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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

AI-Powered Audit Lifecycle: Integrating machine learning in cloud-based accounting systems

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  • AI-Powered Audit Lifecycle: Integrating machine learning in cloud-based accounting systems

Ashif Anwar *

Wolters Kluwer, USA.

Review Article

World Journal of Advanced Research and Reviews, 2025, 26(02), 2753-2760

Article DOI: 10.30574/wjarr.2025.26.2.1868

DOI url: https://doi.org/10.30574/wjarr.2025.26.2.1868

Received on 05 April 2025; revised on 14 May 2025; accepted on 16 May 2025

This article explores the transformative impact of artificial intelligence and machine learning on cloud-based accounting systems throughout the audit lifecycle. It examines how AI-driven technologies are revolutionizing traditional audit methodologies by enabling transaction analysis, enhancing risk assessment accuracy, automating planning processes, and strengthening fraud detection capabilities. The article shows the evolution from manual, sample-based approaches to data-driven, continuous monitoring frameworks that provide real-time insights into organizational risks. Through an article analysis of implementation challenges, performance metrics, and future projections, this study demonstrates how cloud infrastructure combined with advanced analytics is creating more efficient, accurate, and compliant audit processes while fundamentally reshaping the skills required of audit professionals. The findings highlight both the quantifiable benefits of AI integration and the strategic considerations for organizations navigating this technological transition.

Artificial Intelligence; Cloud-Based Auditing; Machine Learning; Fraud Detection; Continuous Monitoring

https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2025-1868.pdf

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Ashif Anwar. AI-Powered Audit Lifecycle: Integrating machine learning in cloud-based accounting systems. World Journal of Advanced Research and Reviews, 2025, 26(2), 2753-2760. Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1868

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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