Balancing AI’s Promise and Pressure: A Dual-Process Model of AI Adoption Psychological States, and Employee Performance in Indonesia
Abstract
Full Text:
PDFReferences
Aldabbas, H., Pinnington, A., & Lahrech, A. (2023). The influence of perceived organizational support on employee creativity: The mediating role of work engagement. Current Psychology, 42(8), 6501–6515. https://doi.org/10.1007/s12144-021-01992-1
Ali, M., Khan, T. I., & Şener, İ. (2025). Transforming hospitality: The dynamics of AI integration, customer satisfaction, and organizational readiness in enhancing firm performance. Journal of Hospitality and Tourism Technology. https://doi.org/10.1108/JHTT-04-2024-0261
Ariño-Mateo, E., Venegas, M. A., Mora-Luis, C., & Pérez-Jorge, D. (2024). The level of conscientiousness trait and technostress: A moderated mediation model. Humanities and Social Sciences Communications, 11(1), 302. https://doi.org/10.1057/s41599-024-02766-3
Aryanti, I., & Perkasa, D. H. (2024). The Effect of Leadership Compensation and Work Discipline on Employee Performance (Study at PT Panca Putra Solusindo Jakarta). Review: Journal of Multidisciplinary in Social Sciences, 1(04), Article 04. https://doi.org/10.59422/rjmss.v1i04.302
Bakker, A. B., & Demerouti, E. (2024). Job demands–resources theory: Frequently asked questions. Journal of Occupational Health Psychology, 29(3), 188–200. https://doi.org/10.1037/ocp0000376
Boccoli, G., Gastaldi, L., & Corso, M. (2024). Transformational leadership and work engagement in remote work settings: The moderating role of the supervisor’s digital communication skills. Leadership & Organization Development Journal, 45(7), 1240–1257. https://doi.org/10.1108/LODJ-09-2023-0490
Burhan, Q.-A. (2024). Unraveling the AI enigma: How perceptions of artificial intelligence forge career adaptability through the crucible of career insecurity and skill development. Management Research Review, 48(3), 470–488. https://doi.org/10.1108/MRR-01-2024-0022
Chen, L., & Zeng, S. (2021). The Relationship Between Intolerance of Uncertainty and Employment Anxiety of Graduates During COVID-19: The Moderating Role of Career Planning. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.694785
Cheung, S. F., & Cheung, S.-H. (2024). manymome: An R package for computing the indirect effects, conditional effects, and conditional indirect effects, standardized or unstandardized, and their bootstrap confidence intervals, in many (though not all) models. Behavior Research Methods, 56(5), 4862–4882. https://doi.org/10.3758/s13428-023-02224-z
Chughtai, M. S., Syed, F., Naseer, S., & Chinchilla, N. (2024). Role of adaptive leadership in learning organizations to boost organizational innovations with change self-efficacy. Current Psychology, 43(33), 27262–27281. https://doi.org/10.1007/s12144-023-04669-z
Compeau, D. R., & Higgins, C. A. (1995). Computer Self-Efficacy: Development of a Measure and Initial Test. MIS Quarterly, 19(2), 189–211. https://doi.org/10.2307/249688
Ersanlı, C. Y., Çelik, F., Barjesteh, H., Duran, V., & Manoochehrzadeh, M. (2025). A review of global reskilling and upskilling initiatives in the age of AI. AI and Ethics. https://doi.org/10.1007/s43681-025-00767-9
Eseye, E., & Debebe, E. (2024). Effect of Employee Engagement on Job Performance Case of Tibebe Ghion Specialized Hospital. International Journal of Management Research and Emerging Sciences, 14(4), Article 4. https://doi.org/10.56536/ijmres.v14i4.673
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
George, D. A. S. (2024a). Artificial Intelligence and the Future of Work: Job Shifting Not Job Loss. Partners Universal Innovative Research Publication, 2(2), Article 2. https://doi.org/10.5281/zenodo.10936490
George, Dr. A. S. (2024b). Sleep Disrupted: The Evolving Challenge of Technology on Human Sleep Patterns Over Two Centuries. https://doi.org/10.5281/ZENODO.11179796
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
Hasan, M. R., Ray, R. K., & Chowdhury, F. R. (2024). Employee Performance Prediction: An Integrated Approach of Business Analytics and Machine Learning. Journal of Business and Management Studies, 6(1), 215–219. https://doi.org/10.32996/jbms.2024.6.1.14
Hemanth Kumar Tummalapalli, Addada Narasimha Rao, Gangula Kamal, Naga Kumari, & Swarup Kumar. (2024). Exploring AI-Driven Management: Impact on Organizational Performance, Decision Making, Efficiency, and Employee Engagement. Journal of Advanced Research in Applied Sciences and Engineering Technology, 148–163. https://doi.org/10.37934/araset.52.2.148163
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
Hou, Y., & Fan, L. (2024). Working with AI: The Effect of Job Stress on Hotel Employees’ Work Engagement. Behavioral Sciences, 14(11), Article 11. https://doi.org/10.3390/bs14111076
Idris, H. (2024). The Effects of FOMO on Investment Behavior in the Stock Market. Golden Ratio of Data in Summary, 4(2), 879–887. https://doi.org/10.52970/grdis.v4i2.757
Kartikasari, E. D. K. E. D. (2025). Economic Growth Strategies and Poverty in Rural Indonesia: Subjective Experiencesof Rural Communities in Indonesia’s Rural Areas in Facing Economic Development Challenges. Journal of Economic and Financial Studies, 1(1), Article 1.
