Ai based management information system to develop superior human resources in the society 5.0
##plugins.themes.bootstrap3.article.main##
Abstract
The rapid advancement of digital technology in the era of Society 5.0 has encouraged organizations to transform their human resource management practices through the integration of Artificial Intelligence (AI) into Management Information Systems (MIS). This study examines the influence of AI-based Management Information Systems on the development of high-quality human resources, with AI utilization positioned as a mediating variable. A quantitative explanatory approach was employed, using a survey method involving employees and human resource practitioners in organizations that have implemented AI-supported systems. Data were collected through a structured questionnaire measured on a five-point Likert scale to analyze the relationships among the proposed variables. The findings indicate that AI-based Management Information Systems have a positive and significant effect on the development of competitive and adaptive human resources. Furthermore, the effective utilization of AI strengthens the relationship between talent management practices—such as recruitment, training and development, performance management, and employee engagement—and improvements in employee competence, creativity, adaptability, and organizational commitment. These results highlight the strategic importance of integrating AI into human resource systems to enhance organizational competitiveness and sustainability in the Society 5.0 era. This study contributes to the development of a technology-driven human resource management framework relevant to the Indonesian organizational context.).
##plugins.themes.bootstrap3.article.details##
How to Cite
Putri, F. B. P., Budiadi, N. A., & Atmoko, W. B. (2026). Ai based management information system to develop superior human resources in the society 5.0 . Indonesia Auditing Research Journal, 15(1), 30–38. https://doi.org/10.35335/arj.v15i1.617
References
Ali, O., & Kallach, L. (2024). Artificial Intelligence Enabled Human Resources Recruitment Functionalities: A Scoping Review. Procedia Computer Science, 232, 3268–3277. https://doi.org/10.1016/j.procs.2024.02.142
Alshamrani, M., Alharthi, ✉ Sager, Helmi, M., & Alwadei, T. (2023). Journal of Business and Management Studies Determinants of Employee Retention in Pharmaceutical Companies: Case of Saudi Arabia. Determinants of Employee Retention in Pharmaceutical Company: Case of Saudi Arabia, 2709–0876, 8–22. https://doi.org/10.32996/jbms
Atay, S., Terzi Müftüoğlu, C., Gülmez, N., & Şahin, M. (2025). Society 5.0 and human-centered technology: Redefining talent management in the digital age. Sustainable Futures, 9(October 2024). https://doi.org/10.1016/j.sftr.2025.100733
Bresciani, S., Ferraris, A., & Del Giudice, M. (2021). The management of organizational ambidexterity through alliances in a new context of analysis: Internet of Things (IoT) smart city projects. Technological Forecasting and Social Change, 136(February), 331–338. https://doi.org/10.1016/j.techfore.2017.03.002
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022). Artificial intelligence–challenges and opportunities for international HRM: a review and research agenda. International Journal of Human Resource Management, 33(6), 1065–1097. https://doi.org/10.1080/09585192.2022.2035161
Chowdhury, S. R., Guha, S., & Sanju, N. L. (2024). Artificial Intelligence Enabled Human Resource Management: A Review and Future Research Avenues. Archives of Business Research, 12(6), 94–111. https://doi.org/10.14738/abr.126.17050
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71(March). https://doi.org/10.1016/j.ijinfomgt.2023.102642
Etikan, I. (2021). Sampling and Sampling Methods. Biometrics & Biostatistics International Journal, 5(6), 215–217. https://doi.org/10.15406/bbij.2017.05.00149
Feng, Z., & Ahn, J. (2024). the Impact of Artificial Intelligence on Human Resource Management Processes. Journal of Theoretical and Applied Information Technology, 102(23), 8513–8529.
Guo, X., Li, Y., & Wang, Z. (2025). AI-enabled systems and employee performance: Integrating technological infrastructure with human resource outcomes. Computers in Human Behavior,.
Guo, S., Shi, L., & Zhai, X. (2025). Developing and validating an instrument for teachers’ acceptance of artificial intelligence in education. Education and Information Technologies, 30(10), 13439–13461. https://doi.org/10.1007/s10639-025-13338-6
Hair Jr et al. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature. In Structural Equation Modeling: A Multidisciplinary Journal (Vol. 30, Issue July).
Huang, M. H., & Rust, R. T. (2024a). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
Huang, M. H., & Rust, R. T. (2024b). The Caring Machine: Feeling AI for Customer Care. Journal of Marketing, 88(5), 1–23. https://doi.org/10.1177/00222429231224748
Kassa, B. Y., & Worku, E. K. (2025). The impact of artificial intelligence on organizational performance: The mediating role of employee productivity. Journal of Open Innovation: Technology, Market, and Complexity, 11(1), 100474. https://doi.org/10.1016/j.joitmc.2025.100474
Koo, M., & Yang, S. (2025). Likert-Type Scale. 1–11.
