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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17337462
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Auditing, Earnings Management, Governance
article

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

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
Wolters Kluwer (Netherlands) (NL), Wolters Kluwer Health (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Auditing, Earnings Management, Governance
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