CiteNScope — Scholarly Index & Analytics
Discover / IJBESPUBLICATION RECORD

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

Favourate Y Mpofu ORCID ↗ · Queen Mpofu ORCID ↗

International Journal of Business Ecosystem & Strategy · 2025 · Vol. 7 / Issue 1 · 39-56

Research reach

Publication metrics

External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.

Dimensions

Live provider badge. If unavailable, use the Dimensions link above.

CROSSREF CITATIONS0

Observed 21 Oct 2026, 00:14 UTC

OpenAlex · Citations1Cached provider observation

Observed 22 Oct 2026 02:28 UTC

Mendeley · Readers39Cached provider observation

Observed 22 Oct 2026 02:28 UTC

OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.

OpenAlex / Citation year

Annual citations to this article

View provider totals ↑

Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.

2017–2026 Annual history last updated:

Citations received

OpenAlex · year of the citing work

OpenAlex

Hover over a year or focus the chart and use arrow keys to inspect values.

2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.

View data & coverage

2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.

Overview

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.

Keywords: {'name': ': Challenges, Double-edged sword, Digital Technologies, External Auditing, Opportunities'}

Authors & affiliations

Favourate Y Mpofu
Affiliation not supplied

Queen Mpofu
Affiliation not supplied

Deposited references

Supplied references, not a list of publications citing this article.

DOI: 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.

DOI: 10.1007/978-3-030-72628-7_14

DOI: 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.

DOI: 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.

DOI: 10.5267/j.ac.2020.12.003

DOI: 10.2308/isys-52660

DOI: 10.31009/hipertext.net.2023.i26.10

DOI: 10.1002/isaf.277

DOI: 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.

DOI: 10.32602/jafas.2022.023

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

DOI: 10.2308/jeta-10718

DOI: 10.1016/j.chb.2021.107018

DOI: 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.

DOI: 10.12968/bjon.2008.17.1.28059

DOI: 10.1108/MAJ-01-2018-1773

DOI: 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.

DOI: 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

DOI: 10.1007/978-3-031-52403-5_9

DOI: 10.1111/1911-3838.12265

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

DOI: 10.1177/0956797620948841

DOI: 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

DOI: 10.2308/HORIZONS-2021-027

DOI: 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.

DOI: 10.1016/j.ijinfomgt.2014.10.007

DOI: 10.1108/MAJ-12-2019-2513

DOI: 10.1016/j.acclit.2017.05.003

DOI: 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.

DOI: 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

DOI: 10.2308/jeta-10511

DOI: 10.5937/StraMan2104028I

DOI: 10.2991/aebmr.k.200312.334

DOI: 10.1111/auar.12305

DOI: 10.1016/j.accinf.2019.100431

DOI: 10.2308/jeta-51730

DOI: 10.2308/HORIZONS-19-145

DOI: 10.1108/PAR-06-2021-0107

DOI: 10.1109/MC.2021.3067225

DOI: 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.

DOI: 10.1177/0268396221990778

DOI: 10.1037/amp0000972

DOI: 10.2139/ssrn.3877347

DOI: 10.1108/JAAR-10-2020-0207

DOI: 10.1108/MEDAR-08-2021-1399

DOI: 10.31617/visnik.knute.2020(131)09

DOI: 10.3390/su13115788

DOI: 10.3390/su14137804

DOI: 10.3390/educsci10070180

DOI: 10.1016/j.bar.2019.04.002

DOI: 10.1007/978-3-030-76313-8_7

DOI: 10.1007/978-3-030-76313-8_6

DOI: 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.

DOI: 10.1007/978-3-031-52403-5_11

DOI: 10.24193/subbnegotia.2024.1.01

DOI: 10.1007/s10551-019-04407-1

DOI: 10.5937/ekonomika2103075M

DOI: 10.1051/shsconf/202110001001

DOI: 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.

DOI: 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.

DOI: 10.33516/maj.v57i9.26-29p

DOI: 10.1080/09638180.2021.1882320

DOI: 10.55197/qjssh.v2i4.89

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

DOI: 10.1007/978-3-030-72651-5_43

DOI: 10.58729/1941-6679.1477

DOI: 10.52728/ijtc.v1i3.101

DOI: 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.

DOI: 10.1007/978-3-030-29739-8_22

DOI: 10.4018/978-1-6684-4950-9.ch009

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

DOI: 10.9734/ajeba/2019/v10i130099

DOI: 10.1016/j.accinf.2024.100676

DOI: 10.5937/AnEkSub2300014V

DOI: 10.2308/JETA-2022-072

DOI: 10.25236/IJNDES.2023.070303

DOI: 10.1016/j.jesp.2022.104327