The application of digital technologies in external auditing: a double edged sword?

Favourate Y Mpofu; Queen Mpofu

doi:10.36096/ijbes.v7i1.641

Authors

Favourate Y Mpofu National University of Science and Technology, Zimbabwe https://orcid.org/0000-0002-6309-1697
Queen Mpofu University of South Africa https://orcid.org/0000-0002-0853-4942

DOI:

https://doi.org/10.36096/ijbes.v7i1.641

Keywords:

: Challenges, Double-edged sword, Digital Technologies, External Auditing, Opportunities

Abstract

The adoption of digital technologies in external auditing has become increasingly common and significant in the digital era, revolutionizing audit practices and offering several opportunities. This study explores whether the application of digital technologies in external auditing presents a double-edged sword, with the ability to transform and disrupt the audit profession. Through a comprehensive examination of the likely opportunities and challenges of the digital transformation of the external audit function, this study sought to provide an insightful discussion of the dual nature of the implications of digital technologies. The aim of this study is to not only provide a balanced assessment of the application of digital technologies in external auditing but also to recommend possible ways for auditors, auditee companies, and other stakeholders to reap maximum benefits from the use of digital technologies, including how these various stakeholders can navigate the associated challenges effectively. Opportunities stemming from the application of digital technologies include the enhancement of audit quality, improved accuracy in audit procedures, increased efficiency and effectiveness, heightened comprehensiveness and extensiveness in risk assessment, and an increased degree of confidence in the audited financial statements by stakeholders (reduction in the audit expectation gap). On the downside, challenges and risks concern the lack of or the need for new skills and competencies for auditors, technological complexities linked to digital technologies, cybersecurity risks, overdependence on technology affecting audit quality, audit evidence, professional skepticism, and the widening of the audit expectation gap. To maximize the possible benefits and minimize risks, this study recommends continuous professional development, capacity building through education, training and collaboration, better technology and data governance initiatives, and continuous assessment of risks.

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References

Aditya, B. R., Hartanto, R., & Nugroho, L. E. (2018). The role of IT audit in the era of digital transformation. IOP Conference Series: Materials Science and Engineering, 407(1), 1–6. https://doi.org/10.1088/1757-899X/407/1/012164 DOI: https://doi.org/10.1088/1757-899X/407/1/012164

Agnew, W., Lee, H., Jang, M., Gavrilovska, A., & Schwan, K. (2016). Drawing insights from "big data" machine learning literature using textual features: Why are some novels considered to be literature? A predictive model of literary judgments shows that textual features are important.

Aksoy, T., & Bicer, A. A. (2021). Common audit deficiencies under the audit quality microscope. In Auditing ecosystem and strategic accounting in the digital era: Global approaches and new opportunities (pp. 315–321). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-72628-7_14

Aksoy, T., & Gurol, B. (2021). Artificial intelligence in computer-aided auditing techniques and technologies (CAATTs) and an application proposal for auditors. In Auditing ecosystem and strategic accounting in the digital era: Global approaches and new opportunities (pp. 361–384). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-72628-7_17

Alacron, A. J., & Ng, C. (2018). Blockchain and the future of accounting. Pennsylvania CPA Journal.

Al-Aroud, S. F. (2020). The impact of artificial intelligence technologies on audit evidence. Academy of Accounting and Financial Studies Journal, 24, 1–11.

Albawwat, I., & Frijat, Y. (2021). An analysis of auditors’ perceptions towards artificial intelligence and its contribution to audit quality. Accounting, 7(4), 755–762. DOI: https://doi.org/10.5267/j.ac.2021.2.009

Alipourfallahpasand, A., & Asgari, S. (2020). Emerging technologies in the audit environment: Use and perceived importance among independent auditors. Iranian Journal of Accounting, Auditing and Finance, 4(2), 103–119.

