Adopsi Artificial Intelligence (AI) Dalam Audit Internal Sektor Publik di Indonesia: Sebuah Tinjauan Sistematis

M. Zainul Khaq, Lidya Primta Surbakti

Abstract


Artificial Intelligence (AI) in public sector internal audit offers substantial promise for enhancing efficiency and accountability, yet its adoption remains limited due to organizational unpreparedness and institutional barriers. This study explores how organizational readiness and institutional challenges influence AI implementation in audit functions, using a Systematic Literature Review of 583 articles. The findings reveal that current literature is heavily centered on conceptual discussions of readiness and barriers, with minimal empirical evidence of real-world implementation. As its core contribution, this research proposes a relational conceptual framework in which readiness and barriers act as primary determinants of AI adoption, embedded within the broader context of digital transformation in the public sector. A phased implementation strategy is also recommended, beginning with readiness assessment, followed by pilot projects, internal reforms, and culminating in systemic integration and continuous evaluation. The study contributes not only to theoretical understanding of digital adoption but also offers a strategic foundation for regulators and oversight bodies to build a sustainable, data-driven public audit ecosystem.

Keywords


artificial intelligence; internal audit; institutional barriers; organizational readiness; public sector

Full Text:

PDF

References


Abdullah, M. I., Zahra, F., & Hadi, S. (2025). Investigating the function of artificial intelligence for the audit of organizational performance. Journal of AI for Government Performance, 10(1), 34–52.

Aldemir, C., & Uçma Uysal, T. (2024). AI competencies for internal auditors in the public sector. Journal of AI Competency and Public Accountability, 11(1), 61–78.

Alneyadi, M. R. M. A. H., & Normalini, Md. K. (2025). Intelligent protection: A study of the key drivers and barriers of AI in the public sector. International Journal of Digital Government Transformation, 10(1), 34–49.

Alsharari, N. M., & Ikem, F. (2023). Digital accounting systems and information technology in emerging economies. Journal of Accounting and Emerging Technologies, 12(1), 45–59.

Althin, Y., Ilmi, B., & Jamaris, E. (2023). Penggunaan Teknologi Kecerdasan Buatan dalam Proses Audit Keuangan: Tantangan dan Peluang. Jurnal Akuntasi Dan Keuangan Kontemporer (JAKK), 6(1).

Alvionita, A., & Ie, M. (2021). Pengaruh Konteks Teknologi, Konteks Organisasi, dan Konteks Lingkungan terhadap Adopsi Media Sosial Bagi UMKM. Jurnal Muara Ilmu Ekonomi Dan Bisnis, 5(1), 214. https://doi.org/10.24912/jmieb.v5i1.11185

Cen, S. H., & Alur, R. (2024). From transparency to accountability and back: Navigating AI governance in audits. International Journal of Public Sector Innovation, 17(2), 92–109.

Chithiraikannu, M. D., Arumugam, G., & Moorthy, P. P. (2025). The impact of artificial intelligence (AI) training on public sector capacity. Government Information Quarterly, 42(1), 67–81.

Eltrudis, D., Monfardini, P., & Pattaro, A. F. (2024). Public auditors’ perception of digital platforms for local government auditing. International Journal of Public Audit Technology, 12(1), 51–68.

Engida, Z. M., Alemu, A. E., & Mulugeta, M. A. (2022). The Effect of Change Leadership on Employees’ Readiness to Change: The Mediating Role of Rrganizational Culture. Future Business Journal, 8(1). https://doi.org/10.1186/s43093-022-00148-2

Hanfy, F., Alakkas, A. A., & Alhumoudi, H. (2024). Analyzing the role of digitalization and its impact on audit functions in the public sector. Journal of Digital Audit and Oversight, 16(1), 72–88.

Hao, J., Shi, H., Shi, V., & Yang, C. (2020). Adoption of automatic warehousing systems in logistics firms: A technology-organization-environment framework. Sustainability (Switzerland), 12(12). https://doi.org/10.3390/su12125185

Herreros-Martínez, A., Magdalena-Benedicto, R., & Robles, J. (2025). Applied machine learning to anomaly detection in financial governance. Journal of Financial Analytics and Public Oversight, 13(1), 91–108.

Hu, K. H., Chen, F. H., Hsu, M. F., & Tzeng, G. H. (2021). Identifying key factors for adopting artificial intelligence-enabled auditing techniques by joint utilization of fuzzy-rough set theory and MRDM technique. Technological and Economic Development of Economy, 27(2), 459–492. https://doi.org/10.3846/tede.2020.13181

Hu, K.-H., Chen, F.-H., Hsu, M.-F., & Tzeng, G.-H. (2023). Governance of artificial intelligence applications in public auditing. Journal of Government Auditing and AI Ethics, 14(1), 33–47.

Insirat, M. N., Syahfir, H. A., Usman, A., & Mediaty, M. (2025). Analisis Dampak Implementasi AI Dalam Proses Pengambilan Keputusan Manajerial Terhadap Etika Bisnis dan Keberlanjutan Organisasi: A Systematic Literature Review. Owner, 9(1), 011–025. https://doi.org/10.33395/owner.v9i1.2525

Iuga, I. C., & Socol, A. (2024). Government artificial intelligence readiness and institutional change. Journal of Digital Government Transformation, 11(1), 58–74.

