Adoption of Artificial Intelligence Technology in Human Resource Management in Digital Office Management
Abstract
The objective of this research is to examine the impact of integrating Artificial Intelligence (AI) on the effectiveness of Human Resource Management (HRM) within a digital office workplace. The study reveals that AI enhances the efficiency, accuracy, and fairness of numerous HR operations, especially recruitment, performance evaluation, and staff development. This research employs a qualitative descriptive approach using a systematic literature review to synthesize relevant scholarly findings on AI adoption in HRM within digital office environments. Furthermore, the implementation of digital technologies promotes enhanced communication, faster information flow, and a collaborative and inventive working environment. Despite these benefits, challenges remain, such as data privacy issues, cybersecurity threats, employees’ insufficient digital literacy, and resistance to technological innovation. Successful AI implementation in human resource management requires a holistic strategy encompassing technological readiness, enhancement of employees’ digital competencies, adherence to ethical standards, and an adaptable organizational culture. This approach allows organizations to develop flexible, sustainable, and effective office management systems that preserve a competitive edge amidst ongoing digital transformation.
References
Abdussamad, Z. (2021). Qualitative Research Methods (P. Rapanna, Ed.). CV. Syakir Media Press.
Adriansyah, M. A., Apriliana, F., Nadzifah, E. R., Febrianti, A. A. A., & Pramesti, S. A. A. (2022). Overview of work engagement with remote workers. International Journal of Social Science and Business, 7(1), 124–130. https://doi.org/10.23887/ijssb.v7i1.51383
Adula, M., Kant, S., & Birbirsa, Z. A. (2022). Systematic literature review on human resource management effect on organizational performance. Annals of Human Resource Management Research, 2(2), 131–146. https://doi.org/10.35912/ahrmr.v2i2.1418
Basu, S., Majumdar, B., Mukherjee, K., Munjal, S., & Palaksha, C. (2023). Artificial intelligence–HRM interactions and outcomes: A systematic review and causal configurational explanation. Human Resource Management Review, 33(1), 100893. https://doi.org/10.1016/j.hrmr.2022.100893
Batra, J., Kumar, D., Kautish, S., & Kumar, A. (2025). AI solutions for inclusive organizational culture and business benefits. Advances in Human Resources Management and Organizational Development Book Series, 1–34. https://doi.org/10.4018/979-8-3693-3960-2.ch001
Bodie, G. D., & Alimardani, M. (2023). Responsible artificial intelligence in human resources management. AI and Ethics, 5(3), 417–429. https://doi.org/10.1007/s43681-023-00325-1
Böhmer, N., & Schinnenburg, H. (2023). Critical exploration of AI-driven HRM to build up organizational capabilities. Employee Relations: The International Journal, 45(5), 1057–1082. https://doi.org/10.1108/ER-04-2022-0202
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. The International Journal of Human Resource Management, 33(6), 1065–1097. https://doi.org/10.1080/09585192.2022.2035161
Calderón-Monge, E., & Ribeiro-Soriano, D. (2023). The role of digitalization in business and management: A systematic literature review. Review of Managerial Science, 18, 449–491. https://doi.org/10.1007/s11846-023-00647-8
Cavanagh, J., Pariona-Cabrera, P., & Halvorsen, B. (2024). The Effects of Artificial Intelligence on Human Resource Activities and the Roles of the Human Resource Triad: Opportunities and Challenges. Frontiers in Psychology, 15, 1360401. https://doi.org/10.3389/fpsyg.2024.1360401
Chaniago, H. (2020). The Effects of Entrepreneurial Personality on Competitiveness and Corporate Image: A Study on Chocolate Entrepreneurs. International Review of Management and Marketing, 10(2), 21–29. https://doi.org/10.32479/irmm
Chaniago, H. (2022). Purchase motives of retail consumers in nanostores: Evidence from Indonesia. Quality - Access to Success, 23(186), 98–103. https://doi.org/10.47750/QAS/23.186.13
Chaniago, H. (2023). An Investigation of Entrepreneurial Leadership and Digital Transformation: Achieving Business Success in Uncertain Economic Conditions. Journal of Technology & Innovation Management, 18(2), 18–27. https://doi.org/10.4067/S0718-27242023000200018
Charlwood, A., & Guenole, N. (2022). HR adapts to the paradoxes of artificial intelligence. Human Resource Management Journal, 32(4), 729–742. https://doi.org/10.1111/1748-8583.12433
Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383. https://doi.org/10.1016/j.ijinfomgt.2021.102383
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., & Williams, M. D. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Efawati, Y. (2024). Peran Budaya Digital dan Kreativitas terhadap Kinerja Karyawan: Apakah Krusial Bagi Perusahaan?. Jurnal Akuntansi Keuangan dan Bisnis, 17(2), 139-150.
