Integration of AI and Auditors’ Cognitive Abilities: The Effects of A Questioning Mind and Suspension of Judgment on Audit Judgment
DOI:
https://doi.org/10.30659/jai.15.1.29-48Abstract
AbstractThe increasing integration of artificial intelligence (AI) in auditing has prompted renewed attention to how technology interacts with auditors’ professional skepticism and ultimately shapes their judgment quality. This study investigates the effects of questioning mind, suspension of judgment, and AI usage on auditor judgment using survey data from 93 Indonesian auditors across Big 4 and non-Big 4 firms, analyzed through SMART-PLS and multiple regression. Results indicate that both components of professional skepticism significantly enhance auditor judgment, with questioning mind exerting the strongest direct influence. However, the moderating role of AI presents a more complex dynamic: AI usage weakens the relationship between questioning mind and auditor judgment. Conversely, AI strengthens the effect of suspension of judgment on auditor. These findings collectively emphasize that the value of AI in auditing is not uniform but depends heavily on specific cognitive attributes of auditors— highlighting that AI serves best as a complementary resource whose benefits arise when paired with appropriate cognitive strategies. The study further suggests the need for future research on experience-level differences, AI literacy training, and the evolving capabilities of generative AI in shaping more effective human–AI judgment symbiosis.
References
Abdulrahman M, A.-Z. (2024). Balancing Act: Exploring the Interplay Between Human Judgment and Artificial Intelligence in Problem-solving, Creativity, and Decision-making. IgMin Research, 2(3), 145–158. https://doi.org/10.61927/igmin158
Ais Sahla, W., & Latif, D. M. (2023). Perceptions of Artificial Intelligence (AI) Usage on Auditor Judgment. In Indonesian Journal of Applied Accounting and Finance (Vol. 3, Number 2).
Almaqtari, F. A. (2024). The Role of IT Governance in the Integration of AI in Accounting and Auditing Operations. Economies, 12(8). https://doi.org/10.3390/economies12080199
Andrae, S. (2024). Critical Thinking in the Age of Algorithms (pp. 221–258). https://doi.org/10.4018/979-8-3373-1692-5.ch010
Bertomeu, J., Cheynel, E., Floyd, E., & Pan, W. (2021). Using machine learning to detect misstatements. Review of Accounting Studies, 26(2), 468–519. https://doi.org/10.1007/s11142-020-09563-8
Black, S., & Gerard, G. J. (2025). Accelerating the future of audit technologies: Introducing the special issue and emphasizing future research directions. In International Journal of Accounting Information Systems (Vol. 56). Elsevier Inc. https://doi.org/10.1016/j.accinf.2025.100740
Bonner, S. E. (1999). Judgment and Decision-Making Research in Accounting. Accounting Horizons, 13(4), 385–398. https://doi.org/10.2308/acch.1999.13.4.385
Chasokela, D., & Hlongwane, J. (2025). Assessing Higher-Order and Critical Skills in the Era of Artificial Intelligence (pp. 285–314). https://doi.org/10.4018/979-8-3693-6351-5.ch010
Cilliers, S. (2023). Emotional intelligence as a key driver of the formation of professional scepticism in auditors. South African Journal of Business Management, 54(1), 1–5. https://doi.org/10.4102/sajbm.v54i1.3654
Ciołek, M. (2002). An Audit of Internal Control over Financial Reporting Performed in Conjunction with an Audit of Financial Statements. In A Journal of Practice & Theory", issue (Vol. 29, Number 14). PCAOB. https://pcaobus.org/
Dalwai, T., Madbouly, A., & Mogammadi, S. S. (2022). An Investigation of Artificial Intelligence Application in Auditing. In Accounting, Finance, Sustainability, Governance & Fraud: Theory and Application Artificial Intelligence and COVID Effect on Accounting (pp. 101–114). Springer.
DeAngelo, L. E. (1981). Auditor size and audit quality. Journal of Accounting and Economics, 3(3), 183–199. https://doi.org/10.1016/0165-4101(81)90002-1
DELIU, D. (2024). Professional Judgment and Skepticism Amidst the Interaction of Artificial Intelligence and Human Intelligence. Audit Financiar, 22(176), 724–741. https://doi.org/10.20869/AUDITF/2024/176/024
Elsa Natali, Dea Maharani, & Nera Marinda Machdar. (2024). Literature Review: Pengaruh Independensi, Skeptisme, dan Akuntabilitas Terhadap Kualitas Audit. Jurnal Riset Ekonomi Dan Akuntansi, 2(2), 186–199. https://doi.org/10.54066/jrea-itb.v2i2.1852
Falco, G., Shneiderman, B., Badger, J., Carrier, R., Dahbura, A., Danks, D., Eling, M., Goodloe, A., Gupta, J., Hart, C., Jirotka, M., Johnson, H., LaPointe, C., Llorens, A. J., Mackworth, A. K., Maple, C., Pálsson, S. E., Pasquale, F., Winfield, A., & Yeong, Z. K. (2021). Governing AI safety through independent audits. In Nature Machine Intelligence (Vol. 3, Number 7, pp. 566–571). Nature Research. https://doi.org/10.1038/s42256-021-00370-7
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. In Source: Journal of Marketing Research (Vol. 18, Number 1).
