The Transformational Impact of Artificial Intelligence on Audit Quality: An Empirical Study in an Emerging Market
DOI:
https://doi.org/10.59992/IJFAES.2025.v4n10p1Keywords:
Artificial Intelligence (AI), Audit Quality, Emerging Markets, Digital Transformation.Abstract
This study empirically examines the impact of Artificial Intelligence (AI) on audit quality in emerging markets. Based on survey data from 370 audit professionals analyzed using Structural Equation Modeling (SEM), the research assesses how AI dimensions—including Robotic Process Automation (RPA), Machine Learning (ML), Anomaly Detection (AD), and Explainable AI (XAI)—affect audit quality, measured by efficiency, accuracy, and auditor independence. The findings confirm a significant positive impact, as anomaly detection enhances accuracy, machine learning improves efficiency and independence, and explainable AI is crucial for building auditor trust in AI-derived evidence. The study offers an evidence-based framework for audit firms and regulators, contributing to the literature on technology adoption in professional services.
References
- Almufadda, G., & Almezeini, N. A. (2022). Artificial intelligence applications in the auditing profession: A literature review. Journal of Emerging Technologies in Accounting, 19(2), 29–42.
- Baaske, B. N., Eulerich, M., & Wood, D. A. (2025). Improving audit quality with data analytic visualizations: The importance of spatial abilities and feedback in anomaly identification. Accounting Horizons, 39(3), 85–97.
- Commerford, B. P., Eilifsen, A., Hatfield, R. C., Holmstrom, K. M., & Kinserdal, F. (2024). Control issues: How providing input affects auditors’ reliance on artificial intelligence. Contemporary Accounting Research, 41(4), 2134–2162.
- Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27(3), 938–985.
- Fotoh, L. E. (2025). Digital inventory audits: An alternative approach to physical observation in audit evidence gathering. Journal of Applied Accounting Research. Advance online publication.
- Freiman, J. W., Kim, Y., & Vasarhelyi, M. A. (2022). Full population testing: Applying multidimensional audit data sampling (MADS) to general ledger data auditing. International Journal of Accounting Information Systems, 46, 100573.
- Fulcer, K., Gu, H., Hu, H., Huang, Q., Kogan, A., Vasarhelyi, M. A., Wei, D., & Young, J. (2025). Application of outlier detection methods in audit analytics. Accounting Horizons, 39(3), 143–157.
- Gu, H., Schreyer, M., Moffitt, K., & Vasarhelyi, M. A. (2024). Artificial intelligence co-piloted auditing. International Journal of Accounting Information Systems, 54, 100698.
- Kamareldawla, N. M. (2025). External auditors’ perceptions toward the use of artificial intelligence in the audit process and ethical challenges facing its application: Evidence from an emerging market. Corporate Ownership & Control, 22(2), 171–184.
- Khan, F., Jan, S. U., & Zia-ul-haq, H. M. (2025). Artificial intelligence adoption, audit quality and integrated financial reporting in GCC markets. Asian Review of Accounting. Advance online publication.
- Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115–122.
- Kokina, J., Blanchette, S., & Davenport, T. H. (2025). Challenges and opportunities for artificial intelligence in auditing: Evidence from the field. International Journal of Accounting Information Systems, 56, 100734.
- Lai, J. (2025). Artificial intelligence applications and audit fees: An empirical study. International Review of Economics & Finance, 103, 104421.
- Law, K. K. F., & Shen, M. (2025). How does artificial intelligence shape audit firms? Management Science, 71(5), 3641–3666.
- Leocádio, D., Malheiro, L., & Reis, J. (2024). Artificial intelligence in auditing: A conceptual framework for auditing practices. Administrative Sciences, 14(10), 238.
- Li, Y., & Goel, S. (2025). Artificial intelligence auditability and auditor readiness for auditing artificial intelligence systems. International Journal of Accounting Information Systems, 56, 100739.
- Libby, R., & Witz, P. D. (2024). Can artificial intelligence reduce the effect of independence conflicts on audit firm liability? Contemporary Accounting Research. Advance online publication.
