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.
Institutions
- Wolters Kluwer (Netherlands) (NL)
- Wolters Kluwer Health (US)
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