Al-Sayyed, S., Al-Aroud, S., & Zayed, L. (2021). The effect of artificial intelligence technologies on audit evidence. Accounting, 7(2), 281–288. DOI: https://doi.org/10.5267/j.ac.2020.12.003

Appelbaum, D., & Nehmer, R. A. (2020). Auditing cloud-based blockchain accounting systems. Journal of Information Systems, 34(2), 5–21. DOI: https://doi.org/10.2308/isys-52660

Arora, C., & Sarkar, D. (2023). Auditing artificial intelligence as a new layer of mediation: Introduction of a new black box to address another black box. Hipertext.net, 26, 65–68. DOI: https://doi.org/10.31009/hipertext.net.2023.i26.10

Baldwin, A. A., Brown, C. E., & Trinkle, B. S. (2006). Opportunities for artificial intelligence development in the accounting domain: The case for auditing. Intelligent Systems in Accounting, Finance & Management: International Journal, 14(3), 77–86. DOI: https://doi.org/10.1002/isaf.277

Balios, D., Kotsilaras, P., Eriotis, N., & Vasiliou, D. (2020). Big data, data analytics and external auditing. Journal of Modern Accounting and Auditing, 16(5), 211–219. DOI: https://doi.org/10.17265/1548-6583/2020.05.002

Botez, D. (2018). Recent challenges for auditors: Using data analytics in the audit of financial statements. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 9(4), 61–71.

Bozhinovska Lazarevska, Z., Tocev, T., & Dionisijev, I. (2022). How to improve performance in public sector auditing through the power of big data and data analytics?: The case of the Republic of North Macedonia. DOI: https://doi.org/10.32602/jafas.2022.023

Brunskill, E. (2019). Computers that learn to help. Human Centred Artificial Intelligence Symposium, Stanford.

Cho, S., Vasarhelyi, M. A., Sun, T., & Zhang, C. (2020). Learning from machine learning in accounting and assurance. Journal of Emerging Technologies in Accounting, 17(1), 1–10. DOI: https://doi.org/10.2308/jeta-10718

Chong, L., Zhang, G., Goucher-Lambert, K., Kotovsky, K., & Cagan, J. (2022). Human confidence in artificial intelligence and in themselves: The evolution and impact of confidence on adoption of AI advice. Computers in Human Behavior, 127, 107018. DOI: https://doi.org/10.1016/j.chb.2021.107018

Commerford, B. P., Dennis, S. A., Joe, J. R., & Ulla, J. W. (2022). Man versus machine: Complex estimates and auditor reliance on artificial intelligence. Journal of Accounting Research, 60(1), 171–201. DOI: https://doi.org/10.1111/1475-679X.12407

CPA. (2017). Deep learning and the future of auditing: How an evolving technology could transform analysis and improve judgment. CPA Journal.

Cronin, P., Ryan, F., & Coughlan, M. (2008). Undertaking a literature review: A step-by-step approach. British Journal of Nursing, 17(1), 38–43. DOI: https://doi.org/10.12968/bjon.2008.17.1.28059

Dagilien?, L., & Klovien?, L. (2019). Motivation to use big data and big data analytics in external auditing. Managerial Auditing Journal, 34(7), 750–782. https://doi.org/10.1108/MAJ-01-2018-1773 DOI: https://doi.org/10.1108/MAJ-01-2018-1773

Dai, J., & Vasarhelyi, M. A. (2016). Imagineering Audit 4.0. Journal of Emerging Technologies in Accounting, 13, 1–15. DOI: https://doi.org/10.2308/jeta-10494

De Mauro, A., Greco, M., Grimaldi, M., & Nobili, G. (2016). Beyond data scientists: A review of big data skills and job families. Proceedings of IFKAD, 1844–1857.

Deepal, A. G., & Jayamaha, A. (2022). Audit expectation gap: A comprehensive literature review. Asian Journal of Accounting Research, 7(3), 308–319. DOI: https://doi.org/10.1108/AJAR-10-2021-0202

Deloitte. (2020). Technology industry outlook: As cloud and AI deployments rise, edge computing is poised to join the mix. Available at www.deloitte.com/content

Denhere, V. (2024). Digital transformation in the auditing environment. In Digital Transformation in South Africa: Perspectives from an Emerging Economy (pp. 119–135). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-52403-5_9

Desplebin, O., Lux, G., & Petit, N. (2021). To be or not to be: Blockchain and the future of accounting and auditing. Accounting Perspectives, 20(4), 743–769. https://doi.org/10.1111/1911-3838.12265 DOI: https://doi.org/10.1111/1911-3838.12265

Dickey, G., Blanke, S., & Seaton, L. (2019). Machine learning in auditing. The CPA Journal, 16–21.

