Digital technologies, artificial intelligence, and bureaucratic transformation. Futures, 136, 102886. https://doi.org/10.1016/j.futures.2021.102886
Ng, C., & Alarcon, J. (2020). Artificial Intelligence in Accounting. Routledge. https://doi.org/10.4324/9781003003342
Nielsen, S. (2022). Management accounting and the concepts of exploratory data analysis and unsupervised machine learning: a literature study and future directions. Journal of Accounting & Organizational Change, 18(5), 811–853. https://doi.org/10.1108/JAOC-08-2020-0107
Nouraldeen, R. M. (2023). The impact of technology readiness and use perceptions on students’ adoption of artificial intelligence: The moderating role of gender. Development and Learning in Organizations: An International Journal, 37(3), 7–10. https://doi.org/10.1108/DLO-07-2022-0133
Petkov, R. (2020). Artificial intelligence (AI) and the accounting function—a revisit and a new perspective for developing framework. Journal of Emerging Technologies in Accounting, 17(1), 99–105. https://doi.org/10.2308/jeta-52648
Phillips, F., & Johnson, B. G. (2011). Online homework versus intelligent tutoring systems: Pedagogical support for transaction analysis and recording. Issues in Accounting Education, 26(1), 87–97. https://doi.org/10.2308/iace.2011.26.1.87
Qasim, A., & Kharbat, F. F. (2020). Blockchain technology, business data analytics, and artificial intelligence: Use in the accounting profession and ideas for inclusion into the accounting curriculum. Journal of Emerging Technologies in Accounting, 17(1), 107–117. https://doi.org/10.2308/jeta-52649
Rahman, M. J., & Zhu, H. (2023). Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China. Accounting & Finance, 63(3), 3455–3486. https://doi.org/10.1111/acfi.13044
Rahman, M. J., & Ziru, A. (2023). Clients’ digitalization, audit firms’ digital expertise, and audit quality: Evidence from China. International Journal of Accounting & Information Management, 31(2), 221–246. https://doi.org/10.1108/IJAIM-08-2022-0170
Roszkowska, P. (2021). Fintech in financial reporting and audit for fraud prevention and safeguarding equity investments. Journal of Accounting & Organizational Change, 17(2), 164–196. https://doi.org/10.1108/JAOC-09-2019-0098
Sage. (2018). Accountants adoption of Artificial Intelligence expected to increase as clients’ expectations shift.
Samanthi, D., & Gooneratne, T. (2023). Bean counter to value-adding business partner: The changing role of the accountant and situated rationality in a multinational firm. Journal of Accounting & Organizational Change, 19(3), 513–535. https://doi.org/10.1108/JAOC-04-2022-0063
Schweitze, B. (2024). Artificial Intelligence (AI) ethics in accounting. Journal of Accounting, Ethics & Public Policy, 25(1). https://doi.org/10.60154/jaepp.2024.v25n1p67
SCImago. (2010). SCImago Journal & Country Rank.
Sherif, K., & Mohsin, H. (2021). The effect of emergent technologies on accountant`s ethical blindness. The International Journal of Digital Accounting Research, 61–94. https://doi.org/10.4192/1577-8517-v21_3
Shimamoto, D. C. (2018). Is artificial intelligence a threat to government accountants and auditors? Journal of Government Financial Management, 67(4), 12–16.
Siladjaja, M., Anwar, Y., & Djan, I. (2022). The impact of real manipulation and tax management on future market value: An artificial intelligence simulation of high earnings quality. ACRN Journal of Finance and Risk Perspectives, 11(1), 33–54. https://doi.org/10.35944/jofrp.2022.11.1.003
Silva de Souza, M. J., Almudhaf, F. W., Henrique, B. M., Silveira Negredo, A. B., Franco Ramos, D. G., Sobreiro, V. A., & Kimura, H. (2019). Can artificial intelligence enhance the Bitcoin bonanza. The Journal of Finance and Data Science, 5(2), 83–98. https://doi.org/10.1016/j.jfds.2019.01.002
Sun, T. S. (2019). Applying deep learning to audit procedures: An illustrative framework. Accounting Horizons, 33(3), 89–109. https://doi.org/10.2308/acch-52455
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73. https://doi.org/10.1016/j.accinf.2016.07.005
Tiwari, K., & Khan, M. S. (2020). Sustainability accounting and reporting in the industry 4.0. Journal of Cleaner Production, 258, 120783. https://doi.org/10.1016/j.jclepro.2020.120783
Türegün, N. (2019). Impact of technology in financial reporting: The case of Amazon Go. Journal of Corporate Accounting & Finance, 30(3), 90–95. https://doi.org/10.1002/jcaf.22394
Wagner, W. P., Otto, J., & Chung, Q. B. (2002). Knowledge acquisition for expert systems in accounting and financial problem domains. Knowledge-Based Systems, 15(8), 439–447. https://doi.org/10.1016/S0950-7051(02)00026-6
Wang, D., Chen, Z., Florescu, I., & Wen, B. (2023). A sparsity algorithm for finding optimal counterfactual explanations: Application to corporate credit rating. Research in International Business and Finance, 64, 101869. https://doi.org/10.1016/j.ribaf.2022.101869
Wessels, T., & Jokonya, O. (2022). Factors affecting the adoption of big data as a service in SMEs. Procedia Computer Science, 196, 332–339. https://doi.org/10.1016/j.procs.2021.12.021
White, C. E. (1995). An analysis of the need for ES and AI in accounting education. Accounting Education, 4(3), 259–269. https://doi.org/10.1080/09639289500000029
Wilson, R. L., & Sharda, R. (1994). Bankruptcy prediction using neural networks. Decision Support Systems, 11(5), 545–557. https://doi.org/10.1016/0167-9236(94)90024-8
Zemánková, A. (2019). Artificial intelligence and blockchain in audit and accounting: Literature review. WSEAS Transactions on Business and Economics, 16, 568–581.
Zide, O., & Jokonya, O. (2022). Factors affecting the adoption of Data Management as a Service (DMaaS) in Small and Medium Enterprises (SMEs). Procedia Computer Science, 196, 340–347. https://doi.org/10.1016/j.procs.2021.12.022
Zotti, J., Socci, C., Severini, F., & Infantino, G. (2023). Scenarios of technological progress in Italy: What can we expect? Industry and Innovation, 30(8), 1029–1059. https://doi.org/10.1080/13662716.2022.2152313