Bridging Leadership and AI Adoption: The Mediating Role of Phenomenological Learning and the Moderating Effect of Digital Culture
Keywords:
TranTransformational Leadership, Digital Culture, Adoption AI, Phenomenological Learning
Abstract
This study investigates the role of transformational leadership, phenomenological learning, and digital culture in shaping the successful adoption of Artificial Intelligence (AI) within Indonesian organizations. Using a quantitative survey design, data were collected from 412 respondents across the service and manufacturing sectors. Structural Equation Modeling Partial Least Squares (SEM-PLS) was employed to test the hypothesized relationships. The findings reveal that transformational leadership significantly enhances phenomenological learning, which in turn positively influences AI adoption. Moreover, phenomenological learning mediates the relationship between transformational leadership and AI adoption, while digital culture strengthens the link between leadership and learning. These results highlight the importance of integrating phenomenological learning as a reflective and human-centered process in organizational digital transformation. The study contributes to theory by extending Phenomenological Learning Theory into technology adoption research and underscores the moderating role of digital culture in shaping organizational readiness. Practically, the findings suggest that leaders should foster reflective learning environments and cultivate adaptive digital cultures to accelerate inclusive and sustainable AI adoption.
References
Abubakar, U., Onasanya, S. A., & Ibrahim, H. A. (2024). Student perspectives and impact of AI integration in pedagogical practices in Nigerian tertiary institutions. Advances in Mobile Learning Educational Research, 4(2), 1135–1148. https://doi.org/10.25082/amler.2024.02.008
Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1504/EJIM.2021.114662
Bass, B. M., & Avolio, B. J. (1994). Improving organizational effectiveness through transformational leadership. Thousand Oaks, CA: Sage Publications.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kumar, A., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2019). Artificial Intelligence ( AI ): Multidisciplinary perspectives on emerging challenges , opportunities , and agenda for research , practice and policy. International Journal of Information Management, August, 0–1. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Fatima, I., Grover, V., Khan, I. R., Ahmad, N., & Yadav, A. (2023). Artificial Intelligence in Medical Field. EAI Endorsed Transactions on Pervasive Health and Technology, 9, 1–5. https://doi.org/10.4108/EETPHT.9.4713
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.
Gama, F., & Magistretti, S. (2025). Artificial intelligence in innovation management : A review of innovation capabilities and a taxonomy of AI applications. Journal of Product Innovation Management, 76–111. https://doi.org/10.1111/jpim.12698
Gama, S. M., Phahlane, M., & Malungana, L. (2025). A digitalisation model for operational efficiency of operations in the insurance industry. South African Journal of Information Management, 27(1), 1–10. https://doi.org/10.4102/sajim.v27i1.1943
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. In Practical Assessment, Research and Evaluation (Vol. 21, Issue 1). http://www.
Hair, J. F., Sarstedt, M., & Ringle, C. M. (2017). Partial least squares structural equation modeling with R. In Practical Assessment, Research and Evaluation (Vol. 21, Issue 1).
Herath, D. B., Ode, E., & Herath, G. B. (2025). Can AI replace humans? Comparing the capabilities of AI tools and human performance in a business management education scenario. British Educational Research Journal, 51(3), 1073–1096. https://doi.org/10.1002/berj.4111
King, S., & Prasetyo, J. (2023). Assessing generative A.I. through the lens of the 2023 Gartner Hype Cycle for Emerging Technologies: a collaborative autoethnography. Frontiers in Education, 8(December), 1–9. https://doi.org/10.3389/feduc.2023.1300391
Kolb, D. A. (2015). Experiential Learning: Experience as The Source of Learning and Development. In Prentice Hall, Inc. https://doi.org/10.1016/B978-0-7506-7223-8.50017-4
Kumar, A., Shankar, A., Hollebeek, L. D., Behl, A., & Lim, W. M. (2025). Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption. Journal of Business Research, 189(January), 115160. https://doi.org/10.1016/j.jbusres.2024.115160
McElheran, K., Yang, M.-J., Brynjolfsson, E., & Kroff, Z. (2025). The Rise of Industrial AI in America: Microfoundations of the productivity J curves. January. https://doi.org/10.2139/ssrn.5036270