Kraus, S., Durst, S., Ferreira, J. J., Veiga, P., Kailer, N., & Weinmann, A. (2022). Digital transformation in business and management research: An overview of the current status quo. International Journal of Information Management, 63(August 2020). https://doi.org/10.1016/j.ijinfomgt.2021.102466
Link Feng, L., & Ahn, J. (2024). Mediating effects of AI utilization on HR performance: Evidence from enterprise systems.o Title. Human Resource Management Review, 1(34), 100876.
M. Damnjanović, A., D. Rašković, M., & N. Skoropad, V. (2025). Artificial Intelligence and Data Analytics in Human Resource Management: Digital Transformation and Competitive Advantage of Enterprises. SCIENCE International Journal, 4(2), 33–38. https://doi.org/10.35120/sciencej0402033d
Marler, J. H., & Boudreau, J. W. (2021). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
Minbaeva, D. (2021). Disrupted HR? Human Resource Management Review, 31(4). https://doi.org/10.1016/j.hrmr.2020.100820
Muhammad Arfah. (2025). Artificial Intelligence in Human Resource Management: A Comprehensive Literature Review. Income Journal Of Economics Development, 5(1), 7–15. https://doi.org/10.54065/ijed.5.1.2025.336
Naoum, R. F., Szakadáti, T., & Balogh, G. (2026). Artificial Intelligence (AI) in human resource management (HRM): a systematic review of its dual impact on diversity, equity, and inclusion (DEI). Management Review Quarterly. https://doi.org/10.1007/s11301-025-00580-y
Narvaez Rojas, C., Alomia Peñafiel, G. A., Loaiza Buitrago, D. F., & Tavera Romero, C. A. (2021). Society 5.0: A Japanese concept for a superintelligent society. Sustainability (Switzerland), 13(12). https://doi.org/10.3390/su13126567
Nitzl, C., Roldan, J. L., & Cepeda, G. (2022). Mediation analysis in partial least squares path modelling, Helping researchers discuss more sophisticated models. Industrial Management and Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
Olan, F., Ogiemwonyi Arakpogun, E., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145(March 2020), 605–615. https://doi.org/10.1016/j.jbusres.2022.03.008
Opatha, H. H. D. P. J. (2020). HR Analytics: A Literature Review and New Conceptual Model. International Journal of Scientific and Research Publications (IJSRP), 10(06), 130–141. https://doi.org/10.29322/ijsrp.10.06.2020.p10217
Selvamohana K. (2025). From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement. Journal of Information Systems Engineering and Management, 10(21s), 578–585. https://doi.org/10.52783/jisem.v10i21s.3395
Tambe, P., Cappelli, P., & Yakubovich, V. (2021). Page Proof Instructions and Queries Book Review. Journal of Thermoplastic Composite and Materials, 1(2003), 1–3.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2022). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122(November 2019), 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Xu, L., Cherian, J., Alturise, F., Alkhalaf, S., Mikhaylov, A., & Comite, U. (2025). Artificial Intelligence Attitude and Innovative Performance in Emerging Economy: The Mediating Roles of AI Supportive Autonomy, AI Big Data Analytics. Journal of Global Information Management, 33(1), 1–35. https://doi.org/10.4018/JGIM.384084
Alshamrani, M., Alharthi, ✉ Sager, Helmi, M., & Alwadei, T. (2023). Journal of Business and Management Studies Determinants of Employee Retention in Pharmaceutical Companies: Case of Saudi Arabia. Determinants of Employee Retention in Pharmaceutical Company: Case of Saudi Arabia, 2709–0876, 8–22. https://doi.org/10.32996/jbms
Atay, S., Terzi Müftüoğlu, C., Gülmez, N., & Şahin, M. (2025). Society 5.0 and human-centered technology: Redefining talent management in the digital age. Sustainable Futures, 9(October 2024). https://doi.org/10.1016/j.sftr.2025.100733
Bresciani, S., Ferraris, A., & Del Giudice, M. (2021). The management of organizational ambidexterity through alliances in a new context of analysis: Internet of Things (IoT) smart city projects. Technological Forecasting and Social Change, 136(February), 331–338. https://doi.org/10.1016/j.techfore.2017.03.002
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022). Artificial intelligence–challenges and opportunities for international HRM: a review and research agenda. International Journal of Human Resource Management, 33(6), 1065–1097. https://doi.org/10.1080/09585192.2022.2035161
Chowdhury, S. R., Guha, S., & Sanju, N. L. (2024). Artificial Intelligence Enabled Human Resource Management: A Review and Future Research Avenues. Archives of Business Research, 12(6), 94–111. https://doi.org/10.14738/abr.126.17050
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71(March). https://doi.org/10.1016/j.ijinfomgt.2023.102642
Etikan, I. (2021). Sampling and Sampling Methods. Biometrics & Biostatistics International Journal, 5(6), 215–217. https://doi.org/10.15406/bbij.2017.05.00149
Feng, Z., & Ahn, J. (2024). the Impact of Artificial Intelligence on Human Resource Management Processes. Journal of Theoretical and Applied Information Technology, 102(23), 8513–8529.
