AI in Indonesian Accounting Practices: Readiness, Ethical Challenges, and Financial Reporting Quality
DOI:
https://doi.org/10.61231/13kvsy32Keywords:
Artificial Intelligence, Accounting Practice, Professional Ethics, Institutional Readiness, Financial ReportingAbstract
This study evaluates Indonesian accounting institutions' readiness for AI adoption, identifies key ethical issues, and assesses AI's impact on reporting quality. Employing a mixed-methods approach, the study gathered quantitative data via a survey of 120 professional accountants and financial managers, alongside qualitative insights from in-depth interviews with 10 key informants across academia, practice, and regulatory bodies. Data were processed using descriptive statistics and inductive thematic analysis. Findings reveal a moderate level of institutional readiness. While technological infrastructure and managerial support are strong, significant weaknesses exist in internal policy formulation and digital ethics training. Major ethical challenges include system accountability, algorithmic bias, and process transparency. Regarding reporting quality, AI enhances information relevance, reliability, and timeliness, though understandability remains reliant on human interpretation.
References
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Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—an interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00659-3
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Ajiga, D. I. (2021). Strategic framework for leveraging artificial intelligence to improve financial reporting accuracy and restore public trust. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), 882–892. https://doi.org/10.54660/IJMRGE.2021.2.1.882-892
Antwi, B. O., Adelakun, B. O., & Eziefule, A. O. (2024). Transforming financial reporting with AI: Enhancing accuracy and timeliness. International Journal of Advanced Economics, 6(6), 205–223. https://doi.org/10.51594/ijae.v6i6.1229
Arisandi, A., Islami, H. A., & Soeprajitno, R. R. W. N. (2022). Internal control disclosure and financial reporting quality: Evidence from banking sector in Indonesia. E-Jurnal Akuntansi, 32(2), 3797–3806. https://doi.org/10.24843/EJA.2022.v32.i02.p15
Calado, S., & Veloso, C. M. (2025). Artificial Intelligence in Accounting: Driving Value Co-Creation, Compliance, and Ethical Transformation. In Empowering Value Co-Creation in the Digital Era (pp. 75–102). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-6684-8752-4.ch005
De Silva, P., Gunarathne, N., & Kumar, S. (2025). Exploring the impact of digital knowledge, integration and performance on sustainable accounting, reporting and assurance. Meditari Accountancy Research, 33(2), 497–552. https://doi.org/10.1108/MEDAR-02-2024-2383
Holzinger, A., Zatloukal, K., & Müller, H. (2024). Is Human Oversight to AI Systems still possible? New Biotechnology. https://doi.org/10.1016/j.nbt.2024.12.003
Huda, M. (2019). Empowering application strategy in the technology adoption: insights from professional and ethical engagement. Journal of Science and Technology Policy Management, 10(1), 172–192. https://doi.org/10.1108/JSTPM-12-2018-0110
Ivchyk, V. (2024). Overcoming barriers to artificial intelligence adoption. Three Seas Economic Journal, 5(4), 14–20.
Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or not, AI comes—an interview study of organizational AI readiness factors. Business & Information Systems Engineering, 63(1), 5–20. https://doi.org/10.1007/s12599-020-00659-3
Königstorfer, F., & Thalmann, S. (2020). Applications of Artificial Intelligence in commercial banks–A research agenda for behavioral finance. Journal of Behavioral and Experimental Finance, 27, 100352. https://doi.org/10.1016/j.jbef.2020.100352
Langer, M., Baum, K., & Schlicker, N. (2024). Effective human oversight of AI-based systems: A signal detection perspective on the detection of inaccurate and unfair outputs. Minds and Machines, 35(1), 1. https://doi.org/10.1007/s11023-023-09698-1
Martinez, D., Magdalena, L., & Savitri, A. N. (2024). AI and blockchain integration: Enhancing security and transparency in financial transactions. International Transactions on Artificial Intelligence, 3(1), 11–20. https://doi.org/10.33050/italic.v3i1.651
McNamara, A. J., Shirowzhan, S., & Sepasgozar, S. M. E. (2024). Investigating the determents of intelligent construction contract adoption: a refinement of the technology readiness index to inform an integrated technology acceptance model. Construction Innovation, 24(3), 702–724. https://doi.org/10.1108/CI-08-2023-0150
Murikah, W., Nthenge, J. K., & Musyoka, F. M. (2024). Bias and ethics of AI systems applied in auditing-A systematic review. Scientific African, e02281. https://doi.org/10.1016/j.sciaf.2024.e02281
Mwachikoka, C. F. (2024). Effects of artificial intelligence on financial reporting accuracy. World Journal of Advanced Research and Reviews, 23(3), 1751–1767. https://doi.org/10.30574/wjarr.2024.23.3.2791
Pasewark, W. R. (2021). Preparing accountants of the future: Five ways business schools struggle to meet the needs of the profession. Issues in Accounting Education, 36(4), 119–151. https://doi.org/10.2308/ISSUES-19-025
Pavlovic, M., Gligoric, C., Zdravkovic, F., & Pavlovic, D. (2024). Revolutionizing management accounting: the role of artificial intelligence in predictive analytics, automated reporting, and decision-making. Business & Management Compass, 68(4), 23–42. https://doi.org/10.56065/nxn2gx53
Qader, K. S., & Cek, K. (2024). Influence of blockchain and artificial intelligence on audit quality: Evidence from Turkey. Heliyon, 10(9). https://doi.org/10.1016/j.heliyon.2024.e30166
Rajagukguk, J. S. S., & Harnovinsah, J. M. V. (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, 6(1), 291–304. https://doi.org/10.56293/IJMSSSR.2024.4826
Samiolo, R., Spence, C., & Toh, D. (2024). Auditor judgment in the fourth industrial revolution. Contemporary Accounting Research, 41(1), 498–528. https://doi.org/10.1111/1911-3846.12901
Shaban, O. S., & Omoush, A. (2025). AI-Driven Financial Transparency and Corporate Governance: Enhancing Accounting Practices with Evidence from Jordan. Sustainability, 17(9), 3818. https://doi.org/10.3390/su17093818
Simkute, A., Tankelevitch, L., Kewenig, V., Scott, A. E., Sellen, A., & Rintel, S. (2025). Ironies of Generative AI: Understanding and Mitigating Productivity Loss in Human AI Interaction. International Journal of Human Computer Interaction, 41(5), 2898–2919. https://doi.org/10.1080/10447318.2024.2320966
Smith, L., & Lamprecht, C. (2024). Identifying the limitations associated with machine learning techniques in performing accounting tasks. Journal of Financial Reporting and Accounting, 22(2), 227–253. https://doi.org/10.1108/JFRA-05-2023-0280
Soori, M., Jough, F. K. G., Dastres, R., & Arezoo, B. (2024). AI-based decision support systems in Industry 4.0, A review. Journal of Economy and Technology. https://doi.org/10.1016/j.ject.2024.08.005
Wadipalapa, R. P., Katharina, R., Nainggolan, P. P., Aminah, S., Apriani, T., Ma’rifah, D., & Anisah, A. L. (2024). An ambitious artificial intelligence policy in a decentralised governance system: evidence from Indonesia. Journal of Current Southeast Asian Affairs, 43(1), 65–93. https://doi.org/10.1177/18681034231159737
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