The Impact of Digitalisation and Information Technology on the Audit Process and Auditor Decision-Making
DOI:
https://doi.org/10.37385/ijedr.v6i6.9649Keywords:
Audit Digitalisation, Information Technology, Artificial Intelligence, Auditor Decision-Making, Audit Quality, Blockchain, RPAAbstract
Developments in digitalisation and information technology have changed the perspective on the auditing profession, shifting from traditional manual practices to integrated technology in auditing. The purpose of this study is to analyse in depth how technologies such as Artificial Intelligence (AI), Big Data Analysis, Blockchain, Robotic Process Automation (RPA), and Enterprise Resource Planning (ERP) influence audit procedures and decision-making by auditors. Using a descriptive and exploratory literature review approach, this study combines the latest empirical and conceptual findings for the period 2021 to 2025. The results show that digitalisation improves efficiency, accuracy, and transparency in auditing through process automation and large-scale data analysis. The use of AI and RPA allows auditors to focus more on strategic analysis and risk assessment, while blockchain improves the reliability of audit evidence by recording immutable transactions. However, this transformation also brings challenges such as a lack of digital competence among auditors, the risk of dependence on automated systems, and ethical and cybersecurity issues. Therefore, success in digital auditing depends not only on the use of technology, but also on good digital literacy, ready infrastructure, and effective ethical governance. This study contributes theoretically to the understanding of the relationship between digitisation and auditor decision-making, and points the way for future research on the impact of technology on auditor independence and professionalism in the digital age.
References
Ajzen, I. (1991). The theory of planned behaviour. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Al Mandalawi, S., Mohammed, M. A., Maclean, H., Cakmak, M. C., & Talburt, J. R. (2025, October 27). Policy-aware generative AI for safe, auditable data access governance (arXiv:2510.23474). arXiv. https://arxiv.org/abs/2510.23474
Alqudah, H., Mansour, Z., Salem, B., & Lutfi, A. (2024). Enhancing the internal auditors’ effectiveness in Jordanian companies: The impact of cloud-based accounting usage and the moderating role of digital proficiency. Computers in Human Behavior Reports, 15, 100442. https://doi.org/10.1016/j.chbr.2024.100442
Azizi, M., Hakimi, M., Amiri, F., & Shahidzay, A. K. (2024). The role of IT (information technology) audit in digital transformation: Opportunities and challenges. Open Access Indonesia Journal of Social Sciences, 7(2). https://doi.org/10.37275/oaijss.v7i2.230
Bani, P., Siregar, N., Subiyanto, B., & Awaludin, D. T. (2025). Digital transformation in the audit process: A systematic review of innovation, challenges, and its impact on audit quality. Journal of Management and Accounting Review, 5(3), 3454–3471.
Bellinga, J., Bosman, T., Höcük, S., Janssen, W. H. P., & Khzam, A. (2022). Robotic process automation for the extraction of audit information: A use case. Current Issues in Auditing, 16(1), A1–A8. https://doi.org/10.2308/ciia-2020-043
Berger, A., Hillebrand, L., Leonhard, D., Deußer, T., de Oliveira, T. B. F., Dilmaghani, T., Khaled, M., Kliem, B., Loitz, R., Bauckhage, C., & Sifa, R. (2025, July 22). Towards automated regulatory compliance verification in financial auditing with large language models (arXiv:2507.16642). arXiv. https://arxiv.org/abs/2507.16642
Chen, N., & Fang, J. (2025). The aggregate release of third-party online sales data and audit quality improvement. China Journal of Accounting Research, 18(1), 100376. https://doi.org/10.1016/j.cjar.2024.100376
Dahiyat, A. (2022). Robotic process automation and audit quality. Corporate Governance and Organisational Behavior Review, 6(1), 160–167. https://doi.org/10.22495/cgobrv6i1p12
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
Devianto, H., Mediaty, M., & Junus, A. (2025). A new era of audit by blockchain technology: Continuous auditing. In M. Nohong et al. (Eds.), Proceedings of the 9th International Conference on Accounting, Management, and Economics 2024 (ICAME 2024) (Vol. 331, pp. 849–857). Atlantis Press. https://doi.org/10.2991/978-94-6463-758-8_72
Fernsel, L., Kalff, Y., & Simbeck, K. (2024, November 15). Assessing the auditability of AI-integrating systems: A framework and learning analytics case study (arXiv:2411.08906). arXiv. https://arxiv.org/abs/2411.08906
Graves, M., & Ratti, E. (2025). A capability approach to ethical development and internal auditing of AI technology. Journal of Business Ethics, Advance online publication.
Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. https://doi.org/10.1016/j.accinf.2022.100598
Herath, S. K., & Joshi, P. L. (2023). Audit data analytics: A game changer for audit firms. International Journal of Auditing and Accounting Studies, 5(1), 29–48. https://doi.org/10.47509/IJAAS.2023.v05i01.02
Indarto, S. L., Ayu, S. D. R., & Setianto, Y. D. (2021). Big data analysis and its contribution to remote audit. International Journal of Advanced Research in Technology and Innovation, 3(4), 19–27. https://doi.org/10.55057/ijarti.2021.3.4.3
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behaviour, agency costs, and ownership structure. Journal of Financial Economics, 3(4), 305–360.
Jinghan, J., Huang, L., Zezhong, J., & Zhang, H. (2025). Do auditors charge clients higher audit fees for blockchain investments? Journal of International Accounting, Auditing and Taxation, 59, 100707. https://doi.org/10.1016/j.intaccaudtax.2025.100707
Leoc, D. (2024). Artificial intelligence in auditing: A conceptual framework for auditing practices. Administrative Sciences, 14(10), 238. https://doi.org/10.3390/admsci14100238
Li, B., Kaplan, B., Lazirko, M., & Kogan, A. (2021). Unsupervised outlier detection in audit analytics: A case study using USA spending data. Rutgers Business School Research Paper.
Lubis, P. S. (2025). Technological innovations in auditing: A systematic literature review on the use of AI and digitalisation. (Working paper).
Matta, J., & Chamoun, E. (2025). Exploring auditor adaptability in the digital era through levels of expertise: The role of IT literacy. Digital Business, 5(2), 100126. https://doi.org/10.1016/j.digbus.2025.100126
Ou, Q., & Wu, Y. (2025). A study on the impact of digital transformation on auditor decision making. Journal of Accounting and Finance, 18(2).
Peng, Y., Ahmad, S. F., Irshad, M., Al-Razgan, M., Ali, Y. A., & Awwad, E. M. (2023). Impact of digitalisation on process optimisation and decision-making towards sustainability: The moderating role of environmental regulation. Sustainability, 15(20), 15156. https://doi.org/10.3390/su152015156
Reichelt, V., Marten, K., Eulerich, M., & Tassilo, L. F. (2025). A framework for the structured implementation of process mining for audit tasks. International Journal of Accounting Information Systems, 56, 100727. https://doi.org/10.1016/j.accinf.2025.100727
Riyanto, J., Wijaya, T., Prasetyo, I., Rahmatika, N., & Indriasih, D. (2025). Artificial intelligence and audit quality: An empirical literature review from Scopus. International Journal of Accounting and Finance Studies, 20(1), 61–76.
Sampaio, C., & Silva, R. (2025). Digital transformation in accounting: An assessment of automation and AI integration. Working paper.
Sayal, A., Johri, A., Chaithra, N., Alhumoudi, H., & Alatawi, Z. (2025). Optimising audit processes through open innovation: Leveraging emerging technologies for enhanced accuracy and efficiency. Journal of Open Innovation: Technology, Market, and Complexity, 11(3), 100573. https://doi.org/10.1016/j.joitmc.2025.100573
Silva, T., Pedro, R., & Marques, P. (2023). The impact of ERP systems in internal auditing: The Portuguese case. Procedia Computer Science, 219, 963–970. https://doi.org/10.1016/j.procs.2023.01.373
Sugeng, L., Yan, C., & Liu, Y. (2025). How does sustainable audit digital explain the relationship between auditor empowerment and e-audit quality? Sustainable Futures, 10, 101229. https://doi.org/10.1016/j.sftr.2025.101229
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285.
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.
Waltersdorfer, L., Ekaputra, F. J., Miksa, T., & Sabou, M. (2024, June 20). AuditMAI: Towards an infrastructure for continuous AI auditing (arXiv:2406.14243). arXiv. https://arxiv.org/abs/2406.14243
Weeradaecha, K. (2021). Robotic process automation (RPA) for auditing (Master’s thesis). Faculty of Commerce and Accountancy, Thammasat University.
Yang, H., Guohua, W., Wanlong, G., Qinghai, H., & Yixian, Y. (2022). Audit-related applications of artificial intelligence systems. Procedia Computer Science, 202, 115–121. https://doi.org/10.1016/j.procs.2022.04.016
Zhang, Y., Ma, Z., & Meng, J. (2025). Auditing in the blockchain: A literature review. Frontiers in Blockchain, 8, Article 1549729. https://doi.org/10.3389/fbloc.2025.1549729
