Title:
Artificial Intelligence and the Evolution of Accounting and Audit Practices: A Systematic Review

Authors:
Rifa Atrous, Tunisia

Abstract:

This paper aims to provide a systematic literature review on the integration of artificial intelligence (AI), including machine learning and deep learning, into the fields of accounting and auditing. Drawing on a corpus of 575 publications extracted from Scopus for the period 2021 to 2025, the study examines the models employed, their applications, and the factors that facilitate or hinder the adoption of AI within the accounting profession. The findings show that supervised models such as logistic regression, decision trees, and neural networks are widely used to enhance audit accuracy, detect fraud, and predict financial risks, while robotic process automation (RPA) contributes to operational efficiency and the streamlining of repetitive tasks. The adoption of AI is also shaped by organizational and human factors, including practitioners' acceptance, skills development, and compliance with ethical and regulatory frameworks. The study further highlights the complementarity of AI with other emerging technologies such as blockchain and cloud computing and underscores its systemic role in improving both economic and social performance. Overall, the findings provide an integrated perspective on recent trends and key issues related to AI in accounting and auditing, while opening avenues for future research on the adoption and optimization of these technologies.

DOI: https://doi.org/10.51505/IJEBMR.2025.91205