Artificial Intelligence and Performance of Auditors in the Big Four Audit Firms in Nigeria

Mary Kehinde Salawu () and Mariam Gbolasie Elegbede
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Mary Kehinde Salawu: Obafemi Awolowo University
Mariam Gbolasie Elegbede: Obafemi Awolowo University

A chapter in Impacting Society Positively Through Technology in Accounting and Business Processes, 2025, pp 839-857 from Springer

Abstract: Abstract The study analysed the effect of artificial intelligence (AI) on the performance of auditors in the audit industry in Nigeria. The study employed descriptive survey research design. The target population for the study were 3240 staff of the Big Four audit firms in Lagos State, Nigeria. This comprised Klynveld Peat Marwick Goerdeler International Limited [KPMG] (1000), Ernst & Young [EY] (640), PricewaterhouseCoopers Corporation [PwC]) (1000) and Deloitte (600). Data were sourced from the websites of the Big Four audit firms. Taro Yamane formula was used to obtain a sample size of 356 respondents, and proportionate sampling technique was used to administer structured questionnaire to the respondents to elicit information on the effect of application of AI on performance in Big Four audit firms. Data were analysed using frequency, mean, percentages and regression analysis. The results revealed that artificial intelligence usage had a positive significant effect on the performance of auditors in the audit industry. The study recommended that audit firms should consider factors such as audit software, gender and professional qualifications in AI integration strategies to maximise its benefits across diverse auditor profiles. Also, management should provide support to auditors to maximise the utilisation of specialised software for various audit tasks most especially to focus on identification of risk and assessment of internal control.

Keywords: Artificial intelligence; Big Four; Audit; Performance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-84885-8_46

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DOI: 10.1007/978-3-031-84885-8_46

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