Efawati, Y. (2023). Trust as Antecedent of Innovative Behavior in the Workplace. International Journal Administration, Business & Organization, 4(3), 35-47. https://doi.org/10.61242/ijabo.23.381
Efawati, Y. (2020). The influence of working conditions, workability and leadership on employee performance. International Journal Administration, Business & Organization, 1(3), 8-15. https://doi.org/10.61242/ijabo.20.40
García-Martínez, I., Fernández-Batanero, J. M., Fernández-Cerero, J., & León, S. P. (2023). Analyzing the impact of artificial intelligence and computational sciences on student performance: Systematic review and meta-analysis. Journal of New Approaches in Educational Research, 12(1), 171–197. https://doi.org/10.7821/naer.2023.1.1240
Golightly, L., Chang, V., Xu, Q. A., Gao, X., & Liu, B. S. (2022). Adoption of cloud computing as innovation in the organization. International Journal of Engineering Business Management, 14, 18479790221093992. https://doi.org/10.1177/18479790221093992
Gowthami, S. (2025). Enhancing the efficiency of human resources with artificial intelligence in management. ComFin Research, 13(S1-i2), 233–237. https://doi.org/10.34293/commerce.v13is1-i2.8773
Hanelt, A., Bohnsack, R., Marz, D., & Antunes Marante, C. (2021). A systematic review of the literature on digital transformation: Insights and implications for strategy and organizational change. Journal of Management Studies, 58(5), 1159–1197. https://doi.org/10.1111/joms.12639
Heliana, & Wahyuni, H. (2024). Big data analysis in human resources decision making: Optimizing workforce management. JRMSI – Indonesian Journal of Management Science Research, 15(01), 58–69. https://doi.org/10.21009/JRMSI.015.1.06
Isa Anshori, M., & Safrizal, H. B. A. (2024). Artificial intelligence in Maryawan's recruitment and selection process: A systematic literature review. *Jurnal Masharif Al-Syariah: Journal of Islamic Economics and Banking, 9*(1), 298–314. https://doi.org/10.30651/jms.v9i1.21072
Jiang, Y. (2022). Application of Data Mining Technology in Enterprise Human Resource Management Informatization In Proceedings of the 2022 International Conference on Artificial Intelligence and Autonomous Robot Systems (AIARS 2022) (pp. 228–232). IEEE. https://doi.org/10.1109/AIARS57204.2022.00058
Komajwar, S. (2025). Artificial intelligence in human resources: Transforming talent management and workforce efficiency. International Journal for Multidisciplinary Research, 7(2), 72. https://doi.org/10.36948/ijfmr.2025.v07i02.395
Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital transformation: An overview of the current state of the art of research. SAGE Open, 11(3), 21582440211047576. https://doi.org/10.1177/21582440211047576
Kuzniarska, A., & Stanczyk, I. (2024). Artificial intelligence in HR. In Information (pp. 83–98). https://doi.org/10.4324/9781032678719-6
Lutfi, A., & Mohammadi, S. (2025). Digital readiness and the adoption of artificial intelligence in human resource management. Journal of Business Research, 172, 114023. https://doi.org/10.1016/j.jbusres.2025.114023
Malik, A., Budhwar, P., & Kazmi, B. A. (2023). Artificial intelligence (AI)-assisted HRM: Towards an extended strategic framework. Human Resource Management Review, 33(1), 100940. https://doi.org/10.1016/j.hrmr.2022.100940
Malik, A., Budhwar, P., Patel, C., & Srikanth, N. R. (2022). Delivering HR cost-effectiveness and individualized employee experiences in an MNE. The International Journal of Human Resource Management, 33(6), 1148–1178. https://doi.org/10.1080/09585192.2020.1859582
Maqueira Marín, J. M., De Oliveira-Dias, D., Jafari Navimipour, N., Gardas, B., & Unal, M. (2022). Cloud computing and human resource management: Systematic literature review and future research agenda. Kybernetes, 51(6), 2172–2191. https://doi.org/10.1108/K-05-2021-0420
Massoud, M., Maaliky, B., El Fawal, A., Mawllawi, A., & Yahkni, F. (2024). Transforming human resources with AI. In IGI Global (pp. 254–299). https://doi.org/10.4018/979-8-3693-1046-5.ch011
Mwita, K. M., & Kitole, F. A. (2025). Potential benefits and challenges of artificial intelligence in human resource management in public institutions. Discover Global Society, 3(1), Article 35. https://doi.org/10.1007/s44282-025-00175-8
Nagel, P. (2020). Improving competitive Indonesian human resources through education in the era of digital transformation and sustainable technology. Proceedings of the National Seminar on Applied Science and Technology, 1(1), 31–38. http://ejurnal.itats.ac.id/sntekpan/article/view/1212
Norman, E., & Pahlawati, E. (2024). The role of artificial intelligence in recruitment and selection: Improving efficiency and accuracy in HRM. *Sci-Tech Journal, 3*(1), 45–59. https://doi.org/10.56709/stj.v3i1.320
Nurain, A., Chaniago, H., & Efawati, Y. (2024). Digital Behavior and Impact on Employee Performance: Evidence from Indonesia. Journal of Technology Management & Innovation, 19(3), 15-27.