Dietvorst, B. J., & Bharti, S. (2020). People reject algorithms in uncertain decision domains because they have diminishing sensitivity to forecasting error. Psychological Science, 31(10), 1302–1314. DOI: https://doi.org/10.1177/0956797620948841

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

El Badlaoui, A., Naji, S., & Chegri, B. (2023). The audit expectation gap in developed and developing countries: Components and reduction factors. American Journal of Multidisciplinary Research & Development (AJMRD), 5(09), 22–44.

El-Monem Serag, A. A., & Al-Aqiliy, L. M. (2020). A proposed framework for big data analytics in external auditing and its impact on audit quality with a field study in Egypt. Alexandria Journal of Accounting Research, 4(3), 1–60. https://aljalexu.journals.ekb.eg/article_124109.htm

Fadaly, D. (2023). Investigating the impact of digital transformation of external auditing on their business in the Egyptian context. Alexandria Journal of Accounting Research, 7(2), 103–140.

Fang, Q., & Gao, S. (2022). Data-based audit approach: The supply-side reform of auditing driven by digital technology. Journal of Contemporary Finance and Economics, (1), 124.

Fotoh, L. E., & Lorentzon, J. I. (2020). Critical issues of the audit expectation gap in the era of audit digitalization. In Proceedings of Hawai’i Accounting Research Conference (HARC), 1–32. https://scholarspace.manoa.hawaii.edu/items/49c8cdcd-d14c-493c-9dad-063a9ccb4d1a

Fotoh, L. E., & Lorentzon, J. I. (2023). Audit digitalization and its consequences on the audit expectation gap: A critical perspective. Accounting Horizons, 37(1), 43–69. DOI: https://doi.org/10.2308/HORIZONS-2021-027

Fotoh, L., & Mugwira, T. (2024). Resistance to adopting emerging technologies in external auditing: An exploration of auditors’ perceptions. Available at SSRN 4702319. DOI: https://doi.org/10.2139/ssrn.4702319

Fukas, P., Rebstadt, J., Remark, F., & Thomas, O. (2021). Developing an artificial intelligence maturity model for auditing. In 29th European Conference on Information Systems Research Papers.

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007 DOI: https://doi.org/10.1016/j.ijinfomgt.2014.10.007

Gauthier, M. P., & Brender, N. (2021). How do the current auditing standards fit the emergent use of blockchain? Managerial Auditing Journal, 36(3), 365–385. https://doi.org/10.1108/MAJ-12-2019-2513 DOI: https://doi.org/10.1108/MAJ-12-2019-2513

Gepp, A., Linnenluecke, M. K., O’Neill, T. J., & Smith, T. (2018). Big data techniques in auditing research and practice: Current trends and future opportunities. Journal of Accounting Literature, 40(1), 102–115. DOI: https://doi.org/10.1016/j.acclit.2017.05.003

Hassani, H., Silva, E. S., Unger, S., TajMazinani, M., & Mac Feely, S. (2020). Artificial intelligence (AI) or intelligence augmentation (IA): What is the future? AI, 1(2), 143–155. DOI: https://doi.org/10.3390/ai1020008

Herath, S. K., & Joshi, P. L. (2023). Audit data analytics: A game changer for audit firms. International Journal of Auditing and Accounting Studies. Special Issue on Auditing in the Digital Age, 5(1), 29–48.

Huang, F., & Vasarhelyi, M. A. (2019). Applying robotic process automation (RPA) in auditing: A framework. International Journal of Accounting Information Systems, 35, 100433. DOI: https://doi.org/10.1016/j.accinf.2019.100433

Ibrahim, K. (2024). Bridging skill gap of future accountant that fits with Industry 4.0. Journal of African Innovation and Advanced Studies.

