AI Adoption and accounting efficiency in Indonesia and Malaysia
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Published:
Jun 30, 2026
Keywords:
Artificial intelligence adoption, Accounting efficience, Employee Competence, Data quality, Organizational readiness
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Articles
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Abstract
This study extends the artificial intelligence (AI) accounting literature by examining how AI adoption translates into measurable accounting efficiency rather than focusing solely on technology adoption intention. It also reconceptualizes organizational readiness as a moderating mechanism influencing post-adoption performance. A quantitative research design was employed using survey data collected from 500 accounting professionals in Indonesia and Malaysia. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), including moderation and multi-group analyses. The findings indicate that AI adoption significantly improves accounting efficiency, with employee competence emerging as the strongest predictor, followed by data quality. Organizational readiness significantly strengthens the positive relationship between AI adoption and accounting efficiency, demonstrating that infrastructure, leadership commitment, and innovation-oriented culture are essential for maximizing AI benefits. The structural model explains 37.2% of the variance in accounting efficiency (R² = 0.372), while multi-group analysis reveals no significant structural differences between Indonesia and Malaysia. By integrating the Technology Acceptance Model, Resource-Based View, and Contingency Theory into a unified framework, this study advances a capability-performance perspective of AI-enabled accounting transformation. The findings suggest that sustainable accounting digitalization requires not only AI investment but also workforce upskilling, robust data governance, and strong organizational readiness.
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How to Cite
Sundari, R., Satria, M. R., & Mubassiran, M. (2026). AI Adoption and accounting efficiency in Indonesia and Malaysia. Indonesia Accounting Research Journal, 13(4), 307–321. Retrieved from https://journals.iarn.or.id/index.php/Accounting/article/view/646
References
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Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2024). Does AI adoption redefine financial reporting accuracy, auditing efficiency, and information asymmetry? An integrated model of TOE-TAM-RDT and big data analytics. Computers in Human Behavior Reports, 16, Article 100572. https://doi.org/10.1016/j.chbr.2024.100572
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Damerji, H. & Saleem, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting, Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160. https://doi.org/10.2307/2095101
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Eulerich, M., Pawlowski, J., Waddoups, N. J., & Wood, D. A. (2022). A framework for using robotic process automation for audit tasks. Contemporary Accounting Research, 39(1), 691–720. https://doi.org/10.1111/1911-3846.12723
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Handoko, B. Mulyani, L. A. & R. Hapsari. (2024). Embracing AI in auditing: An examination of auditor readiness through the TRAM framework. The International Journal of Computational Methods and Experimental Measurements, 12(1), 45–56. https://doi.org/10.18280/ijcmem.120106
Hsiung, H.-H., & Wang, J. L. (2022). Research on the introduction of a robotic process automation (RPA) system in small accounting firms in Taiwan. Economies, 10(8), Article 200. https://doi.org/10.3390/economies10080200
Jackson, D., & Allen, P. J. (2024). Enablers, barriers and strategies for adopting new technology in accounting. International Journal of Accounting Information Systems, 52, Article 100666. https://doi.org/10.1016/j.accinf.2023.100666
Kokina, J., Gilleran, R., S. Blanchette, & D. Stoddard. (2021). Accountant as Digital Innovator: Roles and Competencies in the Age of Automation,. Accounting Horizons, 35(1), 153–184. https://doi.org/10.2308/HORIZONS-19-145
Norzelan, M., Mohd Suki, N. A., & Suki, N. M. (2024). Technology acceptance of artificial intelligence (AI) among heads of finance and accounting units in the shared service industry. Technological Forecasting and Social Change, 198, Article 123022. https://doi.org/10.1016/j.techfore.2023.123022
