The Influence of Artificial Intelligence on Organizational Performance: Mediation of Employee Productivity in the Greater Jakarta Area
DOI:
https://doi.org/10.38035/dijemss.v7i3.6114Keywords:
Artificial Intelligence, Employee Productivity, Organizational Performance, Greater Jakarta AreaAbstract
This study aims to examine the influence of artificial intelligence (AI) on organizational performance, considering employee productivity in the Greater Jakarta area, Indonesia, as a mediating variable. This study is a quantitative study with purposive sampling as the sampling method. The 200 respondents were men and women, employees in the Greater Jakarta area, aged between 18 and 55 years old, who were accustomed to using AI to support their work. Primary data was obtained through a questionnaire distributed online via Google Form. This study used closed-ended questions with a Likert scale as a measurement method, namely a scale of 1-5. SmartPLS version 4 was used as a data analysis tool with the Partial Least Squares technique. The results showed that there was a significant effect between the artificial intelligence variable and organizational performance through employee productivity.References
Abdelwahed, N. A. A., & Doghan, M. A. A. (2023). Developing Employee Productivity and Performance through Work Engagement and Organizational Factors in an Educational Society. Societies, 13(3), 65. https://doi.org/10.3390/soc13030065
Abdul Wahab, M. D., & Radmehr, M. (2024). The impact of AI assimilation on firm performance in small and medium-sized enterprises: A moderated multi-mediation model. Heliyon, 10(8), e29580. https://doi.org/10.1016/j.heliyon.2024.e29580
Ahdiat, A. (2024, September 24). Produktivitas Tenaga Kerja RI Urutan ke-5 di Asia Tenggara. - Katadata https://databoks.katadata.co.id/infografik/2024/09/24/produktivitas-tenaga-kerja-ri-urutan-ke-5-di-asia-tenggara
Al Naqbi, H., Bahroun, Z., & Ahmed, V. (2024). Enhancing Work Productivity through Generative Artificial Intelligence: A Comprehensive Literature Review. Sustainability, 16(3), 1166. https://doi.org/10.3390/su16031166
Ala’a, A.-M. (2023). Adoption of Artificial Intelligence and Robotics in Organisations: A Systematic Literature Review. International Journal of Business and Technology Management. https://doi.org/10.55057/ijbtm.2023.5.3.28
Anis, Y., & Rifa, A. S. (2023). Perancangan Sistem Informasi E-Booking Jasa Steam Mobil Dan Motor Berbasis Web Dengan Metode Waterfall. Bulletin Of Information Technology (BIT), 4(1).
Bhima, B., Rahmania Az Zahra, A., & Nurtino, T. (2023). Enhancing Organizational Efficiency through the Integration of Artificial Intelligence in Management Information Systems. APTISI Transactions on Management (ATM), 7(3), 282–289. https://doi.org/10.33050/atm.v7i3.2146
Drago, H. F., De Moura, G. L., Da Silva, L. S. C. V., Da Veiga, C. P., Kaczam, F., Rita, L. P. S., & Da Silva, W. V. (2022). Reviewing the relationship between organizational performance, dynamic capabilities and strategic behavior. SN Business & Economics, 3(1), 5. https://doi.org/10.1007/s43546-022-00392-2
Gede, D. U., & Huluka, A. T. (2024). Effects of employee engagement on organizational performance: Case of public universities in Ethiopia. Future Business Journal, 10(1), 32. https://doi.org/10.1186/s43093-024-00315-7
Gil De Zúñiga, H., Goyanes, M., & Durotoye, T. (2024). A Scholarly Definition of Artificial Intelligence (AI): Advancing AI as a Conceptual Framework in Communication Research. Political Communication, 41(2), 317–334. https://doi.org/10.1080/10584609.2023.2290497
Gutterman, A. (2023). Organizational Performance and Effectiveness. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4532570
Hanaysha, J. (2016). Improving employee productivity through work engagement: Evidence from higher education sector. Management Science Letters, 61–70. https://doi.org/10.5267/j.msl.2015.11.006
Hidayat, R., Kusumasari, I. R., Sophia, Z. A., & Puspita, D. R. (2024). Peran Teknologi AI dalam Mengoptimalkan Pengambilan Keputusan dalam Pengembangan Bisnis. Sosial Simbiosis : Jurnal Integrasi Ilmu Sosial Dan Politik, 1(4), 167–178. https://doi.org/10.62383/sosial.v1i4.905
Hu, X., Gao, H., Agafari, T., Zhang, M. Q., & Cong, R. (2025). How and when artificial intelligence adoption promotes employee knowledge sharing? The role of paradoxical leadership and technophilia. Frontiers in Psychology, 16, 1573587. https://doi.org/10.3389/fpsyg.2025.1573587
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
Microsoft & LinkedIn. (2024). 2024 Work Trend Index Annual Report: AI at work is here. Now comes the hard part. https://www.microsoft.com/en-us/worklab/work-trend-index/ai-at-work-is-here-now-comes-the-hard-part
Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434
Mikalef, P., Islam, N., Parida, V., Singh, H., & Altwaijry, N. (2023). Artificial intelligence (AI) competencies for organizational performance: A B2B marketing capabilities perspective. Journal of Business Research, 164, 113998. https://doi.org/10.1016/j.jbusres.2023.113998
Mikalef, P., Lemmer, K., Cindy Schaefer, Ylinen, M., Fjørtoft, S. O., Torvatn, H. Y., Gupta, M., & Niehaves, B. (2023). Examining how AI capabilities can foster organizational performance in public organizations. Government Information Quarterly, 40(2), 101797. https://doi.org/10.1016/j.giq.2022.101797
Moumin, I. (2024). Organizational Performance: A Comprehensive Literature Review Of Modern Models And Approache. International Journal of Entrepreneurship, 28(4).