Nasiri, M., Saunila, M., Rantala, T., & Ukko, J. (2022). Sustainable innovation among small businesses: The role of digital orientation, the external environment, and company characteristics. Sustainable Development, 30(4), 703–712. https://doi.org/10.1002/sd.2267
Nguyen, Q. Do, & Nguyen, H. T. (2023). Entrepreneurship education and entrepreneurial intention: The mediating role of entrepreneurial capacity. International Journal of Management Education, 21(1), 217–238. https://doi.org/10.1016/j.ijme.2022.100730
Nguyen, H. M., Mai, L. T., & Huynh, T. L. (2019). The role of transformational leadership toward work performance through intrinsic motivation: A study in the pharmaceutical field in vietnam. Journal of Asian Finance, Economics and Business, 6(4), 201–212. https://doi.org/10.13106/jafeb.2019.vol6.no4.201
Parker, D. A., & Roumell, E. A. (2020). A Functional Contextualist Approach to Mastery Learning in Vocational Education and Training. Frontiers in Psychology, 11(June), 1–11. https://doi.org/10.3389/fpsyg.2020.01479
Pereira, H. M., Martins, I. S., Rosa, I. M. D., & Kim, H. (2024). Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050. Science, 384(6694), 458–465. https://doi.org/https://doi.org/10.1126/science.adn3441
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/IJCHM-04-2020-0259
Salminen, V., Pyykkönen, M., Salminen, K., & Tian, O. (2025). Human Intelligence and Artificial Intelligence Interaction in Start-Up Enterprise. Intelligent Human Systems Integration (IHSI 2025): Integrating People and Intelligent Systems, 160(January). https://doi.org/10.54941/ahfe1005817
Schein, E. H., & Schein, P. (2017). Organisation, culture and leadership. In Construction Project Management: An Integrated Approach. https://doi.org/10.4324/9780203006986
Senge, P. (1990). he Fifth Discipline: The Art and Practice of the Learning Organization. Doubleday/Currency.
Serpa, S., Sá, M. J., & Ferreira, C. M. (2022). Digital Organizational Culture: Contributions to a Definition and Future Challenges. Academic Journal of Interdisciplinary Studies, 11(4), 22–33. https://doi.org/10.36941/ajis-2022-0095
Sheng, B., Chen, X., Li, T., Ma, T., Yang, Y., Bi, L., & Zhang, X. (2022). An overview of artificial intelligence in diabetic retinopathy and other ocular diseases. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.971943
Übellacker, T. (2025). MAKING SENSE OF AI LIMITATIONS: HOW INDIVIDUAL PERCEPTIONS SHAPE ORGANIZATIONAL READINESS FOR AI ADOPTION.
Van Manen, M. (2016). Phenomenology of Practice: Meaning-Giving Methods in Phenomenological Research and Writing. Routledge. https://doi.org/https://doi.org/10.4324/9781315422657
Zhou, L., Rudin, C., Gombolay, M., Spohrer, J., Zhou, M., & Paul, S. (2023). From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues. AIS Transactions on Human-Computer Interaction, 15(1), 111–135. https://doi.org/10.17705/1thci.00185
Anderson, J. C., & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach. Psychological Bulletin, 103(3), 411–423. https://doi.org/10.1504/EJIM.2021.114662
Bass, B. M., & Avolio, B. J. (1994). Improving organizational effectiveness through transformational leadership. Thousand Oaks, CA: Sage Publications.
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kumar, A., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2019). Artificial Intelligence ( AI ): Multidisciplinary perspectives on emerging challenges , opportunities , and agenda for research , practice and policy. International Journal of Information Management, August, 0–1. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Fatima, I., Grover, V., Khan, I. R., Ahmad, N., & Yadav, A. (2023). Artificial Intelligence in Medical Field. EAI Endorsed Transactions on Pervasive Health and Technology, 9, 1–5. https://doi.org/10.4108/EETPHT.9.4713
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50.
Gama, F., & Magistretti, S. (2025). Artificial intelligence in innovation management : A review of innovation capabilities and a taxonomy of AI applications. Journal of Product Innovation Management, 76–111. https://doi.org/10.1111/jpim.12698
Gama, S. M., Phahlane, M., & Malungana, L. (2025). A digitalisation model for operational efficiency of operations in the insurance industry. South African Journal of Information Management, 27(1), 1–10. https://doi.org/10.4102/sajim.v27i1.1943
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. In Practical Assessment, Research and Evaluation (Vol. 21, Issue 1). http://www.
Hair, J. F., Sarstedt, M., & Ringle, C. M. (2017). Partial least squares structural equation modeling with R. In Practical Assessment, Research and Evaluation (Vol. 21, Issue 1).