Nyathani, R. (2023). AI in performance management: Redefining performance appraisals in the digital age. Journal of Artificial Intelligence & Cloud Computing, 2(1), 134. https://doi.org/10.47363/JAICC/2023(2)134
Ore, O., & Sposato, M. (2022). Opportunities and Risks of Artificial Intelligence in Recruitment and Selection International Journal of Organizational Analysis, 30(6), 1771–1782. https://doi.org/10.1108/IJOA-07-2020-2291
Putri, Z. Q. F., & Efawati, Y. (2025). Exploring the Impact of Customer Data Security on Consumer Trust in Gojek's Digital Services. International Journal Administration, Business & Organization, 6(1), 136-145.
Qamar, Y., Agrawal, R. K., Samad, T. A., & Chiappetta Jabbour, C. J. (2021). When technology meets people: The interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339–1370. https://doi.org/10.1108/JEIM-11-2020-0436
Rahwan, I., & Larson, K. (2022). The ethics of AI in human resources. Ethics and Information Technology, 24(4), 723–735. https://doi.org/10.1007/s10676-022-09653-y
Rasyid, S. A., & Putra, R. S. (2018). Office management: Manajemen perkantoran. Bandar Publishing.
Rêgo, B. S., Jayantilal, S., Ferreira, J. J., & Carayannis, E. G. (2021). Digital transformation and strategic management: A systematic review of the literature. Journal of the Knowledge Economy, 14, 1172–1201. https://doi.org/10.1007/s13132-021-00853-3
Saranya, T. S., Babhuti, K., Jyoti, D., Kaur, H., & Kapoor, T. (2025). The evolving role of artificial intelligence (AI) in human resource management (HRM). In Advances in Human Resources Management and Organizational Development (pp. 301–310). https://doi.org/10.4018/979-8-3693-8679-8.ch015
Tabrizchi, H., & Kuchaki Rafsanjani, M. (2020). A survey on security challenges in cloud computing: Issues, threats, and solutions. The Journal of Supercomputing, 76(12), 9493–9532. https://doi.org/10.1007/s11227-020-03213-1
Triono, T. A., & Wijaya, E. F. A. (2025). Artificial intelligence in human resource management: Opportunities, ethics, and the future. Journal of Society Bridge, 3(2), 84–94. https://doi.org/10.59012/jsb.v3i2.82
Tursunbayeva, A., Bunduchi, R., Franco, M., & Pagliari, C. (2021). Ethics of digital health: A scoping review of empirical research. BMC Medical Ethics, 22(1), 13. https://doi.org/10.1186/s12910-021-00654-1
Ulrich, M. D., Way, S. A., & Wright, P. M. (2024). Building strategic human capabilities that drive performance. International Journal of Human Resource Management, 35(20), 3341–3373. https://doi.org/10.1080/09585192.2024.2408026
Votto, A. M., Valecha, R., Najafirad, P., & Rao, H. R. (2021). Artificial intelligence in tactical human resource management: A systematic literature review. International Journal of Information Management Data Insights, 1(2), 100047. https://doi.org/10.1016/j.jjimei.2021.100047
Zhang, J., & Chen, Z. (2024). Exploring human resource management digital transformation in the digital age. Journal of the Knowledge Economy, 15, 1482–1498. https://doi.org/10.1007/s13132-023-01214-y
Zhao, M., & Rabiei, K. (2023). Feasibility of implementing the human resource payroll management system based on cloud computing. Kybernetes, 52(4), 1245–1268. https://doi.org/10.1108/K-07-2021-0554
Copyright (c) 2025 Marcha Dwi Yuliana; Febri Mardianti
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish in this journal agree to the following terms:
- The authors confirm that they are the authors of the submitted article, which will be published (online) in the journal IJABO (International Journal Administration, Business & Organization) by the Asosiasi Ahli Administrasi Indonesia (A3i), Bandung, Indonesia. The author’s name will be evident in the article. The publisher makes all decisions regarding the layout and distribution of the work.
- Authors guarantee that the work is their own original creation and does not infringe any statutory or common-law copyright or any proprietary right of any third party. In case of claims by third parties, authors commit themself to defend the interests of the publisher and shall cover any potential costs.
- Authors retain copyright and grant the journal the right of first publication, with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). This license allows the redistribution and reuse of papers provided the authorship is properly credited.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., posting it to an institutional repository or publishing it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as this can lead to productive exchanges and earlier and greater citations of published work.
