ALGORITHMIC JUDGEMENT VERSUS PROFESSIONAL SKEPTICISM: REDEFINING AUDITOR DECISION-MAKING IN AI-SUPPORTED AUDITS
Keywords:
Algorithmic Judgment, Professional Skepticism, AI-Supported Audits, Auditor Decision-MakingAbstract
The development of artificial intelligence technology has brought significant changes to audit practice, particularly through the use of AI systems to support auditor decision-making. The emergence of intelligent algorithms has sparked debate regarding the role of algorithmic judgment versus auditor professional skepticism in the audit process. This study aims to analyze and redefine the dynamics of auditor decision-making in the context of AI-based audits using a literature review method. The literature review was conducted by reviewing various academic publications, professional reports, and empirical research related to the implementation of AI in audits, its impact on professional judgment, and the challenges in maintaining professional skepticism. The results indicate that although AI algorithms improve the efficiency and accuracy of risk detection, there is a risk of overreliance, which can reduce the level of auditor skepticism. This study emphasizes the importance of integrating professional judgment and critical evaluation of AI output, so that auditors maintain their oversight and independent assessment. These findings provide a theoretical contribution to the development of a modern audit framework that combines AI capabilities with the principle of professional skepticism.
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References
Abdullah, F., Olilingo, F. Z., Hinelo, R., & Amaliah, T. H. (2025). AI-Based Audit Judgment: A Systematic Analysis of the Integration Between Algorithmic Rationality and Auditor Professional Intuition. International Journal of Economics Studies, 2(3), 124–134. https://doi.org/10.59613/ijes.v2i3.15
Al-Omush, A., Almasarwah, A., & Al-Wreikat, A. (2025). Artificial intelligence in financial auditing: Redefining accuracy and transparency in assurance services. EDPACS, 70(6), 1–20. https://doi.org/10.1080/07366981.2025.2459490
Implementing AI in auditing in organizations. (2025). Journal of Accounting and Management Information Systems, 24(3), 456–478.
James, S., Williams, J., & Idowu, B. (2025). Integrating Neutrosophic Logic with AI-Supported Auditing for Enhanced Decision Transparency in Financial Systems.
Landers, R. N., & Behrend, T. S. (2023a). Auditing the AI auditors: A framework for evaluating fairness and bias in high stakes AI predictive models. American Psychologist, 78(1), 36–49. https://doi.org/10.1037/amp0000972
Landers, R. N., & Behrend, T. S. (2023b). Auditing the AI auditors: A framework for evaluating fairness and bias in high stakes AI predictive models. American Psychologist, 78(1), 36–49. https://doi.org/10.1037/amp0000972
Limba, F. B., Sapulette, S. G., & Sitanala, T. F. (2025a). AUDITOR PERCEPTION OF CLOUD TECHNOLOGY-BASED AUDITS. INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE, 3(5), 291–306.
Limba, F. B., Sapulette, S. G., & Sitanala, T. F. (2025b). AUDITOR PERCEPTION OF CLOUD TECHNOLOGY-BASED AUDITS. INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE, 3(5), 291–306.
Menguy, B., & El Khoury, K. (2025). Reframing Financial Decision-Making in the Age of AI: Rethinking Oversight, Accountability, and Control in the Algorithmic Era. https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-214602
Murikah, W., Nthenge, J. K., & Musyoka, F. M. (2024). Bias and ethics of AI systems applied in auditing—A systematic review. Scientific African, 25, e02281. https://doi.org/10.1016/j.sciaf.2024.e02281
Nuritdinovich, M. A., Bokhodirovna, K. M., Kavitha, V. O., & Ugli, S. A. O. (2025). Advanced AI algorithms in accounting: Redefining accuracy and speed in financial auditing. AIP Conference Proceedings, 3306(1), 050008. https://doi.org/10.1063/5.0275750
Onyenahazi, O. (2025). Integrating Artificial Intelligence in Financial Auditing to Enhance Accuracy, Efficiency, and Regulatory Compliance Outcomes. International Journal of Research Publication and Reviews, 02, 23–44. https://doi.org/10.55248/gengpi.6.0725.2402
Puthukulam, G., Ravikumar, A., Sharma, R. V. K., & Meesaala, K. M. (2021a). Auditors’ Perception on the Impact of Artificial Intelligence on Professional Skepticism and Judgment in Oman. Universal Journal of Accounting and Finance, 9(5), 1184–1190. https://doi.org/10.13189/ujaf.2021.090527
Puthukulam, G., Ravikumar, A., Sharma, R. V. K., & Meesaala, K. M. (2021b). Auditors’ Perception on the Impact of Artificial Intelligence on Professional Skepticism and Judgment in Oman. Universal Journal of Accounting and Finance, 9(5), 1184–1190. https://doi.org/10.13189/ujaf.2021.090527
Rajagukguk, J. S. S., Harnovinsah, & Mulyadi, Jmv. (2024). Evaluation of Audit Evidence Quality in Public Accounting Firms in DKI Jakarta: Perspectives of Professional Scepticism, Auditor Experience, and Artificial Intelligence Usage. International Journal of Management Studies and Social Science Research, 06(01), 291–304. https://doi.org/10.56293/IJMSSSR.2024.4826
Talla, A., Sapulette, S. G., & Limba, F. B. (2025). THE RELATIONSHIP BETWEEN PUBLIC SECTOR INTERNAL CONTROLS AND FRAUD PREVENTION. INTERNATIONAL JOURNAL OF ECONOMIC LITERATURE, 2(12), 2150–2170.
Tiron-Tudor, A., & Deliu, D. (2021a). Reflections on the human-algorithm complex duality perspectives in the auditing process. Qualitative Research in Accounting & Management, 19(3), 255–285. https://doi.org/10.1108/QRAM-04-2021-0059
Tiron-Tudor, A., & Deliu, D. (2021b). Reflections on the human-algorithm complex duality perspectives in the auditing process. Qualitative Research in Accounting & Management, 19(3), 255–285. https://doi.org/10.1108/QRAM-04-2021-0059
Żulicki, R. (2025). Skeptical to AI Like a Data Scientist. Results from a Polish Sociological Study of the So-Called Artificial Intelligence Developers Community and Suggestions for Academic Teachers. Lubelski Rocznik Pedagogiczny, 44, 59–75. https://doi.org/10.17951/lrp.2025.44.2.59-75