Perdana, A. B., Lee, W. E., & Kim, C. M. (2023). Prototyping and implementing robotic process automation in accounting firms: Benefits, challenges and opportunities to audit automation. International Journal of Accounting Information Systems, 50, Article 100641. https://doi.org/10.1016/j.accinf.2023.100641
Solikin, A. Wibowo, & Suhartono, H. (2023). Impact of artificial intelligence in improving the effectiveness of accounting information systems. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 14(2), 89–104. https://doi.org/10.58346/jowua.2023.i2.007
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640
Vărzaru, A. A. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14), Article 2256. https://doi.org/10.3390/electronics11142256
Vărzaru, A. A., Bocean, C. C., & Nicolescu, M. D. (2022). Assessing users' behavior on the adoption of digital technologies in management and accounting information systems. Electronics, 11(21), Article 3613. https://doi.org/10.3390/electronics11213613
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099
Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1), Article 67. https://doi.org/10.1186/1748-5908-4-67
Wong, W. P., & Yap, S. F. (2024). Factors influencing the adoption of artificial intelligence in accounting among micro, small medium enterprises (MSMEs). Quantum Journal of Social Sciences and Humanities, 5(1), 16–28. https://doi.org/10.55197/qjssh.v5i1.323
X. Chen, Liu, Y. & Wang, Z. (2022). Construction of conceptual framework of intelligent accounting under the condition of new generation information technology,. Advances in Economics, Business and Management Research, 203, 165–170. https://doi.org/10.2991/aebmr.k.220307.027
Zhang, C. Kokina, T. H. Cao, & Schnader, D. (2022). Robotic process automation (RPA) implementation case studies in accounting: A beginning to end perspective, Accounting Horizons, 36(4), 193–217. https://doi.org/10.2308/horizons-2021-084.
Afifa, M. A., Nguyen, N. T., & Nguyen, P. T. (2024). Accounting going digital: A Vietnamese experimental study on artificial intelligence in accounting. VINE Journal of Information and Knowledge Management Systems. Advance online publication. https://doi.org/10.1108/vjikms-10-2023-0266
AlNasrallah, W., & Saleem, F. (2022). Determinants of the digitalization of accounting in an emerging market: The roles of organizational support and job relevance. Sustainability, 14(11), Article 6483. https://doi.org/10.3390/su14116483
Al-Okaily, M. (2024). Artificial intelligence and its applications in the context of accounting and disclosure. Journal of Financial Reporting and Accounting. Advance online publication. https://doi.org/10.1108/jfra-04-2024-0209
Anh, T. Nguyen, N. T., & Pham, P. T. (2024). The effect of technology readiness on adopting artificial intelligence in accounting and auditing in Vietnam. Journal of Risk and Financial Management, 17(1), Article 27. https://doi.org/10.3390/jrfm17010027
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108
Bin-Nashwan, S. A., Sadallah, M., & Bouteraa, M. (2024). Does AI adoption redefine financial reporting accuracy, auditing efficiency, and information asymmetry? An integrated model of TOE-TAM-RDT and big data analytics. Computers in Human Behavior Reports, 16, Article 100572. https://doi.org/10.1016/j.chbr.2024.100572
Bin-Nashwan, S. A., & Li, H. (2025). What shapes AI adoption in financial service-oriented contexts? The game-changing role of innovation climate. Information Discovery and Delivery. Advance online publication. https://doi.org/10.1108/idd-12-2024-0199
Chowdhury, M., A., Islam, M. A. & S. K. Saha. (2025). Adoption of Artificial Intelligence Accounting Systems in Bangladeshi Accounting Firms: TOE Framework and Country-Specific Variables, International Journal of Business and Management, 20(4), 262–278. https://doi.org/10.5539/ijbm.v20n4p262
Cooper, L. A. Holderness Jr, D. A. T. L. Sorensen, & D. A. Wood. (2019). Robotic Process Automation in Public Accounting, Accounting Horizons, 33(4), 15–35. https://doi.org/10.2308/ACCH-52466
Damerji, H. & Saleem, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting, Accounting Education, 30(2), 107–130. https://doi.org/10.1080/09639284.2021.1872035
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48(2), 147–160. https://doi.org/10.2307/2095101
Donaldson, L. (2001). The contingency theory of organizations. Sage Publications.