Kaushik, S., & Tiwari, P. K. (2023). Job Engagement: A Theoretical Foundation for Enhanced Perspective. 9(1).
Kim, B.-J., Kim, M.-J., & Lee, J. (2024). The impact of an unstable job on mental health: The critical role of self-efficacy in artificial intelligence use. Current Psychology, 43(18), 16445–16462. https://doi.org/10.1007/s12144-023-05595-w
Kim, B.-J., & Lee, J. (2025). The Dark Sides of Artificial Intelligence Implementation: Examining How Corporate Social Responsibility Buffers the Impact of Artificial Intelligence-Induced Job Insecurity on Pro-Environmental Behavior Through Meaningfulness of Work. Sustainable Development, 33(3), 4732–4756. https://doi.org/10.1002/sd.3376
Koen, J., & van Bezouw, M. J. (2021). Acting Proactively to Manage Job Insecurity: How Worrying About the Future of One’s Job May Obstruct Future-Focused Thinking and Behavior. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.727363
Lee, A. T., Ramasamy, R. K., & Subbarao, A. (2025). Understanding Psychosocial Barriers to Healthcare Technology Adoption: A Review of TAM Technology Acceptance Model and Unified Theory of Acceptance and Use of Technology and UTAUT Frameworks. Healthcare, 13(3), Article 3. https://doi.org/10.3390/healthcare13030250
Mahapatra, M., & Ford, D. P. (2024). Technostress and disengagement from knowledge sharing: Insights from pre-pandemic and mid-pandemic data sets. Journal of Knowledge Management, 28(9), 2689–2711. https://doi.org/10.1108/JKM-08-2023-0711
Meng, K., Xiao, X., Wei, W., Chen, G., Nashalian, A., Shen, S., Xiao, X., & Chen, J. (2022). Wearable Pressure Sensors for Pulse Wave Monitoring. Advanced Materials, 34(21), 2109357. https://doi.org/10.1002/adma.202109357
Nawaz, A., & Shabir, G. (2024). Transforming Work Performance: The Role of Artificial Intelligence in Job Enhancement. Unpublished. https://doi.org/10.13140/RG.2.2.11699.85287
Nawaz, A., Soomro, S. A., & Mansoor Kundi, Y. (2023). Linking engagement for innovation with innovative performance: The role of discretionary efforts and knowledge-sharing behaviour. International Journal of Innovation Management, 27(06), 2350027. https://doi.org/10.1142/S1363919623500275
Prayag, G., & Dassanayake, D. M. C. (2023). Tourism employee resilience, organizational resilience and financial performance: The role of creative self-efficacy. Journal of Sustainable Tourism, 31(10), 2312–2336. https://doi.org/10.1080/09669582.2022.2108040
Pykett, J., & Paterson, M. (2022). Stressing the ‘body electric’: History and psychology of the techno-ecologies of work stress. History of the Human Sciences, 35(5), 185–212. https://doi.org/10.1177/09526951221081754
Qudus, L. (2025). Leveraging Artificial Intelligence to Enhance Process Control and Improve Efficiency in Manufacturing Industries. International Journal of Computer Applications Technology and Research. https://doi.org/10.7753/ijcatr1402.1002
Radic, A., Singh, S., Singh, N., Ariza-Montes, A., Calder, G., & Han, H. (2024). The good shepherd: Linking artificial intelligence (AI)-driven servant leadership (SEL) and job demands-resources (JD-R) theory in tourism and hospitality. Journal of Hospitality and Tourism Insights, 8(4), 1494–1521. https://doi.org/10.1108/JHTI-06-2024-0628
Rane, N. L., Paramesha, M., Choudhary, S. P., & Rane, J. (2024). Artificial Intelligence, Machine Learning, and Deep Learning for Advanced Business Strategies: A Review. Partners Universal International Innovation Journal, 2(3), Article 3. https://doi.org/10.5281/zenodo.12208298
Ruth, A. O., Meddour, H., & Majid, A. H. A. (2024). Unleashing work engagement: Sighting the influence of technology self-efficacy and the mediating role of ICT adoption. Multidisciplinary Science Journal, 6(9), 2024089–2024089. https://doi.org/10.31893/multiscience.2024089
Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The Measurement of Work Engagement With a Short Questionnaire: A Cross-National Study. Educational and Psychological Measurement, 66(4), 701–716. https://doi.org/10.1177/0013164405282471