IFAC. (2015). Exploring artificial intelligence and the accounting profession. Opportunity, threat, both, neither? Available at www.ifac.org/knowledge-gateway-/preparing-future-ready-professionals/discussion/exploring-artificial-intelligence-accounting-profession-opportunity-threat-both-neither

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

Ivanovi?, T., & Mari?, M. (2021). Application of modern enterprise resource planning (ERP) systems in the era of digital transformation. Strategic Management, 26(4), 28–36. https://doi.org/10.5937/StraMan2104028I DOI: https://doi.org/10.5937/StraMan2104028I

Kazakova, N. A., Bobkova, M. P., & Sivkova, A. E. (2020, March). Evaluation and prediction of the business continuity risks. In International Scientific Conference "Far East Con" (ISCFEC 2020) (pp. 2407–2412). Atlantis Press. DOI: https://doi.org/10.2991/aebmr.k.200312.334

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, CPA Australia, 30(4), 269–282. https://doi.org/10.1111/auar.12305 DOI: https://doi.org/10.1111/auar.12305

Kokina, J., & Blanchette, S. (2019). Early evidence of digital labour in accounting: Innovation with Robotic Process Automation. International Journal of Accounting Information Systems, 35, 100431. DOI: https://doi.org/10.1016/j.accinf.2019.100431

Kokina, J., & Davenport, T. (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 DOI: https://doi.org/10.2308/jeta-51730

Kokina, J., Gilleran, R., Blanchette, S., & Stoddard, D. (2021). Accountant as digital innovator: Roles and competencies in the age of automation. Accounting Horizons, 35(1), 153–184. DOI: https://doi.org/10.2308/HORIZONS-19-145

Kommunuri, J. (2022). Artificial intelligence and the changing landscape of accounting: A viewpoint. Pacific Accounting Review, (ahead-of-print). DOI: https://doi.org/10.1108/PAR-06-2021-0107

Koshiyama, A., Kazim, E., & Treleaven, P. (2022). Algorithm auditing: Managing the legal, ethical, and technological risks of artificial intelligence, machine learning, and associated algorithms. Computer, 55(4), 40–50. DOI: https://doi.org/10.1109/MC.2021.3067225

Koshiyama, A., Kazim, E., Treleaven, P., Rai, P., Szpruch, L., Pavey, G., ... & Lomas, E. (2021). Towards algorithm auditing: A survey on managing legal, ethical, and technological risks of AI, ML, and associated algorithms. DOI: https://doi.org/10.2139/ssrn.3778998

KPMG. (2019). Learning and the audit: Rise of machines. Available at https://home.kpmg/au/en/home/insights/2019/04/audit-technology-machine-learning

Lacity, M., & Willcocks, L. P. (2018). Robotic process and cognitive automation: The next phase. SB Publishing.

Lacity, M., Willcocks, L., & Gozman, D. (2021). Influencing information systems practice: The action principles approach applied to robotic process and cognitive automation. Journal of Information Technology, 36(3), 216–240. DOI: https://doi.org/10.1177/0268396221990778

Landers, R. N., & Behrend, T. S. (2022). Auditing the AI auditors: A framework for evaluating fairness and bias in high-stakes AI predictive models. American Psychologist. DOI: https://doi.org/10.1037/amp0000972

Lim, F. X. (2021). Emerging technologies to detect fraud in audit testing: A perception of Malaysian Big Four auditors. Available at SSRN 3877347. DOI: https://doi.org/10.2139/ssrn.3877347

Losbichler, H., & Lehner, O. M. (2021). Limits of artificial intelligence in controlling and the ways forward: A call for future accounting research. Journal of Applied Accounting Research. DOI: https://doi.org/10.1108/JAAR-10-2020-0207

Lugli, E., & Bertacchini, F. (2022). Audit quality and digitalization: Some insights from the Italian context. Meditari Accountancy Research, ahead-of-print. https://doi.org/10.1108/MEDAR-08-2021-1399 DOI: https://doi.org/10.1108/MEDAR-08-2021-1399

Mariia, N., & Viktoriia, M. (2020). Digitalization of audit. Knute Bulletin, 3(131), 123–134. https://doi.org/10.31617/visnik.knute.2020(131)09 DOI: https://doi.org/10.31617/visnik.knute.2020(131)09

Mhlanga, D. (2021). Artificial intelligence in Industry 4.0 and its impact on poverty, innovation, infrastructure development, and the sustainable development goals: Lessons from emerging economies? Sustainability, 13(11), 5788. DOI: https://doi.org/10.3390/su13115788

