Business transformation of msmes in the digital era: a qualitative study on cross-functional artificial intelligence integration
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Abstract
This study examines how artificial intelligence (AI) is integrated into managerial routines and business processes of micro, small, and medium-sized enterprises (MSMEs) in the context of digital transformation. Using a qualitative approach, data were collected through semi-structured interviews with ten MSME owners and managers and analyzed using thematic analysis. The findings reveal that AI adoption is driven primarily by pragmatic considerations, particularly tangible business benefits, ease of use, and facilitating conditions, while social influence plays a limited role. More importantly, once AI becomes part of routine practice, its impact extends across marketing, human resources, finance, and operations. The study demonstrates that AI contributes to business transformation by enabling cross-functional integration and more coherent managerial decision-making. These results highlight that the value of AI in MSMEs emerges from its routinized and integrated use rather than from adoption alone
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Relifra, R., Hamdani, F., Bharti, R. and Nurhayati, D. (2026) “Business transformation of msmes in the digital era: a qualitative study on cross-functional artificial intelligence integration”, Jurnal Mantik, 9(4), pp. 1181-1194. doi: 10.35335/mantik.v9i4.6927.
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campagnolo, diego, Gianecchini, M., & Mosca, L. (2023). Configurations of business model themes and strategies in small firms: a qualitative comparative analysis. Journal of Management and Governance, 28, 1–29. https://doi.org/10.1007/s10997-023-09680-x
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Cekuls, A. (2023). AI-Driven Competitive Intelligence: Enhancing Business Strategy and Decision Making. Journal of Intelligence Studies in Business. https://api.semanticscholar.org/CorpusID:257468323
Chatterjee, S., Chaudhuri, R., Vrontis, D., & Basile, G. (2022). Digital transformation and entrepreneurship process in SMEs of India: a moderating role of adoption of AI-CRM capability and strategic planning. Journal of Strategy and Management, 15(3), 416–433. https://doi.org/10.1108/JSMA-02-2021-0049
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Chouki, M., Talea, M., Okar, C., & Chroqui, R. (2019). Barriers to Information Technology Adoption Within Small and Medium Enterprises: A Systematic Literature Review. International Journal of Innovation and Technology Management, 17. https://doi.org/10.1142/S0219877020500078
Clemente-Almendros, J. A., Nicoara-Popescu, D., & Pastor-Sanz, I. (2024). Digital transformation in SMEs: Understanding its determinants and size heterogeneity. Technology in Society, 77, 102483. https://doi.org/https://doi.org/10.1016/j.techsoc.2024.102483
Creswell, J. W., & Creswell, J. D. (2018). Mixed Methods Procedures. In Research Defign: Qualitative, Quantitative, and Mixed M ethods Approaches.
Creswell, J. W., & Poth, C. N. (2017). Qualitative Inquiry and Research Design: Choosing Among Five Approaches. SAGE Publications. https://books.google.co.id/books?id=gX1ZDwAAQBAJ
Dalal, S., Lilhore, U. K., Simaiya, S., Radulescu, M., & Belascu, L. (2024). Improving efficiency and sustainability via supply chain optimization through CNNs and BiLSTM. Technological Forecasting and Social Change, 209(December 2023), 123841. https://doi.org/10.1016/j.techfore.2024.123841
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