Skip to content
Research Article Open access CC BY 4.0

Challenges and Opportunities of Implementing Artificial Intelligence in Auditing Practices: A Case Study of Nigerian Accounting Firms

Oluyinka Isaiah Oluwagbade, Olayinka Dominion Boluwaji, Oyebanji Abiola Azeez, Lakori Micah Njengo

Asian Journal of Economics, Business and Accounting · pp. 32–45 · Published 4 Jan 2024

10.9734/ajeba/2024/v24i11210

Abstract

The ever-evolving nature of the worldwide business arena is undergoing a significant change propelled by technological progress, where artificial intelligence (AI) is emerging as a central force redefining conventional methodologies. This research intends to identify and dissect the challenges encountered by Nigerian accounting firms in incorporating AI into their auditing processes, and to illuminate the opportunities that arise from leveraging AI capabilities in the auditing domain. This research utilized a survey research design. A well-structured questionnaire was employed to gather data from statutory auditors familiar with the use of artificial intelligence within their accounting firms situated in Lagos, the commercial hub of the Nigerian economy. The study encompassed all 35 registered accounting firms in Lagos State, Nigeria, employing a census sampling technique to determine the sample size, representing 100% of the population. Given the relative size of the population, five respondents were chosen from each accounting firm, totaling 175 respondents. The study received 153 responses, constituting 87% of the sample size. Descriptive and inferential statistics were applied to analyze the collected data. The outcomes reveal that AI, encompassing machine learning, natural language processing, and expert systems, significantly contributes to identifying challenges and highlighting opportunities in this context. The results underscore the positive role of AI in addressing challenges and revealing potential advancements in auditing practices within Nigerian accounting firms. The study concludes that AI, particularly machine learning, holds promise for addressing challenges and fostering advancements in auditing practices for Nigerian accounting firms. Given the significant positive impact of machine learning, accounting firms in Nigeria should consider prioritizing the integration of machine learning technologies into their auditing practices.

Artificial intelligence machine learning expert systems natural language processing auditing practices Nigerian accounting firm

References (24)

  1. 1 Theory of the firm: Managerial behavior, agency costs and ownership structure [DOI]
  2. 2 Theory of the firm; managerial Behavior, Agency Costs, and Ownership Structure [DOI]
  3. 3 The Emergence of Artificial Intelligence: How Automation is Changing Auditing [DOI]
  4. 4 Machine learning and data mining in manufacturing [DOI]
  5. 5 The Ethical Implications of Using Artificial Intelligence in Auditing [DOI]
  6. 6 Research Ideas for Artificial Intelligence in Auditing: The Formalization of Audit and Workforce Supplementation [DOI]
  7. 7 Credibility of sustainability reports: The contribution of audit committees [DOI]
  8. 8 The application of artificial intelligence in auditing: Looking back to the future [DOI]
  9. 9 The effect of artificial intelligence technologies on audit evidence [DOI]
  10. 10 Audit Quality Practices and Financial Reporting in Nigeria [DOI]
  11. 11 Artificial intelligence and audit quality: Implications for practicing accountants [DOI]
  12. 12 Application of Artificial Intelligence and Audit Quality in Nigeria [DOI]
  13. 13 Audit Quality Indicators: Audit Practice Meets Audit Research [DOI]
  14. 14 Adoption of Cloud Computing on the Efficacy of Accounting Practices in Nigeria [DOI]
  15. 15 Artificial Intelligence and Service Quality of Telecommunication Firms in Nigeria [DOI]
  16. 16 An Assessment of the Impact of Disruptive Technologies on the Efficacy of Accounting Practices in Selected South Western States, Nigeria [DOI]
  17. 17 Artificial Intelligence in Auditing : The Case of the Portuguese Statutory Auditors [DOI]
  18. 18 Robotic Process Automation for Auditing [DOI]
  19. 19 International Journal of Research and Innovation in Social Science [DOI]
  20. 20 Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society [DOI]
  21. 21 Man Versus Machine: Complex Estimates and Auditor Reliance on Artificial Intelligence [DOI]
  22. 22 Journal of Accounting and Financial Management [DOI]
  23. 23 Advances in Multidisciplinary & Scientific Research Journal Publication [DOI]
  24. 24 Evaluation of Artificial Intelligence and Efficacy of Audit Practice in Nigeria [DOI]

Cited by 15

Balancing innovation and accountability: AI’s transformative influence on logistics in G20 nations

Ya Li, Zheng Guangwen · Humanities and Social Sciences Communications · 2025

GenAI and reshaping the job market of accounting and auditing profession in Jordan: insights for digital transformation in accounting curriculum

Sokiyna Hamad Alliemoun, Krayyem Al-Hajaya · Higher Education, Skills and Work-Based Learning · 2025

Auditor’s willingness to learn and its effect on the intention to use AI technologies in the audit process: evidence from emerging economies

Ebrahim Mahmoud Mansour, Lina Al-Zyod, Esam Emad Ghassab · Journal of Financial Reporting and Accounting · 2025

Factors influencing artificial intelligence implementation in the accounting industry: a comparative study among private and public sectors

Wael Abdallah, Arezou Harraf, Hasan Al Wael · Journal of Financial Reporting and Accounting · 2025

The AI Surge: Transfiguring Audit Profession With AI Technology

Suhaib B. Bani Kinana, Omar Arabiat · Technological Horizons · 2025

Showing 6 of 15 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

22

Page views

0

PDF downloads

11

Outbound clicks

15

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.