Jejeniwa, T. O., Mhlongo, N. Z., & Jejeniwa, T. O. (2024). A Comprehensive Review of The Impact of Artificial Intelligence on Modern Accounting Practices and Financial Reporting. Computer Science & IT Research Journal, 5(4), 1031–1047. https://doi.org/10.51594/csitrj.v5i4.1086

Judijanto, L., Amin, A., & Nurhakim, L. (2024). Implementasi Teknologi Artificial Intelligence dan Machine Learning dalam Praktik Akuntansi dan Audit: Sebuah Revolusi atau Evolusi (Vol. 1, Issue 6). Elektronik.

Kahyaoglu, S. B., & Aksoy, T. (2021). Artificial intelligence in internal audit and its effect on auditor’s performance. Journal of Emerging Audit Technologies, 12(2), 77–94.

Krysovatyy, A., Desyatnyuk, O., & Ptashchenko, O. (2024). Digital innovations and their ramifications for public sector oversight. International Journal of Public Digital Transformation, 15(2), 122–138.

Lutfi, A., & Alqudah, H. (2023). The Influence of Technological Factors on the Computer-Assisted Audit Tools and Techniques Usage during COVID-19. Sustainability (Switzerland), 15(9). https://doi.org/10.3390/su15097704

Mahyoro, A. K., & Kasoga, P. S. (2021). Attributes of the internal audit function and performance of local government authorities. Journal of Local Governance and Accountability, 9(2), 65–81.

Mawlidy, E. R., Primasatya, R. D., & Lorensa, L. (2024). Kemampuan Artificial Intelligence terhadap Pendeteksian Fraud: Studi Literatur. Jurnal Studi Akuntansi Dan Keuangan, 7(1), 89–104.

Naveen, K., Selvan, C. P., & Bahumik, A. (2022). Performance evaluation through audit of 519 organizations using digital evidence. Journal of Internal Audit Quality, 10(2), 121–138.

Neuman, W. L. (2014). Social research methods: Qualitative and quantitative approaches (7th ed.). Pearson Education Limited.

Nur Muslihatun, F. A., Hantono, B. S., & Fauzi, R. M. (2021). Using artificial intelligence technology for decision making in internal auditing. Journal of Emerging Technologies in Internal Audit, 14(2), 93–107.

Nurlaila, Z., Zuriatin, Z., & Nurhasanah, N. (2024). Transformasi digital pelayanan publik: Tantangan dan prospek dalam implementasi e-government di Kabupaten Bima. PSGJ: Jurnal Penelitian Sosial Keagamaan, 5(2), 21–37.

Olamilekan, F., & Salam, A. (2022). Relationship Between Change Readiness and organizational Performance of Selected organization in Nigeria. African Economic and Management Review, 2(1), 31–39. https://doi.org/10.53790/aemr.v2i1.30

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., Hróbjartsson, 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. The BMJ, 372. https://doi.org/10.1136/bmj.n71

Peng, G., Zhao, B., & He, Y. (2024). Integrated classification method with hybrid supervised machine learning algorithms. Journal of Predictive Analytics in Governance, 12(1), 67–83.

Qu, C., & Kim, E. (2025). Investigating AI Adoption, Knowledge Absorptive Capacity, and Organizational Readiness. Journal of Public Sector Innovation, 18(1), 45–61.

Sembiring, F. N. B. R., & Widuri, R. (2023). The effect of auditor experience, big data, and audit complexity on audit effectiveness. Asian Journal of Government Auditing, 11(2), 88–102.

Setyaningrum, D., Azhar, Z., Kuntadi, C., & Dharmayanti, I. A. S. (2025). Revitalizing accountability: Exploring the impact of government audit functions. Journal of Public Sector Oversight, 13(1), 45–62.

Shabani, N., Munir, A., & Mohanty, S. P. (2022). A study of big data analytics in internal auditing. Journal of Digital Audit Analytics, 11(2), 88–105.

Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039

Susniwati, Ardiyansah, & Sukorina, D. (2025). Good governance di era digital: Studi kasus implementasi e-government di Indonesia. Pandita: Jurnal Ilmu Agama Dan Sosial Budaya, 5(2), 21–37.

Syahfir, H. A., Panggeso, A. G., & Syamsuddin, A. (2025). Melampaui Batas Penglihatan Manusia: Peran AI dalam Mendeteksi Fraud pada Proses Audit. Jurnal Revenue, 5(2), 1531–1545. https://doi.org/10.46306/rev.v5i2

Syifa Hendri, A., & Sudarmilah, E. (2024). Enhancing Information Technology Adoption Potential in MSMEs: a Conceptual Model Based on TOE Framework. JUITA: Jurnal Informatika, 12(1), 91–100.

Toufan, A., & Tirtoprojo, S. (2021). An Analysis of The Influence of Transformational Leadership and Organizational Commitments on Change Readiness. Modern Management Review, 26(2), 7–15. https://doi.org/10.7862/rz.2021.mmr.07

Venson, E., Figueiredo, R. M. da C., & Canedo, E. D. (2024). Leveraging a startup-based approach for digital auditing in public institutions. Journal of Digital Governance Innovation, 10(1), 33–49.

Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1). https://doi.org/10.1186/1748-5908-4-67

Wu, Z., Mao, Y., & Fang, C. (2023). Data-driven analytics in government auditing: Enhancing detection of inefficiencies and fiscal risk. International Journal of Public Sector Data Science, 15(1), 101–119.

Zhang, L. (2023). Intelligent internal audit platform architecture. Journal of Digital Audit Innovation, 17(1), 44–59




DOI: https://doi.org/10.35308/akbis.v9i2.12692

Refbacks

  • There are currently no refbacks.