Skip to content
Research Article Open access CC BY 4.0

Evaluation of Artificial Intelligence and Efficacy of Audit Practice in Nigeria

Victor Olufemi Owonifari, Igbekoyi Olusola Esther, Niyi Solomon Awotomilusi, Dagunduro Muyiwa Emmanuel

Asian Journal of Economics, Business and Accounting · pp. 1–14 · Published 10 Jun 2023

10.9734/ajeba/2023/v23i161022

Abstract

Artificial Intelligence (AI) has become increasingly popular globally as a crucial tool for auditing financial statements, but in Nigeria, the adoption and use of AI tools by auditors is still in its early stages. Attention has been primarily focused on the Big 4 accounting firms, with little attention given to small-scale audit practitioners in Nigeria. This study seeks to examine the impact of AI on audit practice in Nigeria by employing a survey research design. The population of this study comprises 89 accounting firms operating in the Ikeja Local Government area of Lagos State, with a sample size of 62 firms selected using purposive sampling. Data was collected through a well-structured questionnaire, and the reliability of the research instrument was confirmed with a Cronbach Alpha test result of an average of 70%. Descriptive analysis and regression analysis were used to analyze the data, and the results indicated that data mining, machine learning, and image recognition exhibited a significant positive relationship with audit practice in Nigeria. The study concluded that the use of AI will enable auditors to predict future trends and make more informed decisions that focus on improving audit practice. The study recommended constant training of accountants and audit personnel on the use of data mining techniques to improve audit practice, investment in machine learning tools by audit firms in Nigeria, and increased use of image recognition to assist in object classification.

Audit practice data mining artificial intelligence image recognition machine learning

Cited by 11

Article metrics

Real usage data collected on this platform.

0

Page views

0

PDF downloads

0

Outbound clicks

11

Citations

Views by country

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

No views recorded yet.

Traffic sources

Referring site, by host.

No traffic recorded yet.

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.