Economic Planning Unit & Malaysia Digital Economy Corporation. (2021). Malaysia digital economy blueprint. Prime Minister's Department, Malaysia. https://ekonomi.gov.my/sites/default/files/2021-02/malaysia-digital-economy-blueprint.pdf (Accessed: March 02, 2026)
Eulerich, M., Pawlowski, J., Waddoups, N. J., & Wood, D. A. (2022). A framework for using robotic process automation for audit tasks. Contemporary Accounting Research, 39(1), 691–720. https://doi.org/10.1111/1911-3846.12723
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Handoko, B. Mulyani, L. A. & R. Hapsari. (2024). Embracing AI in auditing: An examination of auditor readiness through the TRAM framework. The International Journal of Computational Methods and Experimental Measurements, 12(1), 45–56. https://doi.org/10.18280/ijcmem.120106
Hsiung, H.-H., & Wang, J. L. (2022). Research on the introduction of a robotic process automation (RPA) system in small accounting firms in Taiwan. Economies, 10(8), Article 200. https://doi.org/10.3390/economies10080200
Jackson, D., & Allen, P. J. (2024). Enablers, barriers and strategies for adopting new technology in accounting. International Journal of Accounting Information Systems, 52, Article 100666. https://doi.org/10.1016/j.accinf.2023.100666
Kokina, J., Gilleran, R., S. Blanchette, & D. Stoddard. (2021). Accountant as Digital Innovator: Roles and Competencies in the Age of Automation,. Accounting Horizons, 35(1), 153–184. https://doi.org/10.2308/HORIZONS-19-145
Norzelan, M., Mohd Suki, N. A., & Suki, N. M. (2024). Technology acceptance of artificial intelligence (AI) among heads of finance and accounting units in the shared service industry. Technological Forecasting and Social Change, 198, Article 123022. https://doi.org/10.1016/j.techfore.2023.123022
Perdana, A. B., Lee, W. E., & Kim, C. M. (2023). Prototyping and implementing robotic process automation in accounting firms: Benefits, challenges and opportunities to audit automation. International Journal of Accounting Information Systems, 50, Article 100641. https://doi.org/10.1016/j.accinf.2023.100641
Solikin, A. Wibowo, & Suhartono, H. (2023). Impact of artificial intelligence in improving the effectiveness of accounting information systems. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 14(2), 89–104. https://doi.org/10.58346/jowua.2023.i2.007
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. https://doi.org/10.1002/smj.640
Vărzaru, A. A. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14), Article 2256. https://doi.org/10.3390/electronics11142256
Vărzaru, A. A., Bocean, C. C., & Nicolescu, M. D. (2022). Assessing users' behavior on the adoption of digital technologies in management and accounting information systems. Electronics, 11(21), Article 3613. https://doi.org/10.3390/electronics11213613
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems, 12(4), 5–33. https://doi.org/10.1080/07421222.1996.11518099
Weiner, B. J. (2009). A theory of organizational readiness for change. Implementation Science, 4(1), Article 67. https://doi.org/10.1186/1748-5908-4-67
Wong, W. P., & Yap, S. F. (2024). Factors influencing the adoption of artificial intelligence in accounting among micro, small medium enterprises (MSMEs). Quantum Journal of Social Sciences and Humanities, 5(1), 16–28. https://doi.org/10.55197/qjssh.v5i1.323
X. Chen, Liu, Y. & Wang, Z. (2022). Construction of conceptual framework of intelligent accounting under the condition of new generation information technology,. Advances in Economics, Business and Management Research, 203, 165–170. https://doi.org/10.2991/aebmr.k.220307.027
Zhang, C. Kokina, T. H. Cao, & Schnader, D. (2022). Robotic process automation (RPA) implementation case studies in accounting: A beginning to end perspective, Accounting Horizons, 36(4), 193–217. https://doi.org/10.2308/horizons-2021-084.
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