AI Capability and SME Business Model Innovation: An Integrative Review
DOI:
https://doi.org/10.65310/0mkq7f07Keywords:
AI capability, business model innovation, dynamic capabilities, SMEs, competitive advantage.Abstract
This study examines how artificial intelligence (AI) capability is associated with business model innovation and competitive advantage in small and medium-sized enterprises (SMEs), distinguishing AI-related resources from organizational capabilities and contextual conditions. An integrative literature review synthesized 32 scholarly publications issued between 2007 and 2026, selected for their relevance to AI capability, dynamic capabilities, business model innovation, and firm performance. A theory-guided thematic synthesis organized the evidence into resource and capability foundations, organizational conversion mechanisms, boundary conditions, and strategic outcomes. The reviewed literature identifies technological infrastructure, data resources, and human expertise as important foundations of AI capability, while leadership, organizational learning, governance, and data-driven culture shape the organizational utilization of these resources. Business model innovation is identified as a potential intermediary mechanism involving changes in value proposition, value creation and delivery, and value capture. Environmental dynamism, sustainability orientation, organizational adaptability, and external integration influence the applicability of these relationships. The review develops a capability-to-business-model pathway that distinguishes AI resource foundations, capability utilization, organizational conversion processes, business model changes, and context-dependent competitive outcomes. Its contribution lies in clarifying construct boundaries and integrating previously separated explanations of AI-related organizational value in SMEs. The findings support differentiated, resource-sensitive approaches to AI adoption, although the conceptual synthesis does not establish causal effects or uniform performance benefits across firms.
Downloads
References
Alqahtani, M. M. M., Singh, H., Haddadi, E. A. A., Al-Shibli, F. S. R., & Al-Balushi, H. A. A. (2024). Impact of internet of things, cloud computing, artificial intelligence, digital capabilities, digital innovation, IT flexibility on firm performance in Saudi Arabia Islamic bank. Advances in Social Sciences Research Journal, 11(7), 71-91. https://doi.org/10.14738/assrj.117.17252
Borges, A. F. S., Laurindo, F. J. B., Spínola, M. M., Gonçalves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57, 102225. https://doi.org/10.1016/j.ijinfomgt.2020.102225
Brabete, V., Sichigea, M., Vasilescu, L., Goagără, D., & Berceanu, D. (2026). From operational efficiency to strategic meta-capability: A bibliometric analysis of the relationship between artificial intelligence and firm performance. Oeconomia Copernicana, 17(2), 387-455. https://doi.org/10.24136/oc.4214
Chalmers, D., MacKenzie, N. G., & Carter, S. (2021). Artificial intelligence and entrepreneurship: Implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5), 1028-1053. https://doi.org/10.1177/1042258720934581
Chen, J., Viardot, E., & Brem, A. (2019). Innovation and innovation management. Routledge.
Ciampi, F., Faraoni, M., Ballerini, J., & Meli, F. (2022). The co-evolution effect of digital technologies and sustainable business models on firm performance. Technological Forecasting and Social Change, 174, 121244. https://doi.org/10.1016/j.techfore.2021.121244
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
Dwivedi, Y. K., Hughes, L., Ismagilova, E., et al. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial intelligence and business value: A literature review. Information Systems Frontiers, 24, 1709-1734. https://doi.org/10.1007/s10796-021-10186-w
Farmanesh, P., Solati Dehkordi, N., Vehbi, A., & Chavali, K. (2025). Artificial intelligence and green innovation in small and medium-sized enterprises and competitive-advantage drive toward achieving sustainable development goals. Sustainability, 17(5), 2162. https://doi.org/10.3390/su17052162
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
Fosso Wamba, S., Queiroz, M. M., Pappas, I. O., & Sullivan, Y. (2024). Artificial intelligence capability and firm performance: A sustainable development perspective by the mediating role of data-driven culture. Information Systems Frontiers, 26(6), 2189-2203. https://doi.org/10.1007/s10796-023-10460-z
Ghosh, S. (2024). Developing artificial intelligence (AI) capabilities for data-driven business model innovation: Roles of organizational adaptability and leadership. Journal of Engineering and Technology Management, 73, 101851. https://doi.org/10.1016/j.jengtecman.2024.101851
Haefner, N., Wincent, J., Parida, V., & Gassmann, O. (2021). Artificial intelligence and innovation management: A review, framework, and research agenda. Technological Forecasting and Social Change, 162, 120392. https://doi.org/10.1016/j.techfore.2020.120392
Keding, C. (2021). Understanding the interplay of artificial intelligence and strategic management: Four decades of research in review. Management Review Quarterly, 71, 91-134. https://doi.org/10.1007/s11301-020-00181-x
Kitsios, F., & Kamariotou, M. (2021). Artificial intelligence and business strategy towards digital transformation: A research agenda. Sustainability, 13(4), 2025. https://doi.org/10.3390/su13042025
Loureiro, S. M. C., Guerreiro, J., & Tussyadiah, I. (2021). Artificial intelligence in business: State of the art and future research agenda. Journal of Business Research, 129, 911-926. https://doi.org/10.1016/j.jbusres.2020.11.001
Mariani, M. M., Machado, I., Magrelli, V., & Dwivedi, Y. K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122, 102623. https://doi.org/10.1016/j.technovation.2022.102623
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
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
Shahid, M. K., Mahmood, K., Altayyar, R. S., & Abdullah, H. (2026). Role of AI capabilities in sustainable firm performance: Mediating role of innovative work behavior and the moderating effect of environmental dynamism. International Journal of Productivity and Performance Management, 75(2), 651-671. https://doi.org/10.1108/IJPPM-02-2025-0114
Shao, S., Shao, Z., & Xiong, Y. (2026). The influence of AI capability on enterprise competitive advantage: The mediating effect of business model innovation. Journal of Enterprise Information Management. https://doi.org/10.1108/JEIM-08-2024-0453
Sharma, P., & Dang, G. P. (2026). Unveiling the transformative role of artificial intelligence in improving business process performance. Journal of Manufacturing Technology Management, 37(5), 905-925. https://doi.org/10.1108/JMTM-04-2025-0308
Singh, R., Khan, S., Joshi, A., Katragadda, R., & Kumar, V. (2026). Exploring the role of artificial intelligence on business innovation and entrepreneurship. Strategy & Leadership, 54(3), 302-322. https://doi.org/10.1108/SL-04-2025-0080
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319-1350. https://doi.org/10.1002/smj.640
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
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., 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. The Journal of Strategic Information Systems, 28(2), 118-144. https://doi.org/10.1016/j.jsis.2019.01.003
Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893-1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326-349. https://doi.org/10.1016/j.lrp.2018.12.001
Zhang, G., Wang, X., Xie, J., & Hu, Q. (2024). A mechanistic study of enterprise digital intelligence transformation, innovation resilience, and firm performance. Systems, 12(6), 186. https://doi.org/10.3390/systems12060186
Zott, C., Amit, R., & Massa, L. (2011). The business model: Recent developments and future research. Journal of Management, 37(4), 1019-1042. https://doi.org/10.1177/0149206311406265
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Hasan Ahmad, Mahfud Heru Fatoni, Diganta Hatiboruah (Author)
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
