Peran Kecerdasan Buatan (Artificial Intelligence) dalam Transformasi Praktik Akuntansi dan Pengambilan Keputusan Keuangan: a Systematic Literature Review
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Abstract
Perkembangan pesat kecerdasan buatan (Artificial Intelligence atau AI) telah mendorong transformasi signifikan dalam profesi akuntansi, mulai dari otomatisasi proses hingga peningkatan kualitas pengambilan keputusan keuangan. Perubahan ini menuntut pemahaman yang komprehensif mengenai arah perkembangan, peluang, dan tantangan penerapan AI dalam bidang akuntansi. Penelitian ini bertujuan untuk mensintesis literatur internasional terkait peran AI dalam transformasi praktik akuntansi dan pengambilan keputusan keuangan selama periode 2021–2025. Penelitian menggunakan pendekatan kualitatif dengan desain Systematic Literature Review (SLR) berdasarkan protokol PRISMA 2020. Sumber data berasal dari artikel ilmiah yang terindeks pada Google Scholar, Scopus, ScienceDirect, dan Semantic Scholar, dengan tiga puluh lima artikel terpilih yang dianalisis menggunakan thematic content analysis dan perangkat bibliometrik VOSviewer. Hasil penelitian mengidentifikasi enam tema utama, yaitu otomatisasi akuntansi berbasis Robotic Process Automation (RPA), peningkatan kualitas audit melalui machine learning, transformasi pengambilan keputusan keuangan melalui analitik prediktif, pergeseran peran akuntan menuju fungsi yang lebih strategis, tantangan implementasi AI, serta isu etika dan tata kelola AI. Penelitian ini menyimpulkan bahwa AI telah menjadi katalis transformasi paradigmatik dalam ekosistem akuntansi yang tidak hanya meningkatkan efisiensi dan kualitas informasi, tetapi juga menuntut pengembangan kompetensi digital, kerangka regulasi yang adaptif, serta tata kelola teknologi yang bertanggung jawab.
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References
Adebayo, O., & Okafor, E. (2024). Ethical risks of Artificial Intelligence in accounting: A framework for responsible implementation. Journal of Applied Ethics in Professional Practice, 5(1), 12–31. https://doi.org/10.1080/jaepp.2024.0501.03
Al-Sartawi, A. M. M., Hamdan, A., Khamis, R., & Mushtaha, E. (2025). Bibliometric analysis of Artificial Intelligence in accounting research: Trends, patterns, and future directions. International Journal of Advanced and Applied Sciences, 12(8), 1–18. https://doi.org/10.21833/ijaas.2025.08.015
Aliah, N., & Faridani, M. R. (2025). Transforming accounting through Artificial Intelligence: A systematic literature review. Proceedings of the International Conference on Innovation and Entrepreneurship (ICIE), Universitas Prima Indonesia. https://proceeding.pancabudi.ac.id/index.php/ICIE/article/download/626/561/2162
Amstrong, D., & Patel, S. (2024). AI and blockchain integration in financial fraud detection and audit practices. Research and Innovation in Digital Accounting, 6(1), 33–51. https://doi.org/10.55544/raida.2024.6101
Azimah, N., & Ria, E. (2024). Technology acceptance model for Artificial Intelligence accounting information systems. Jurnal Akuntansi dan Keuangan, 12(2), 45–62. https://doi.org/10.24843/EJA.2024.v12.i02.p05
Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative Artificial Intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52–62. https://doi.org/10.61969/jai.1337500
Bhimani, A. (2020). Digital data and management accounting: Why management accounting research must embrace the digital revolution. Accounting and Business Research, 50(5), 422–429. https://doi.org/10.1080/00014788.2020.1776151
Chukwuemeka, N., & Ihejirika, P. (2024). Accountability ambiguity in AI-automated financial decisions: An ethical analysis. International African Review of Networks, 6(2), 55–72. https://doi.org/10.46970/IARN.2024.6202
Coman, M. D., Ionescu, C. A., Tudorache, F. G., Grigorescu, A., Coman, A. C., Nitu, M., & Bendic, C. V. (2022). Digitization of accounting: Bibliometric analysis and systematic literature review. Electronics, 11(22), 3818. https://doi.org/10.3390/electronics11223818
Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods approaches (6th ed.). SAGE Publications.
Emzir. (2012). Metodologi penelitian kualitatif: Analisis data (Ed. 3). Rajawali Pers.
