From Human Leadership to Hybrid Intelligence Leadership: A Theory-Building Qualitative Study
Keywords:
Hybrid intelligence leadership, artificial intelligence, qualitative research, theory building, human–AI collaboration, digital leadership, organizational decision-making.Abstract
This study aimed to develop a theory-building qualitative model explaining how leadership is transformed when human judgment, artificial intelligence systems, and organizational decision processes become interdependent. This qualitative study used a theory-building design based on semi-structured interviews with 24 participants selected through purposive and theoretical sampling from technology-intensive, financial, consulting, healthcare, and digital service organizations in Tehran. Participants included senior managers, digital transformation leaders, data and AI specialists, human resource managers, and strategy executives with direct experience in AI-enabled organizational decision-making. Data collection continued until theoretical saturation was achieved at the twenty-first interview, followed by three confirmatory interviews. Interviews were audio-recorded, transcribed verbatim, and analyzed using open, axial, and selective coding. NVivo software was used to organize transcripts, coding nodes, analytical memos, and category relationships. The analysis generated five main categories: algorithmic decision augmentation, relational reconfiguration of leadership authority, ethical and explainable governance, human–AI capability integration, and adaptive orchestration of hybrid intelligence. The findings showed that hybrid intelligence leadership does not simply replace human leadership with AI-based automation; rather, it reconstructs leadership as a distributed, interpretive, and ethically mediated practice in which leaders translate algorithmic outputs into organizationally legitimate decisions. Participants emphasized that AI strengthened analytical speed and pattern recognition but increased the need for human sensemaking, accountability, contextual judgment, and trust-building. The proposed model conceptualizes hybrid intelligence leadership as a dynamic leadership form in which human leaders act as orchestrators of human expertise, algorithmic insight, ethical safeguards, and adaptive organizational learning. The study contributes to leadership theory by explaining the transition from leader-centered decision authority to a hybrid configuration of judgment, data, technology, and collective intelligence.
References
Avolio, B. J., Kahai, S., & Dodge, G. E. (2000). E-leadership: Implications for theory, research, and practice. The Leadership Quarterly, 11(4), 615–668. https://doi.org/10.1016/S1048-9843(00)00062-X
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton.
Charmaz, K. (2014). Constructing grounded theory (2nd ed.). SAGE.
Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (4th ed.). SAGE.
Cortellazzo, L., Bruni, E., & Zampieri, R. (2019). The role of leadership in a digitalized world: A review. Frontiers in Psychology, 10, 1938. https://doi.org/10.3389/fpsyg.2019.01938
Creswell, J. W., & Poth, C. N. (2018). Qualitative inquiry and research design: Choosing among five approaches (4th ed.). SAGE.
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. M. (2019). Hybrid intelligence. Business & Information Systems Engineering, 61(5), 637–643. https://doi.org/10.1007/s12599-019-00595-2
Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013). Seeking qualitative rigor in inductive research: Notes on the Gioia methodology. Organizational Research Methods, 16(1), 15–31. https://doi.org/10.1177/1094428112452151
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human–AI symbiosis in organizational decision-making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007
Kamar, E. (2016). Directions in hybrid intelligence: Complementing AI systems with human intelligence. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (pp. 4070–4073). AAAI Press.
Kellogg, K. C., Valentine, M. A., & Christin, A. (2020). Algorithms at work: The new contested terrain of control. Academy of Management Annals, 14(1), 366–410. https://doi.org/10.5465/annals.2018.0174
Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE.
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
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J. F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A., … Wellman, M. (2019). Machine behaviour. Nature, 568(7753), 477–486. https://doi.org/10.1038/s41586-019-1138-y
Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257
Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18(4), 298–318. https://doi.org/10.1016/j.leaqua.2007.04.002
Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–123.
