Challenges of Implementing Artificial Intelligence in the Audit Profession and Its Impact on Audit Quality

Muhammad Abduh; Nuramal; Rusni; Andika Pramukti; Nur Aliyah; Riska Ananda

doi:10.37899/mjde.v3i1.338

Authors

Muhammad Abduh Accounting Study Program, Universitas Muslim Indonesia
Nuramal Accounting Study Program, Stiem Bongaya Makassar, Indonesia
Rusni Management Study Program, Stiem Bongaya Makassar, Indonesia
Andika Pramukti Accounting Study Program, Universitas Muslim Indonesia
Nur Aliyah Accounting Study Program, Universitas Muslim Indonesia
Riska Ananda Accounting Study Program, Universitas Muslim Indonesia

DOI:

https://doi.org/10.37899/mjde.v3i1.338

Keywords:

Artificial Intelligence, Audit Profession, Audit Quality

Abstract

The rapid development of Artificial Intelligence (AI) has significantly transformed the audit profession by introducing advanced data analytics, automation, and intelligent decision support systems. These technologies offer considerable potential to enhance audit quality by improving efficiency, enabling comprehensive data analysis, and strengthening fraud and risk detection capabilities. However, the adoption of AI in auditing is accompanied by complex challenges that extend beyond technological implementation. This study examines the challenges associated with AI implementation in the audit profession and analyzes their implications for auditor roles, professional judgment, and audit quality. Using a systematic literature review approach, this study synthesizes existing academic research to identify the dominant technical, ethical, regulatory, and human-related issues influencing AI adoption in auditing practice. The findings indicate that although AI can improve audit accuracy and effectiveness, its success largely depends on factors such as data quality, system transparency, auditor competence, and ethical governance. Furthermore, AI is reshaping the role of auditors by shifting their focus from routine procedural tasks toward analytical evaluation and professional judgment. Ethical concerns such as data privacy, algorithmic bias, and accountability, along with regulatory limitations, remain key barriers. Overall, AI should be viewed as a complementary tool that strengthens audit quality when responsibly integrated with professional expertise and appropriate governance mechanisms.

References

Alles, M. (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

Alles, M., & Gray, G. L. (2016). Incorporating big data in audits: Identifying inhibitors and a research agenda to address those inhibitors. International Journal of Accounting Information Systems, 22, 44–59. https://doi.org/10.1016/j.accinf.2016.07.004

Appelbaum, D., Kogan, A., & Vasarhelyi, M. A. (2017). Big data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice & Theory, 36(4), 1–27. https://doi.org/10.2308/ajpt-51684

Brown-Liburd, H., Issa, H., & Lombardi, D. (2015). Behavioral implications of big data's impact on audit judgment and decision making and future research directions. Accounting Horizons, 29(2), 451–468. https://doi.org/10.2308/acch-51023

Cao, M., Chychyla, R., & Stewart, T. (2015). Big data analytics in financial statement audits. Accounting Horizons, 29(2), 423–429. https://doi.org/10.2308/acch-51068

Curtis, M. B., & Payne, E. A. (2014). Modeling voluntary CAAT utilization decisions in auditing. Managerial Auditing Journal, 29(4), 304–326. https://doi.org/10.1108/MAJ-07-2013-0903

DeAngelo, L. (1981). Auditor size and audit quality. Journal of Accounting and Economics, 3(3), 183–199. https://doi.org/10.1016/0165-4101(81)90002-1

Dowling, C., & Leech, S. (2014). A Big 4 firm's use of information technology to control the audit process. Auditing: A Journal of Practice & Theory, 33(1), 51–72. https://doi.org/10.1111/1911-3846.12010

Earley, C. (2015). Data analytics in auditing: Opportunities and challenges. Business Horizons, 58(5), 493–500. https://doi.org/10.1016/j.bushor.2015.05.002

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., … Vayena, E. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

Francis, J. (2011). A framework for understanding and researching audit quality. Auditing: A Journal of Practice & Theory, 30(2), 125–152. https://doi.org/10.2308/ajpt-50006

IFAC. (2018). Handbook of the International Code of Ethics for Professional Accountants. International Federation of Accountants.

IAASB. (2020). The IAASB’s technology initiative: Exploring the growing use of technology in the audit, with a focus on data analytics. International Auditing and Assurance Standards Board.

Issa, H., Sun, T., & Vasarhelyi, M. (2016). Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation. Journal of Emerging Technologies in Accounting, 13(2), 1–20. https://doi.org/10.2308/jeta-10511

Janvrin, D., Bierstaker, J., & Lowe, D. (2014). An examination of audit information technology use and perceived importance. Accounting Horizons, 28(1), 77–98. https://doi.org/10.2308/acch.2008.22.1.1

Kachelmeier, S. (2022). The impact of artificial intelligence on auditing. Accounting Horizons, 36(1), 1–15.

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

Kroon, N., Alvesalo-Kuusi, A., & Vasarhelyi, M. (2021). The use of data analytics and artificial intelligence in auditing. Accounting Horizons, 35(3), 125–143.

Martin, K. (2019). Ethical implications and accountability of algorithms. Journal of Business Ethics, 160(4), 835–850. https://doi.org/10.1007/s10551-018-3921-3

Moffitt, K. C., Rozario, A., & Vasarhelyi, M. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1–10. https://doi.org/10.2308/jeta-10589

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

Nelson, M. W. (2009). A model and literature review of professional skepticism in auditing. Auditing: A Journal of Practice & Theory, 28(2), 1–34. https://doi.org/10.2308/aud.2009.28.2.1

Power, M. (2021). Organized uncertainty: Designing a world of risk management. Oxford University Press.

Raschke, R., & Charron, K. (2021). Artificial intelligence and auditing: Opportunities and challenges. Journal of Emerging Technologies in Accounting, 18(2), 1–18.

Richins, G., Stapleton, A., Stratopoulos, T., & Wong, C. (2017). Big data analytics: Opportunity or threat for the accounting profession? Journal of Information Systems, 31(3), 63–79. https://doi.org/10.2308/isys-51805

Rozario, A., & Vasarhelyi, M. (2018). Auditing with smart machines. International Journal of Accounting Information Systems, 29, 1–15. https://doi.org/10.4192/1577-8517-v18_1

Salijeni, G., Samsonova-Taddei, A., & Turley, S. (2019). Big data and changes in audit technology. Accounting and Business Research, 49(1), 95–119. https://doi.org/10.1080/00014788.2018.1459458?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle

Smith, S. S. (2021). Artificial intelligence and the future of accounting. Journal of Accounting Education, 54, 100716. https://doi.org/10.1007/978-3-031-43300-9_27

Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford University Press.

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

Vasarhelyi, M. A., Kogan, A., & Tuttle, B. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396. https://doi.org/10.2308/acch-51071

Vasarhelyi, M. A., Alles, M., & Williams, K. T. (2010). Continuous assurance for the now economy. International Journal of Accounting Information Systems, 11(4), 249–258.

Vasarhelyi, M. A., Lombardi, D., & Brown-Liburd, H. (2021). The future of audit. Journal of Emerging Technologies in Accounting, 18(1), 1–10. https://doi.org/10.4301/S1807-17752014000100002