Eze, B., & Okoye, A. (2024). Cybersecurity, data privacy, and competency challenges in AI-driven accounting systems. Advances in Research, 25(3), 1–18. https://doi.org/10.9734/AIR/2024/v25i3876
Ezr, B., & Okafor, A. (2024). Cybersecurity challenges in AI accounting systems. Advances in Research, 25(3), 1–18. https://doi.org/10.9734/AIR/2024/v25i3876
Habib, M. A., & Rahman, S. (2024). Artificial Intelligence in accounting and financial decision-making: A comprehensive review. Global Journal of Accounting Research and Reviews, 3(2), 89–107. https://doi.org/10.55014/gjarr.v3i2.112
Hafasy, M. I., & Setiawan, B. (2024). Kompetensi akuntan di era transformasi digital: Analisis kualitatif. Jurnal Akuntansi, Ekonomi dan Manajemen Bisnis, 12(2), 78–92. https://doi.org/10.30812/jafar.v12i2.3456
Hu, M., Li, X., & Shi, M. (2026). Artificial Intelligence and audit quality: Evidence from a large-scale experiment. Journal of Accounting Research, 64(1), 1–42. https://doi.org/10.1111/1475-679X.12567
Khan, M. A., Kaur, P., & Chaudhary, A. (2024). Artificial Intelligence in auditing: A systematic review of applications and implications. Managerial Auditing Journal, 39(3), 312–338. https://doi.org/10.1108/MAJ-04-2023-3893
Kurniawan, A., & Rahmawati, D. (2026). Pergeseran peran akuntan di era kecerdasan buatan: Tinjauan literatur. E-Jurnal ULBI Akuntansi, 8(1), 1–15. https://doi.org/10.36805/ejurnal-ulbi.v8i1.789
Mensah, K., & Agyapong, D. (2025). Artificial Intelligence as a driver of financial decision quality: Evidence from enterprise applications. International Journal of Economics, Politics, and Organizations, 7(1), 21–39. https://doi.org/10.53982/ijepo.2025.0701.02
Novak, P., & Kovarik, M. (2024). Robotic Process Automation in financial management: Empirical evidence from implementation cases. Acta Montanistica Slovaca, 29(1), 45–58. https://doi.org/10.46544/AMS.v29i1.05
Nugroho, F., Sari, D. K., Prasetyo, A., & Wibowo, H. (2024). Review of Artificial Intelligence in accounting: Trends, implementation and implications. Journal of Accounting and Finance Management, 5(5), 889–902. https://doi.org/10.38035/jafm.v5i5.1222
Okonkwo, E., & Nwosu, C. (2025). Predictive analytics in financial decision-making: Transforming accounting practices through Artificial Intelligence. Open Journal of Business and Management, 13(2), 712–731. https://doi.org/10.4236/ojbm.2025.132039
Osei-Bonsu, K., & Mensah, B. (2024). Robotic Process Automation in accounting: Benefits, challenges, and future directions. World Journal of Advanced Research and Reviews, 21(2), 1105–1118. https://doi.org/10.30574/wjarr.2024.21.2.0456
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hrobjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., ... Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Prasetya, H., & Santoso, W. (2024). Machine learning algorithms for fraud detection in financial auditing: Ethical dimensions and organizational commitment. Sinergi: Jurnal Riset Ilmiah, 14(1), 88–104. https://doi.org/10.31940/sinergi.v14i1.2891
Santoso, R., Wijaya, T., & Handoko, B. L. (2025). Artificial Intelligence and the evolution of audit practices: A systematic review of 575 Scopus documents. International Journal of Economics, Business, and Management Research, 9(2), 101–120. https://doi.org/10.51505/IJEBMR.2025.9208
Schrader, A., Müller, J., & Hoffmann, T. (2025). Automation and Artificial Intelligence in accounting: A bibliometric analysis of research trends 2001–2024. Journal of Accounting Innovation, 3(1), 1–28. https://doi.org/10.1007/s44230-025-00098-2
Sudaryono. (2018). Metodologi penelitian: Kuantitatif, kualitatif, dan mix method. Rajawali Pers.
Sugiyono. (2021). Metode penelitian kualitatif: Untuk penelitian yang bersifat eksploratif, enterpretif, interaktif dan konstruktif. Alfabeta.
Sugiyono. (2022). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.
Vasarhelyi, M. A., Kogan, A., & Tuttle, B. M. (2015). Big data in accounting: An overview. Accounting Horizons, 29(2), 381–396. https://doi.org/10.2308/acch-51071
Widiyastuti, M., Setiawan, R., & Pratama, A. (2025). The impact of Artificial Intelligence on accounting practices: Perspectives from Indonesian academics. Indonesian Accounting Review, 15(1), 45–62. https://doi.org/10.14414/tiar.v15i1.3112
Wiryana, I. N. A., & Wirama, D. G. (2025). UTAUT-3 model for Artificial Intelligence adoption among accounting employees. E-Jurnal Akuntansi Universitas Udayana, 35(1), 112–130. https://doi.org/10.24843/EJA.2025.v35.i01.p07
Zhang, L., Chen, Y., & Wang, H. (2024). Big data analytics and financial forecasting: Integrating real-time data into predictive models. Journal of Accounting and Finance, 24(3), 78–96. https://doi.org/10.33423/jaf.v24i3.7123