Seidl, B. (2025). Legitimizing and Contesting Lethal Autonomous Weapons Systems in Japan: A Multilayered Analysis of Public Discourse. https://bristoluniversitypressdigital.com/edcollchap-oa/book/9781529237191/ch014.xml
Selenko, E., Bankins, S., Shoss, M., Warburton, J., & Restubog, S. L. D. (2022). Artificial Intelligence and the Future of Work: A Functional-Identity Perspective. Current Directions in Psychological Science, 31(3), 272–279. https://doi.org/10.1177/09637214221091823
Setiadi, & Muharam, H. (2024). Logistics Innovation in Developing Economies: Integrating Digital Solutions in E-Commerce Supply Chains. Sinergi International Journal of Logistics, 2(4), Article 4. https://doi.org/10.61194/sijl.v2i4.733
Shao, C., Nah, S., Makady, H., & McNealy, J. (2025). Understanding User Attitudes Towards AI-Enabled Technologies: An Integrated Model of Self-Efficacy, TAM, and AI Ethics. International Journal of Human–Computer Interaction, 41(5), 3053–3065. https://doi.org/10.1080/10447318.2024.2331858
Singh, Y., & Phoolka, S. (2024). Unleashing the creative spark: The mediating role of employee work engagement on the relationship between employee training and creativity. International Journal of Educational Management, 38(2), 429–446. https://doi.org/10.1108/IJEM-07-2023-0342
Suseno, Y., Chang, C., Hudik, M., & Fang, E. S. (2023). Beliefs, anxiety and change readiness for artificial intelligence adoption among human resource managers: The moderating role of high- performance work systems. In Artificial Intelligence and International HRM. Routledge.
Tan, K.-L., Hofman, P. S., Noor, N., Tan, S.-R., Hii, I. S. H., & Cham, T.-H. (2024). Does artificial intelligence improve hospitality employees’ individual competitive productivity? A time-lagged moderated-mediation model involving job crafting and meaningful work. Current Issues in Tourism, 0(0), 1–18. https://doi.org/10.1080/13683500.2024.2391114
Tarafdar, M., Cooper, C. L., & Stich, J.-F. (2019). The technostress trifecta - techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information Systems Journal, 29(1), 6–42. https://doi.org/10.1111/isj.12169
Uche Ojika, F., Oseremen Owobu, W., Anthony Abieba, O., Janet Esan, O., Chibunna Ubamadu, B., & Ifesinachi Daraojimba, A. (2024). The Role of Artificial Intelligence in Business Process Automation: A Model for Reducing Operational Costs and Enhancing Efficiency. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 1449–1462. https://doi.org/10.62225/2583049x.2024.4.6.4046
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540
Wadhwa, S. N., Bhardwaj, G., Srivastava, A. P., & Malik, R. (2025a). AI-driven job insecurity and work performance: Unveiling the mediating role of psychological well-being. International Journal of Information Technology. https://doi.org/10.1007/s41870-025-02602-0
Wadhwa, S. N., Bhardwaj, G., Srivastava, A. P., & Malik, R. (2025b). AI-driven job insecurity and work performance: Unveiling the mediating role of psychological well-being. International Journal of Information Technology. https://doi.org/10.1007/s41870-025-02602-0
Yang, L., & Zhao, S. (2024). AI-induced emotions in L2 education: Exploring EFL students’ perceived emotions and regulation strategies. Computers in Human Behavior, 159, 108337. https://doi.org/10.1016/j.chb.2024.108337
Yu, X., Xu, S., & Ashton, M. (2022). Antecedents and outcomes of artificial intelligence adoption and application in the workplace: The socio-technical system theory perspective. Information Technology & People, 36(1), 454–474. https://doi.org/10.1108/ITP-04-2021-0254
DOI: http://dx.doi.org/10.14203/STIPM.2025.429
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 STI Policy and Management Journal

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright of Journal of STI (Science Technology Innovation) Policy and Management Journal (e-ISSN 2502-5996 p-ISSN 2540-9786). Powered by OJS.

