Friska, R., & Agustia, D. (2025). Enhancing Auditor Judgment Quality: A Review of Evidence from Experimental Research. In Journal of Risk and Financial Management (Vol. 18, Number 3). Multidisciplinary Digital Publishing Institute (MDPI). https://doi.org/10.3390/jrfm18030115
Gonsalves, C. (2024). Generative AI’s Impact on Critical Thinking: Revisiting Bloom’s Taxonomy. Journal of Marketing Education. https://doi.org/10.1177/02734753241305980
Goodhue, D. L., & Thompson, R. L. (1995). Task-Technology Fit and Individual Performance. MIS Quarterly, 19(2), 213–236. https://doi.org/10.2307/249689
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hurtt, R. K. (2010). Development of a Scale to Measure Professional Skepticism. AUDITING: A Journal of Practice & Theory, 29(1), 149–171. https://doi.org/10.2308/aud.2010.29.1.149
Kadous, K., Nolder, C. J., & Peecher, M. E. (2019). The Role of the Attitudes in Auditing Research and Directions for Future Research. In Handbook of Attitudes (2nd ed.). Albarracin, D., & Johnson, B.T. (Eds.) Routledge (Taylor & Francis Group).
Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling (3rd ed.). New York: The Guilford Press.
Lipych, L., Melnyk, K., Bortnik, S., Vizniak, Y., & Kozoriz, M. (2022). AUDIT POLICY OF AUDIT ENTITIES IN CONDITIONS OF SUSTAINABLE DEVELOPMENT. Financial and Credit Activity: Problems of Theory and Practice, 2(43), 39–45. https://doi.org/10.55643/fcaptp.2.43.2022.3580
Lombardi, D. R., Kim, M., Sipior, J. C., & Vasarhelyi, M. A. (2025). The increased role of advanced technology and automation in audit: A delphi study. International Journal of Accounting Information Systems, 56. https://doi.org/10.1016/j.accinf.2025.100733
Mökander, J., & Floridi, L. (2021). Ethics-Based Auditing to Develop Trustworthy AI. In Minds and Machines (Vol. 31, Number 2, pp. 323–327). Springer Science and Business Media B.V. https://doi.org/10.1007/s11023-021-09557-8
Molina-Perez, E., Cortes, P., Molina, I., Sobrino, F., Tellez, M., Orozco, Y., Castellón, M., Popper, S., & Serra, L. (2024). The Impact of Artificial Intelligent Tools on Decision Making Behavioral and Neural Dynamics. https://doi.org/10.21203/rs.3.rs-4651166/v1
Nelson, M. W. (2009). A Model and Literature Review of Professional Skepticism in Auditing. Auditing: A Journal of Practice & Theory, 28(2), 1–34. https://doi.org/10.2308/aud.2009.28.2.1
Ojewale, V., Steed, R., Vecchione, B., Birhane, A., & Raji, I. D. (2025, April 26). Towards AI Accountability Infrastructure: Gaps and Opportunities in AI Audit Tooling. Conference on Human Factors in Computing Systems - Proceedings . https://doi.org/10.1145/3706598.3713301
Pérez-Calderón, E., Alrahamneh, S. A., & Milanés Montero, P. (2025). Impact of artificial intelligence on auditing: an evaluation from the profession in Jordan. Discover Sustainability, 6(1). https://doi.org/10.1007/s43621-025-01058-3
Quadackers, L., Groot, T., & Wright, A. (2009). Auditors’ Skeptical Characteristics and Their Relationship to Skeptical Judgments and Decisions. https://doi.org/https://doi.org/10.2139/SSRN.1478105
Quadackers, L., Groot, T., & Wright, A. (2012). Auditors’ Professional Skepticism: Neutrality Versus Presumptive Doubt. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2162947
Quadackers, L. M. (2009). A study of auditors’ skeptical characteristics and their relationship to skeptical judgments and decisions.
Richins, G., Trotman, K. T., & Yang, D. (2024). The effects of prevalence induced concept change on audit scepticism judgements. Accounting and Finance, 64(4), 4429–4446. https://doi.org/10.1111/acfi.13312
Shivram, V. (2024). AUDITING WITH AI: A THEORETICAL FRAMEWORK FOR APPLYING MACHINE LEARNING ACROSS THE INTERNAL AUDIT LIFECYCLE. EDPACS, 69(1), 22–40. https://doi.org/10.1080/07366981.2024.2312025
Toba, Y. (2011). Toward a Conceptual Framework of Professional Skepticism in Auditing. In WASEDA BUSINESS & ECONOMIC STUDIES (Number 47).
Downloads
Published
Issue
Section
License
Jurnal Akuntansi Indonesia is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License 
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities tacitly or explicitly of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with JAI agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.






ALLIANCE