Opportunities and Challenges in Integrating Artificial Intelligence into Financial Auditing

This research examines the opportunities and challenges in the integration of Artificial Intelligence (AI) in the financial audit process in the era of the Industrial Revolution 4.0. AI has great potential to improve audit efficiency and accuracy by automating routine tasks, detecting anomalies, and reducing human error in financial reporting. However, the application of this technology is not free from significant challenges, such as limited auditor expertise in using AI, transparency of algorithms that often function as “black boxes,” and data security and privacy risks.This research uses a qualitative approach with a literature study method, analyzing secondary data from scientific journals, industry reports, and related regulatory documents. The results show that although AI is capable of automating many routine tasks, auditors still play an important role in assessing the results produced by AI. Existing challenges, such as limited auditor knowledge and algorithm transparency issues, can be addressed through intensive training and the development of easier-to-understand algorithms.In conclusion, AI can strengthen the audit process if implemented appropriately, providing benefits in terms of efficiency and accuracy. However, its successful implementation relies heavily on auditors' ability to adapt to the technology and the development of solutions that address the challenges.

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Publication Details

Journal
Journal of Economic Education and Entrepreneurship Studies
Published
2024-10-31
DOI
https://doi.org/10.62794/je3s.v5i4.4563
Citations
3
Primary Topic
Stock Market Forecasting Methods
Type
article
Field-Weighted Citation Impact
1.47
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article

Opportunities and Challenges in Integrating Artificial Intelligence into Financial Auditing

Sifera Patricia Maithy, Pratiwi Hamzah, Evinalia Yeba, Gema Borneo Poetra
3 citations
Journal of Economic Education and Entrepreneurship Studies
Stock Market Forecasting Methods
1.47
article

Opportunities and Challenges in Integrating Artificial Intelligence into Financial Auditing

Sifera Patricia Maithy, Pratiwi Hamzah, Evinalia Yeba, Gema Borneo Poetra
article en
3 citations

Abstract

This research examines the opportunities and challenges in the integration of Artificial Intelligence (AI) in the financial audit process in the era of the Industrial Revolution 4.0. AI has great potential to improve audit efficiency and accuracy by automating routine tasks, detecting anomalies, and reducing human error in financial reporting. However, the application of this technology is not free from significant challenges, such as limited auditor expertise in using AI, transparency of algorithms that often function as “black boxes,” and data security and privacy risks.This research uses a qualitative approach with a literature study method, analyzing secondary data from scientific journals, industry reports, and related regulatory documents. The results show that although AI is capable of automating many routine tasks, auditors still play an important role in assessing the results produced by AI. Existing challenges, such as limited auditor knowledge and algorithm transparency issues, can be addressed through intensive training and the development of easier-to-understand algorithms.In conclusion, AI can strengthen the audit process if implemented appropriately, providing benefits in terms of efficiency and accuracy. However, its successful implementation relies heavily on auditors' ability to adapt to the technology and the development of solutions that address the challenges.

Journal of Economic Education and Entrepreneurship StudiesVol. 5(4)
University of Palangka Raya (ID)
Peace, Justice and strong institutions
Openalex Percentile: Top 16%
Stock Market Forecasting Methods
1.47
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Opportunities and Challenges in Integrating Artificial Intelligence into Financial Auditing — Sifera Patricia Maithy, Pratiwi Hamzah, et al. · Journal of Economic Education and Entrepreneurship Studies (2024) | TGRS Research Map | TGRS