Mhlanga, D. (2022). Human-centered artificial intelligence: The superlative approach to achieve sustainable development goals in the fourth industrial revolution. Sustainability, 14(13), 7804. DOI: https://doi.org/10.3390/su14137804

Mhlanga, D., & Moloi, T. (2020). COVID-19 and the digital transformation of education: What are we learning on 4IR in South Africa? Education Sciences, 10(7), 180. DOI: https://doi.org/10.3390/educsci10070180

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. DOI: https://doi.org/10.1016/j.bar.2019.04.002

Moloi, T., & Marwala, T. (2021a). Robotic Process Automation in strategy and strategy implementation. In Artificial Intelligence and the Changing Nature of Corporations (pp. 97-104). Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-76313-8_7

Moloi, T., & Marwala, T. (2021b). Natural language processing in strategy and implementation. In Artificial Intelligence and the Changing Nature of Corporations (pp. 77-95). Springer, Cham. DOI: https://doi.org/10.1007/978-3-030-76313-8_6

Mpofu, F. (2023). The application of artificial intelligence in external auditing and its implications on audit quality: A review of the ongoing debates. International Journal of Research in Business and Social Science, 12(9), 496-512. DOI: https://doi.org/10.20525/ijrbs.v12i9.2737

Mpofu, F. Y. (2021). Review articles: A critical review of the pitfalls and guidelines to effectively conducting and reporting reviews. Technium Soc. Sci. J., 18, 550.

Mpofu, F. Y. (2024a). Digital transformation by tax authorities. In Digital Transformation in South Africa: Perspectives from an Emerging Economy (pp. 151-170). Cham: Springer Nature Switzerland. DOI: https://doi.org/10.1007/978-3-031-52403-5_11

Mpofu, F. Y. (2024b). Digital currencies: Is Africa ready? Studia Universitatis Babes Bolyai-Negotia, 69(1), 7-38. DOI: https://doi.org/10.24193/subbnegotia.2024.1.01

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. DOI: https://doi.org/10.1007/s10551-019-04407-1

Musabegovi?, I., Ozer, M., Lazi?, M., & Jovanovi?, S. (2021). Interplay between digital technologies and business performance in banking industry: Global and regional perspectives. Ekonomika, 67(3), 75-92. DOI: https://doi.org/10.5937/ekonomika2103075M

Nazarova, K., Nezhyva, M., Hotsuliak, V., Novikova, N., & Fedorenko, O. (2021). Digital audit as an imperative for Ukraine’s way out from the COVID-crisis and a tool to increase the competitiveness of the state. SHS Web of Conferences, 100, 01001. https://doi.org/10.1051/shsconf/202110001001 DOI: https://doi.org/10.1051/shsconf/202110001001

Nezhyva, M., Zaremba, O., & Nehodenko, V. (2021). Application of blockchain technology in accounting and audit: International and domestic experience. DOI: https://doi.org/10.1051/shsconf/202110702001

Ramdhani, A., Ramdhani, M. A., & Amin, A. S. (2014). Writing a literature review research paper: A step-by-step approach. International Journal of Basic and Applied Science, 03(01), 47-56.

Rebstadt, J., Remark, F., Fukas, P., Meier, P., & Thomas, O. (2022). Towards personalized explanations for AI systems: Designing a role model for explainable AI in auditing.

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

Rickett, L. K. (2017). The use of big data in auditing and barriers to adoption. Business Faculty Publications, 62(3-4), 319. https://engagedscholarship.csuohio.edu/bus_facpub/31

Rozario, A. M., & Vasarhelyi, M. A. (2018). How robotic process automation is transforming accounting and auditing. The CPA Journal, 88(6), 46-49.

