Human–AI Collaboration Readiness Across Generations: The Roles of Digital Skills, Growth Mindset, and Organizational Support
DOI: https://doi.org/10.70184/c5wezw47
Human-AI Collaboration; , Multigenerational Readiness; , Digital Skills; , Growth Mindset; , Organizational Support.
Abstract
Purpose: This study examines the simultaneous effects of digital skills, growth mindset, and organizational support on human–AI collaboration readiness among multigenerational academic workers, with generational cohort as a moderating variable.
Research Method: A sequential explanatory mixed-method design was employed. Quantitative data were collected from 280 academic workers at a public university in Indonesia using stratified random sampling and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The quantitative findings were further explored through semi-structured interviews with 12 key informants representing Generation X, Millennials, and Generation Z.
Results and Discussion: Organizational support emerged as the strongest and most consistent predictor of human–AI collaboration readiness across generations (β = 0.384; p < 0.001). Generational cohort significantly moderated the effects of digital skills (β = 0.110; p = 0.041) and growth mindset (β = 0.154; p = 0.004), with stronger effects among Generation Z workers. This pattern is identified as the “Generation Z Acceleration Effect.” The model explained 62.4% of the variance in collaboration readiness.
Implications: The findings support generationally differentiated HR interventions for strengthening human–AI collaboration in higher education and contribute to SDGs 4, 8, and 9.
Originality: This study integrates individual capabilities, psychological orientation, organizational support, and generational differences into a unified model of human–AI collaboration readiness and introduces the Generation Z Acceleration Effect.
References
Aggarwal, R. (2025). AI and the workplace: Shaping roles, skills, and human growth. Inspira, 1(1), 14–28. https://doi.org/10.62823/inspira/2025/9788199024557/14
Ahmed, N. I. (2025). Human-AI collaboration for inclusive growth and sustainable development. SBS Monograph, 1(1), 1–9. https://doi.org/10.70301/sbs.mono.2025.1.9
Allen, J., Rorissa, A., Alemneh, D., et al. (2025). Fostering and cultivating human–AI collaboration and partnerships in an evolving workplace. Proceedings of the Association for Information Science and Technology, 61(1), 1365–1370. https://doi.org/10.1002/pra2.1365
Andrei, A. G., Mațcu-Zaharia, M., & Mariciuc, D. F. (2024). Ready to grip AI's potential? Insights from an exploratory study on perceptions of human-AI collaboration. BRAIN: Broad Research in Artificial Intelligence and Neuroscience, 15(2), 212–230. https://doi.org/10.18662/brain/15.2/560
Challa, A. (2025). Artificial intelligence (AI) for achieving SDGs. International Journal of Research in Social Sciences and Humanities, 15(3), 1–15. https://doi.org/10.37648/ijrssh.v15i03.008
Cordella, A., Gualdi, F., & van de Laar, M. (2023). Digital skills within the public sector: A missing link to achieve the sustainable development goals (SDGs). Information Polity, 28(2), 175–192. https://doi.org/10.3233/IP-230008
Doargajudhur, M., & Baboo, S. (2024). Navigating the impact of digital technologies on the multigenerational workforce in the post-COVID-19 work environment. In Digital Transformation and Its Impact on Human Resources (pp. 213–231). IGI Global. https://doi.org/10.4018/979-8-3693-6366-9.ch013
Ferreira, D. H. L., Normanha, B. A., Sugahara, C. R., et al. (2025). Human-centered AI to accelerate the SDGs: Evidence map (2020–2024). Preprints, 2025110527. https://doi.org/10.20944/preprints202511.0527.v1
Goyal, N., Shukla, B., Rathore, J. S., et al. (2025). Accelerate universities' role for the implementation of the UN SDGs 2030: Synergizing AI and human intelligence. Inspira, 2(2), 107–120. https://doi.org/10.62823/inspira/2025/9788199024557/09
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage.
Kanungo, D. (2025). Generational wisdom: A framework for leveraging multigenerational strengths in modern organizations. IntechOpen. https://doi.org/10.5772/intechopen.1009298
Kerstetter, W. (2025). Bridging the divide: Understanding the relationship between generation gaps and talent stagnation in the workforce. Journal of Organizational Psychology, 25(2), 45–60. https://doi.org/10.64657/akzt7856
Müller, S. (2025). Bridging educational skills for sustainable development: Lessons from digital transformation models. Zenodo. https://doi.org/10.5281/zenodo.17447890
Priya. (2024). Reskilling and upskilling the workforce for the AI-driven world. In Advances in Human and Social Aspects of Technology (pp. 150–165). IGI Global. https://doi.org/10.4018/979-8-3693-4147-6.ch011
Putra, A. S. B. (2024). Membangun sinergi lintas generasi: Strategi kolaboratif untuk meningkatkan kinerja organisasi di era digital. Jurnal Pengabdian Kepada Masyarakat Pakmas, 4(2), 155–168. https://doi.org/10.54259/pakmas.v4i2.3129
Simon, C., Franco, G., Kerstetter, W., et al. (2025). Developing dynamic workforce talent with Gen Z and millennials. Journal of Human Resource Development, 14(3), 78–92. https://doi.org/10.64657/wmqd1054
Yunita, F. E., & Isnaini, S. (2024). Analisis peran kepemimpinan digital dan budaya organisasi dalam meningkatkan kinerja karyawan: Tinjauan literatur sistematis. RESLAJ: Religion Education Social Laa Roiba Journal, 6(11), 5110–5130. https://doi.org/10.47467/reslaj.v6i11.5295
Zong, R., Yan, S., Shang, L., et al. (2025). Bidirectional human–AI collaboration for equitable student performance prediction via deep uncertainty learning. Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI), 1114–1122. https://doi.org/10.24963/ijcai.2025/1114
Published
Issue
Section
Categories
License
Copyright (c) 2026 Wahdaniah Wahdaniah, Ayyub Yunus, Mujirin M. Yamin (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the full copyright of their published articles. By submitting and publishing their work, authors grant Vifada Management and Social Sciences the right of first publication. All published articles are simultaneously licensed under the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided that the original author(s) and the initial publication in this journal are properly acknowledged.