Herath, D. B., Ode, E., & Herath, G. B. (2025). Can AI replace humans? Comparing the capabilities of AI tools and human performance in a business management education scenario. British Educational Research Journal, 51(3), 1073–1096. https://doi.org/10.1002/berj.4111
King, S., & Prasetyo, J. (2023). Assessing generative A.I. through the lens of the 2023 Gartner Hype Cycle for Emerging Technologies: a collaborative autoethnography. Frontiers in Education, 8(December), 1–9. https://doi.org/10.3389/feduc.2023.1300391
Kolb, D. A. (2015). Experiential Learning: Experience as The Source of Learning and Development. In Prentice Hall, Inc. https://doi.org/10.1016/B978-0-7506-7223-8.50017-4
Kumar, A., Shankar, A., Hollebeek, L. D., Behl, A., & Lim, W. M. (2025). Generative artificial intelligence (GenAI) revolution: A deep dive into GenAI adoption. Journal of Business Research, 189(January), 115160. https://doi.org/10.1016/j.jbusres.2024.115160
McElheran, K., Yang, M.-J., Brynjolfsson, E., & Kroff, Z. (2025). The Rise of Industrial AI in America: Microfoundations of the productivity J curves. January. https://doi.org/10.2139/ssrn.5036270
Nasiri, M., Saunila, M., Rantala, T., & Ukko, J. (2022). Sustainable innovation among small businesses: The role of digital orientation, the external environment, and company characteristics. Sustainable Development, 30(4), 703–712. https://doi.org/10.1002/sd.2267
Nguyen, Q. Do, & Nguyen, H. T. (2023). Entrepreneurship education and entrepreneurial intention: The mediating role of entrepreneurial capacity. International Journal of Management Education, 21(1), 217–238. https://doi.org/10.1016/j.ijme.2022.100730
Nguyen, H. M., Mai, L. T., & Huynh, T. L. (2019). The role of transformational leadership toward work performance through intrinsic motivation: A study in the pharmaceutical field in vietnam. Journal of Asian Finance, Economics and Business, 6(4), 201–212. https://doi.org/10.13106/jafeb.2019.vol6.no4.201
Parker, D. A., & Roumell, E. A. (2020). A Functional Contextualist Approach to Mastery Learning in Vocational Education and Training. Frontiers in Psychology, 11(June), 1–11. https://doi.org/10.3389/fpsyg.2020.01479
Pereira, H. M., Martins, I. S., Rosa, I. M. D., & Kim, H. (2024). Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050. Science, 384(6694), 458–465. https://doi.org/https://doi.org/10.1126/science.adn3441
Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/IJCHM-04-2020-0259
Salminen, V., Pyykkönen, M., Salminen, K., & Tian, O. (2025). Human Intelligence and Artificial Intelligence Interaction in Start-Up Enterprise. Intelligent Human Systems Integration (IHSI 2025): Integrating People and Intelligent Systems, 160(January). https://doi.org/10.54941/ahfe1005817
Schein, E. H., & Schein, P. (2017). Organisation, culture and leadership. In Construction Project Management: An Integrated Approach. https://doi.org/10.4324/9780203006986
Senge, P. (1990). he Fifth Discipline: The Art and Practice of the Learning Organization. Doubleday/Currency.
Serpa, S., Sá, M. J., & Ferreira, C. M. (2022). Digital Organizational Culture: Contributions to a Definition and Future Challenges. Academic Journal of Interdisciplinary Studies, 11(4), 22–33. https://doi.org/10.36941/ajis-2022-0095
Sheng, B., Chen, X., Li, T., Ma, T., Yang, Y., Bi, L., & Zhang, X. (2022). An overview of artificial intelligence in diabetic retinopathy and other ocular diseases. Frontiers in Public Health, 10. https://doi.org/10.3389/fpubh.2022.971943
Übellacker, T. (2025). MAKING SENSE OF AI LIMITATIONS: HOW INDIVIDUAL PERCEPTIONS SHAPE ORGANIZATIONAL READINESS FOR AI ADOPTION.
Van Manen, M. (2016). Phenomenology of Practice: Meaning-Giving Methods in Phenomenological Research and Writing. Routledge. https://doi.org/https://doi.org/10.4324/9781315422657
Zhou, L., Rudin, C., Gombolay, M., Spohrer, J., Zhou, M., & Paul, S. (2023). From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues. AIS Transactions on Human-Computer Interaction, 15(1), 111–135. https://doi.org/10.17705/1thci.00185
Published
2025-09-16
How to Cite
Hashmi, M., Jovinda Percillia Ma’rifatul Umairoh, Mega Aprillia Pratamasari, Ogun Prayoga, & Zaki Nur Hamam. (2025). Bridging Leadership and AI Adoption: The Mediating Role of Phenomenological Learning and the Moderating Effect of Digital Culture. International Journal of Economics, Business and Innovation Research, 4(05), 515-530. https://doi.org/10.63922/ijebir.v4i05.2287
.png)
Contact Person +6282139474255
Email : ijebir@citakonsultindo.or.id / editor.ijebir@gmail.com
