Hybrid Human-AI Business Models: A Socio-Technical Framework for Artificial Intelligence-Driven Value Creation
Keywords:
artificial intelligence, business model innovation, human-AI collaboration, socio-technical systems, hybrid intelligence, digital transformationAbstract
Artificial intelligence is increasingly reshaping how organizations create, deliver, and capture value in digitally mediated environments. Despite its rapid diffusion across industries, existing research remains conceptually fragmented in explaining how artificial intelligence interacts with human expertise to transform business model innovation. Prior studies on AI adoption emphasize algorithmic capabilities and automation, while business model research focuses on value creation architectures, leaving the socio-technical mechanisms linking these perspectives underexplored. This article addresses this gap by developing a conceptual framework explaining the emergence of hybrid human–AI business models. The study adopts a theory-building approach based on conceptual synthesis across three research streams: artificial intelligence in organizations, business model innovation, and socio-technical systems theory. Through cross-theoretical integration, the framework identifies three core mechanisms: cognitive augmentation, task reconfiguration, and adaptive value creation. These mechanisms explain how algorithmic capabilities interact with human expertise to reshape value proposition design, transform value delivery architectures, and enable the continuous adaptation of business models. The framework contributes by integrating fragmented literature and conceptualizing AI-enabled business models as hybrid socio-technical systems, while providing a foundation for future empirical research on human–AI collaboration and strategic transformation.
References
Amit, R., & Zott, C. (2020). Business model innovation strategy: Transformational concepts and tools for entrepreneurial leaders. Wiley.
Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing artificial intelligence. MIS Quarterly, 45(3), 1433–1450. https://doi.org/10.25300/MISQ/2021/16274
Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital business strategy: Toward a next generation of insights. MIS Quarterly, 37(2), 471–482. https://doi.org/10.25300/MISQ/2013/37.2.3
Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. W. W. Norton & Company.
Brynjolfsson, E., Rock, D., & Syverson, C. (2021). The productivity J-curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333–372. https://doi.org/10.1257/mac.20180386
Clauss, T. (2017). Measuring business model innovation: Conceptualization, scale development, and proof of performance. R&D Management, 47(3), 385–403. https://doi.org/10.1111/radm.12186
Cockburn, I. M., Henderson, R., & Stern, S. (2019). The impact of artificial intelligence on innovation. Research Policy, 48(1), 103–116. https://doi.org/10.1016/j.respol.2018.10.014
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
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., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2023). So what if ChatGPT wrote it? Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
Faraj, S., Pachidi, S., & Sayegh, K. (2018). Working and organizing in the age of artificial intelligence. Information and Organization, 28(1), 62–70. https://doi.org/10.1016/j.infoandorg.2018.02.007
Foss, N. J., & Saebi, T. (2017). Fifteen years of research on business model innovation: How far have we come, and where should we go? Journal of Management, 43(1), 200–227. https://doi.org/10.1177/0149206316675927
Jaakkola, E. (2020). Designing conceptual articles: Four approaches. AMS Review, 10(1–2), 18–26. https://doi.org/10.1007/s13162-020-00161-0
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
Kraus, S., Durst, S., Ferreira, J. J., Veiga, P., Kailer, N., & Weinmann, A. (2021). Digital transformation in business and management research: An overview of the current status quo. International Journal of Information Management, 63, 102466. https://doi.org/10.1016/j.ijinfomgt.2021.102466
Mikalef, P., Boura, M., Lekakos, G., & Krogstie, J. (2019). Big data analytics capabilities and innovation: The mediating role of dynamic capabilities and moderating effect of the environment. British Journal of Management, 30(2), 272–298. https://doi.org/10.1111/1467-8551.12343
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), 103773. https://doi.org/10.1016/j.respol.2019.03.018
Newell, S., & Marabelli, M. (2015). Strategic opportunities (and challenges) of algorithmic decision-making: A call for action on the long-term societal effects of ‘datification’. Journal of Strategic Information Systems, 24(1), 3–14. https://doi.org/10.1016/j.jsis.2015.02.001
Parker, G. G., Van Alstyne, M. W., & Choudary, S. P. (2016). Platform revolution: How networked markets are transforming the economy. W. W. Norton & Company.
Pasmore, W., Winby, S., Mohrman, S., & Vanasse, R. (2019). Reflections: Sociotechnical systems design and organization change. Journal of Change Management, 19(2), 67–85. https://doi.org/10.1080/14697017.2018.1553761
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
Teece, D. J. (2018). Business models and dynamic capabilities. Long Range Planning, 51(1), 40–49. https://doi.org/10.1016/j.lrp.2017.06.007
Trabucchi, D., & Buganza, T. (2020). Fostering digital platform innovation: From two-sided to multi-sided platforms. Creativity and Innovation Management, 29(2), 345–358. https://doi.org/10.1111/caim.12320
Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. https://doi.org/10.1177/001872675100400101
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2021). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365. https://doi.org/10.1016/j.jbusres.2016.08.009