Saha, A. (2022). Digital transformation in audit function. The Management Accountant Journal, 57(9), 26-29. DOI: https://doi.org/10.33516/maj.v57i9.26-29p

Salijeni, G., Samsonova-Taddei, A., & Turley, S. (2021). Understanding how big data technologies reconfigure the nature and organization of financial statement audits: A sociomaterial analysis. European Accounting Review, 30(3), 531-555. DOI: https://doi.org/10.1080/09638180.2021.1882320

Sastry, S., Lee, T. H., & Teoh, M. T. T. (2021). The use of blockchain technology and data analytics in the audit profession. Quantum Journal of Social Sciences and Humanities, 2(4), 67-86. DOI: https://doi.org/10.55197/qjssh.v2i4.89

Seethamraju, R. C., & Hecimovic, A. (2020). Impact of artificial intelligence on auditing: An exploratory study.

Sousa, C., Carvalho, M., & Pereira, C. (2021, March). Boosting e-auditing process through e-files semantic enrichment. In World Conference on Information Systems and Technologies (pp. 449-458). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-72651-5_43

Sujata, S., & Shalini, C. (2021). Exploring factors influencing adoption of blockchain in accounting applications using technology–organization–environment framework. Information Journal of International Technology Management, 30(1), 30-68. https://scholarworks.lib.csusb.edu/jitim/vol30/iss1/2 DOI: https://doi.org/10.58729/1941-6679.1477

Supriadi, I., Prasetyo, H. D., & Suprihandari, M. D. (2020). The effect of applying blockchain to accounting and auditing. Ilomata International Journal of Tax & Accounting, 1(3), 161-169. https://doi.org/10.52728/ijtc.v1i3.101 DOI: https://doi.org/10.52728/ijtc.v1i3.101

Tiberius, V., & Hirth, S. (2019). Impacts of digitization on auditing: A Delphi study for Germany. Journal of International Accounting, Auditing and Taxation, 37, 100288. DOI: https://doi.org/10.1016/j.intaccaudtax.2019.100288

Tiron-Tudor, A., & Deliu, D. (2022). Reflections on the human-algorithm complex duality perspectives in the auditing process. Qualitative Research in Accounting & Management, 19(3), 255-285.

Turker, I., & Bicer, A. A. (2020). How to use blockchain effectively in auditing and assurance services. In Digital Business Strategies in Blockchain Ecosystems: Transformational Design and Future of Global Business (pp. 457-471). DOI: https://doi.org/10.1007/978-3-030-29739-8_22

Üço?lu, D. (2022). Artificial intelligence and auditing: Benefits and risks. In Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments (pp. 162-187). IGI Global. DOI: https://doi.org/10.4018/978-1-6684-4950-9.ch009

Uglum, M. K. (2021). Consideration of the ethical implications of artificial intelligence in the audit profession.

Ukpong, E. G., Udoh, I., & Essien, I. T. (2019). Artificial intelligence: Opportunities, issues and applications in accounting and auditing in Nigeria. Journal of Accounting & Marketing, 8(1). https://doi.org/10.4172/2168-9601.1000309 DOI: https://doi.org/10.9734/ajeba/2019/v10i130099

Vitali, S., & Giuliani, M. (2024). Emerging digital technologies and auditing firms: Opportunities and challenges. International Journal of Accounting Information Systems, 53, 100676. DOI: https://doi.org/10.1016/j.accinf.2024.100676

Vukovi?, B., Tica, T., & Jakši?, D. (2023). Challenges of using digital technologies in audit. Anali Ekonomskog fakulteta u Subotici. DOI: https://doi.org/10.5937/AnEkSub2300014V

Wan Mohamad Noor, W. N. B., Abd Razak, S. N. A., Mat Jusoh, Y. H., & Hasan, S. J. (2023). Navigating the digital landscape: Unraveling technological, organizational, and environmental factors affecting digital auditing readiness in the Malaysian public sector. Journal of Emerging Technologies in Accounting, 1-17. DOI: https://doi.org/10.2308/JETA-2022-072

Yin, X. (2023). Ethical dilemma of using Natural Language Processing (NLP) machine learning method in auditing company internal communication. International Journal of New Developments in Engineering and Society, 7(3), 16-20. DOI: https://doi.org/10.25236/IJNDES.2023.070303

Zhang, Z., Chen, Z., & Xu, L. (2022). Artificial intelligence and moral dilemmas: Perception of ethical decision-making in AI. Journal of Experimental Social Psychology, 101, 104327. DOI: https://doi.org/10.1016/j.jesp.2022.104327