Integrating Articial Intelligence into Modern Audit Processes

This research paper by David Bakinsky, JD, "Integrating Artificial Intelligence into Modern Audit Processes in 2025," provides an in-depth examination of the dynamic transformation occurring in auditing due to the rapid development of Artificial Intelligence (AI) and its associated technologies. The article begins with a foundational overview of AI concepts pertinent to auditing, then explores transformative AI applications, their diverse benefits, such as enhanced efficiency, accuracy, and fraud detection and critically addresses associated challenges including data quality, algorithmic bias, ethical dilemmas, and implementation hurdles. Furthermore, the paper discusses the evolving responsibilities of auditors, the shifting regulatory framework, and the future trajectory of AI in the field. The analysis concludes that while AI presents unprecedented opportunities to improve audit quality and analytical insights, its successful and ethical adoption necessitates proactive strategies to manage technological, human capital, and regulatory issues, ultimately redirecting auditors towards higher-level strategic functions.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-24
DOI
https://doi.org/10.5281/zenodo.15511691
Primary Topic
Auditing, Earnings Management, Governance
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating Articial Intelligence into Modern Audit Processes

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

Integrating Articial Intelligence into Modern Audit Processes

article en

Abstract

This research paper by David Bakinsky, JD, "Integrating Artificial Intelligence into Modern Audit Processes in 2025," provides an in-depth examination of the dynamic transformation occurring in auditing due to the rapid development of Artificial Intelligence (AI) and its associated technologies. The article begins with a foundational overview of AI concepts pertinent to auditing, then explores transformative AI applications, their diverse benefits, such as enhanced efficiency, accuracy, and fraud detection and critically addresses associated challenges including data quality, algorithmic bias, ethical dilemmas, and implementation hurdles. Furthermore, the paper discusses the evolving responsibilities of auditors, the shifting regulatory framework, and the future trajectory of AI in the field. The analysis concludes that while AI presents unprecedented opportunities to improve audit quality and analytical insights, its successful and ethical adoption necessitates proactive strategies to manage technological, human capital, and regulatory issues, ultimately redirecting auditors towards higher-level strategic functions.

Zenodo (CERN European Organization for Nuclear Research)
Temple College (US), Temple University (US)
Openalex Percentile: Top 43%
Auditing, Earnings Management, Governance
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