- Moffitt, K. C., Rozario, A. M., & Vasarhelyi, M. A. (2018). Robotic process automation for auditing. Journal of Emerging Technologies in Accounting, 15(1), 1–10.
- Mökander, J. (2023). Auditing of AI: Legal, ethical and technical approaches. Digital Society, 2, Article 49.
- Murikah, W., Nthenge, J. K., & Musyoka, F. M. (2024). Bias and ethics of AI systems applied in auditing – A systematic review. Scientific African, 25, e02281.
- Murphy, B., Feeney, O., Rosati, P., & Lynn, T. (2024). Exploring accounting and AI using topic modelling. International Journal of Accounting Information Systems, 55, 100709.
- Musa, A. M. H. (2024). Detecting the effect of artificial intelligence on internal audit performance: Empirical study in Saudi Arabia. Decision Science Letters, 13(4), 967–976.
- Noordin, N. A., Hussainey, K., & Hayek, A. F. (2022). The use of artificial intelligence and audit quality: An analysis from the perspectives of external auditors in the UAE. Journal of Risk and Financial Management, 15(8), 339.
- O’Leary, D. E., Richardson, V. J., & Weidenmier Watson, M. (2024). Data-driven audits: Audit analytic platforms and general ledger analytic tools. Current Issues in Auditing, 19(1), A1–A9.
- Pérez-Calderón, E., Alrahamneh, S. A., & Milanés Montero, P. (2025). Impact of artificial intelligence on auditing: An evaluation from the profession in Jordan. Discover Sustainability, 6, 251.
- Qader, K. S., & Cek, K. (2024). Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey. Heliyon, 10(9), e30166.
- Rahman, M. J., Zhu, H., & Yue, L. (2024). Does the adoption of artificial intelligence by audit firms and their clients affect audit quality and efficiency? Evidence from China. Managerial Auditing Journal, 39(6), 668–699.
- Samiolo, R., Spence, C., & Toh, D. (2024). Auditor judgment in the fourth industrial revolution. Contemporary Accounting Research, 41(1), 498–528.
- Sandu, I., Wiersma, M., & Manichand, D. (2022). Time to audit your AI algorithms. Maandblad voor Accountancy en Bedrijfseconomie, 96(7–8), 253–265.
- Seethamraju, R., & Hecimovic, A. (2023). Adoption of artificial intelligence in auditing: An exploratory study. Australian Journal of Management, 48(4), 780–800.
- Senave, E., Jans, M. J., & Srivastava, R. P. (2023). The application of text mining in accounting. International Journal of Accounting Information Systems, 50, 100624.
- Tan, J., Chang, S., & Zheng, Y. (2025). Client artificial intelligence application and audit quality. International Review of Financial Analysis, 104, 104271.
- Tragouda, M., Doumpos, M., & Zopounidis, C. (2024). Identification of fraudulent financial statements through a multi-label classification approach. Intelligent Systems in Accounting, Finance and Management, 31(2), e1564.
- Vitali, S., & Giuliani, M. (2024). Emerging digital technologies and auditing firms: Opportunities and challenges. International Journal of Accounting Information Systems, 53, 100676.
- Wei, D., Cho, S., Vasarhelyi, M. A., & Te-Wierik, L. (2024). Outlier detection in auditing: Integrating unsupervised learning within a multilevel framework for general ledger analysis. Journal of Information Systems, 38(2), 123–142.
- Zhang, C. A., Cho, S., & Vasarhelyi, M. A. (2022). Explainable artificial intelligence (XAI) in auditing. International Journal of Accounting Information Systems, 46, 100572.
- Zhao, T., & Duan, W. (2025). Auditors’ digital expertise and audit quality: Empirical evidence based on China’s A-share listed companies. Emerging Markets Finance and Trade. Advance online publication.
- Zhong, C., & Goel, S. (2024). Transparent AI in auditing through explainable AI. Current Issues in Auditing, 18(2), A1–A14.
