The Transformational Impact of Artificial Intelligence on Audit Quality: An Empirical Study in an Emerging Market

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.

Authors

Publication Details

Journal
International Journal of Financial Administrative and Economic Sciences
Published
2025-10-08
DOI
https://doi.org/10.59992/ijfaes.2025.v4n10p1
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

The Transformational Impact of Artificial Intelligence on Audit Quality: An Empirical Study in an Emerging Market

Huda A. Muhammad
International Journal of Financial Administrative and Economic Sciences
Impact of AI and Big Data on Business and Society
article

The Transformational Impact of Artificial Intelligence on Audit Quality: An Empirical Study in an Emerging Market

Huda A. Muhammad
article en

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.

International Journal of Financial Administrative and Economic SciencesVol. 4(10)
Openalex Percentile: Top 67%
Impact of AI and Big Data on Business and Society
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