Murire, O. T. (2024). Artificial Intelligence and Its Role in Shaping Organizational Work Practices and Culture. Administrative Sciences, 14(12), 316. https://doi.org/10.3390/admsci14120316
Nosike, C. J., & Okerekeoti, C. U. (2022). Employee Productivity And Organizational Performance Evidence From Pharmaceutical Firms In Nigeria. International Journal of Trend in Scientific Research and Development (IJTSRD), 6(4).
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, 605–615. https://doi.org/10.1016/j.jbusres.2022.03.008
Pakpahan, R. (2021). Analisa pengaruh implementasi artificial intelligence dalam kehidupan manusia. Journal of Information System, Informatics and Computing, 5(2), 506–513.
Perkasa, D. H., Lusitawati, Susiang, M. I. N., Parashakti, R. D., & Rostina, C. N. (2023). The Influence of the Physical Work Environment, Work Motivation, and Work Discipline on Employee Performance. KnE Social Sciences. https://doi.org/10.18502/kss.v8i12.13678
Rasheed, H. (2025). Analyzing the Impact of Employee Productivity on Organizational Performance. ISRG Journal Of Economics, Business & Management. https://doi.org/10.5281/ZENODO.15128542
Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2).
Ridwan, M., Mulyani, S. R., & Ali, H. (2020). Building Behavior and Performance Citizenship: Perceived Organizational Support and Competence (Case Study at SPMI Private University In West Sumatra). International Journal of Psychosocial Rehabilitation, 24(06).
Saksono, A. S., & Yuliana, L. (2024). An analysis of the Bango Soy Sauce Brand’s Reputation and Performance. Jurnal Ekonomi, 13(01).
Sarker, I. H. (2022). AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems. SN Computer Science, 3(2), 158. https://doi.org/10.1007/s42979-022-01043-x
Sheikh, H., Prins, C., & Schrijvers, E. (2023). Artificial Intelligence: Definition and Background. In H. Sheikh, C. Prins, & E. Schrijvers, Mission AI (pp. 15–41). Springer International Publishing. https://doi.org/10.1007/978-3-031-21448-6_2
Song, Y., Qiu, X., & Liu, J. (2025). The Impact of Artificial Intelligence Adoption on Organizational Decision-Making: An Empirical Study Based on the Technology Acceptance Model in Business Management. Systems, 13(8), 683. https://doi.org/10.3390/systems13080683
Waruwu, M. (2023). Pendekatan Penelitian Pendidikan: Metode Penelitian Kualitatif, Metode Penelitian Kuantitatif dan Metode Penelitian Kombinasi. Jurnal Pendidikan Tambusai, 7(1), 2896–2910.
Yarsasi, S., Tahyudin, I., & Hariguna, T. (2025). Analisis Validitas dan Reliabilitas Kuesioner dengan Metode Partial Least Squares Structural Equation Modeling pada Aplikasi SMARTPLS. Jurnal Pendidikan Dan Teknologi Indonesia, 5(7), 1905–1913. https://doi.org/10.52436/1.jpti.885
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Imron Jarjuni, Didin Hikmah Perkasa

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish their manuscripts in this journal agree to the following conditions:
- The copyright on each article belongs to the author(s).
- The author acknowledges that the Dinasti International Journal of Education Management and Social Science (DIJEMSS) has the right to be the first to publish with a Creative Commons Attribution 4.0 International license (Attribution 4.0 International (CC BY 4.0).
- Authors can submit articles separately, arrange for the non-exclusive distribution of manuscripts that have been published in this journal into other versions (e.g., sent to the author's institutional repository, publication into books, etc.), by acknowledging that the manuscript has been published for the first time in the Dinasti International Journal of Education Management and Social Science (DIJEMSS).









