Guo, X., Li, Y., & Wang, Z. (2025). AI-enabled systems and employee performance: Integrating technological infrastructure with human resource outcomes. Computers in Human Behavior,.
Guo, S., Shi, L., & Zhai, X. (2025). Developing and validating an instrument for teachers’ acceptance of artificial intelligence in education. Education and Information Technologies, 30(10), 13439–13461. https://doi.org/10.1007/s10639-025-13338-6
Hair Jr et al. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (p. 197). Springer Nature. In Structural Equation Modeling: A Multidisciplinary Journal (Vol. 30, Issue July).
Huang, M. H., & Rust, R. T. (2024a). Artificial Intelligence in Service. Journal of Service Research, 21(2), 155–172. https://doi.org/10.1177/1094670517752459
Huang, M. H., & Rust, R. T. (2024b). The Caring Machine: Feeling AI for Customer Care. Journal of Marketing, 88(5), 1–23. https://doi.org/10.1177/00222429231224748
Kassa, B. Y., & Worku, E. K. (2025). The impact of artificial intelligence on organizational performance: The mediating role of employee productivity. Journal of Open Innovation: Technology, Market, and Complexity, 11(1), 100474. https://doi.org/10.1016/j.joitmc.2025.100474
Koo, M., & Yang, S. (2025). Likert-Type Scale. 1–11.
Kraus, S., Durst, S., Ferreira, J. J., Veiga, P., Kailer, N., & Weinmann, A. (2022). Digital transformation in business and management research: An overview of the current status quo. International Journal of Information Management, 63(August 2020). https://doi.org/10.1016/j.ijinfomgt.2021.102466
Link Feng, L., & Ahn, J. (2024). Mediating effects of AI utilization on HR performance: Evidence from enterprise systems.o Title. Human Resource Management Review, 1(34), 100876.
M. Damnjanović, A., D. Rašković, M., & N. Skoropad, V. (2025). Artificial Intelligence and Data Analytics in Human Resource Management: Digital Transformation and Competitive Advantage of Enterprises. SCIENCE International Journal, 4(2), 33–38. https://doi.org/10.35120/sciencej0402033d
Marler, J. H., & Boudreau, J. W. (2021). An evidence-based review of HR Analytics. International Journal of Human Resource Management, 28(1), 3–26. https://doi.org/10.1080/09585192.2016.1244699
Minbaeva, D. (2021). Disrupted HR? Human Resource Management Review, 31(4). https://doi.org/10.1016/j.hrmr.2020.100820
Muhammad Arfah. (2025). Artificial Intelligence in Human Resource Management: A Comprehensive Literature Review. Income Journal Of Economics Development, 5(1), 7–15. https://doi.org/10.54065/ijed.5.1.2025.336
Naoum, R. F., Szakadáti, T., & Balogh, G. (2026). Artificial Intelligence (AI) in human resource management (HRM): a systematic review of its dual impact on diversity, equity, and inclusion (DEI). Management Review Quarterly. https://doi.org/10.1007/s11301-025-00580-y
Narvaez Rojas, C., Alomia Peñafiel, G. A., Loaiza Buitrago, D. F., & Tavera Romero, C. A. (2021). Society 5.0: A Japanese concept for a superintelligent society. Sustainability (Switzerland), 13(12). https://doi.org/10.3390/su13126567
Nitzl, C., Roldan, J. L., & Cepeda, G. (2022). Mediation analysis in partial least squares path modelling, Helping researchers discuss more sophisticated models. Industrial Management and Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
Olan, F., Ogiemwonyi Arakpogun, E., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145(March 2020), 605–615. https://doi.org/10.1016/j.jbusres.2022.03.008
Opatha, H. H. D. P. J. (2020). HR Analytics: A Literature Review and New Conceptual Model. International Journal of Scientific and Research Publications (IJSRP), 10(06), 130–141. https://doi.org/10.29322/ijsrp.10.06.2020.p10217
Selvamohana K. (2025). From HR Analytics to AI-Driven HRM: Enhancing Workforce Productivity and Engagement. Journal of Information Systems Engineering and Management, 10(21s), 578–585. https://doi.org/10.52783/jisem.v10i21s.3395
Tambe, P., Cappelli, P., & Yakubovich, V. (2021). Page Proof Instructions and Queries Book Review. Journal of Thermoplastic Composite and Materials, 1(2003), 1–3.
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2022). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328–376. https://doi.org/10.17705/1jais.00428
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122(November 2019), 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Xu, L., Cherian, J., Alturise, F., Alkhalaf, S., Mikhaylov, A., & Comite, U. (2025). Artificial Intelligence Attitude and Innovative Performance in Emerging Economy: The Mediating Roles of AI Supportive Autonomy, AI Big Data Analytics. Journal of Global Information Management, 33(1), 1–35. https://doi.org/10.4018/JGIM.384084
Copyright and Licensing
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.