Digital Transformation and AI Adoption in Small and Medium-sized Enterprises: Business Model Innovation, Costs and Benefits, and Implementation Barriers
DOI:
https://doi.org/10.56830/WRBA03202606Keywords:
Digital Transformation, Artificial Intelligence, Small & Medium Enterprise, Innovation, Business ModelsAbstract
There’s a great pressure on SMEs for digital transformation. In this perspective, the integration of AI technology can streamline operations, enhance customer insights, and enable personalized services. In addition, the pandemic created by COVID-19 accelerated the tendency of business sectors to adopt AI. SMEs can gain a competitive advantage by adopting AI in business operations. Despite the opportunities that AI poses, small businesses are slow in the AI adoption process. Therefore, in this situation, it is significant to analyze the challenges concerning resistance to change, limited availability of human resources, etc., of SMEs adopting AI. According to a recent Microsoft Asia AI Adoption report, nearly half of all Asian and small businesses say the significant concerns are about AI-led current issues and concerns. In addition to investing in the company's AI strategy, creating an AI governance framework, and establishing collaboration with the AI partner, it is also important to have sufficient data and quality. SMEs are slow in AI adoption. Despite this, when it comes to the share of SMEs, they are large in numbers. Therefore, it is suggested to create a tailored roadmap for technology adoption with the support of the government. In order for a company to support each other and share infrastructure, it is necessary to have a cooperative ecosystem. However, for SMEs that have a shortage of manpower, it is recommended to set the milestone for the AI journey to achieve a given goal. AI is limited in developing countries like Southeast Asia. Therefore, there are several policies to help tailor companies in terms of lack of financial resources policy or to establish a public-private partnership that openly collaborates and exchanges knowledge and share investment risks. These suggestions are a small step to help SMEs digital transformation successfully. However, overcoming these barriers is essential for business growth and resilience and will allow SMEs to lead innovation in the marketplace
References
Arroyabe, M. F., Arranz, C. F., De Arroyabe, I. F., & de Arroyabe, J. C. (2024). Analyzing AI adoption in European SMEs: A study of digital capabilities, innovation, and external environment. Technology in Society, 79, 102733. DOI: https://doi.org/10.1016/j.techsoc.2024.102733
Boonmee, C., Mangkalakeeree, J., & Jeong, Y. (2025). Towards sustainable digital transformation: AI adoption barriers and enablers among SMEs in Northern Thailand. Sustainable Futures. DOI: https://doi.org/10.1016/j.sftr.2025.101169
D'Ippolito, B., Messeni Petruzzelli, A., & Panniello, U. (2019). Archetypes of incumbents' strategic responses to digital innovation. DOI: https://doi.org/10.1108/JIC-04-2019-0065
Drydakis, N. (2022). Artificial Intelligence and Reduced SMEs’ Business Risks. A Dynamic Capabilities Analysis During the COVID-19 Pandemic. DOI: https://doi.org/10.2139/ssrn.4114609
E Cuc, J., & Miina, A. (2018). Classifying the Business Model from a Strategic and Innovation Perspective.
Esangbedo, C. O., Zhang, J., Esangbedo, M. O., Kone, S. D., & Xu, L. (2024). The role of industryacademia collaboration in enhancing educational opportunities and outcomes under the digital driven Industry 4.0. Journal of Infrastructure, Policy and Development, 8(1), 2569. DOI: https://doi.org/10.24294/jipd.v8i1.2569
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. Sustainability. DOI: https://doi.org/10.3390/su17052162
Himeur, Y., Elnour, M., Fadli, F., Meskin, N., Petri, I., Rezgui, Y., et al. (2022). AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives. Artificial intelligence review, 56(6),4929. DOI: https://doi.org/10.1007/s10462-022-10286-2
Iyelolu, T. V., Agu, E. E., Idemudia, C., & Ijomah, T. I. (2024). Driving SME innovation with AI solutions: overcoming adoption barriers and future growth opportunities. International Journal of Science and Technology Research Archive, 7(1), 036-054. DOI: https://doi.org/10.53771/ijstra.2024.7.1.0055
Jussen, I., Möller, F., Schweihoff, J., Gieß, A., Giussani, G., & Otto, B. (2024). Issues in interorganizational data sharing: Findings from practice and research challenges. Data & Knowledge Engineering, 150, 102280. DOI: https://doi.org/10.1016/j.datak.2024.102280
Keränen, T. (2025). Adoption of AI in Finnish Small and Medium size Enterprises: AI opportunities, challenges and misconceptions.
Khan, A. N., Jabeen, F., Mehmood, K., Soomro, M. A., & Bresciani, S. (2023). Paving the way for technological innovation through adoption of artificial intelligence in conservative industries. Journal of Business Research, 165, 114019. DOI: https://doi.org/10.1016/j.jbusres.2023.114019
Krishnan, R. (2024). Challenges and benefits for small and medium enterprises in the transformation to smart manufacturing: a systematic literature review and framework. Journal of Manufacturing Technology Management. DOI: https://doi.org/10.1108/JMTM-07-2022-0255
Le, A. T., Kunasekaran, P., & Rasoolimanesh, S. M. (2022). Investigating the determinants and process of destination management system (DMS) implementation. Change Management. DOI: https://doi.org/10.1108/JOCM-11-2020-0352
Lokuge, S., & Duan, S. (2023). Exploring the Enablers of Digital Transformation in Small and Medium-Sized Enterprise. DOI: https://doi.org/10.4018/978-1-6684-4895-3.ch008
Lu, X., Wijayaratna, K., Huang, Y., & Qiu, A. (2022). AI-enabled opportunities and transformation challenges for SMEs in the post-pandemic era: a review and research agenda. Frontiers in Public Health. DOI: https://doi.org/10.3389/fpubh.2022.885067
Olukoya, D., Alumona, P., & Okoro, S. C. (2025). AI in SMEs-A holistic approach for successful implementations. Journal of Science. DOI: https://doi.org/10.30574/ijsra.2025.17.3.3278
Quach, S., Thaichon, P., D. Martin, K., Weaven, S., & W. Palmatier, R. (2022). Digital technologies:
tensions in privacy and data.
Roman, A., & Rusu, V. D. (2022). Digital technologies and the performance of small and medium enterprises. Studies in Business and Economics. DOI: https://doi.org/10.2478/sbe-2022-0055
Schleth, H. C., Breu, F., Kanbach, D. K., & Kraus, S. (2026). AI-driven business model innovation in service industries: a systematic review. The Service Industries Journal, 1-25. DOI: https://doi.org/10.1080/02642069.2026.2631386
Schönberger, M. (2023). Artificial intelligence for small and medium-sized enterprises: Identifying key applications and challenges. Journal of Business Management. DOI: https://doi.org/10.32025/JBM23004
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), 302322. DOI: https://doi.org/10.1108/SL-04-2025-0080
Terho, T. (2018). Artificial intelligence transformation and implementation frameworks.
Ugbaja, U. S., Nwabekee, U. S., Owobu, W. O., & Abieba, O. A. (2024). The impact of AI and business process automation on sales efficiency and customer relationship management (CRM) performance. International Journal of Advanced Multidisciplinary Research and Studies, 4(6), 1829-1841. DOI: https://doi.org/10.62225/2583049X.2024.4.6.4156
Usman, F. O., Kess-Momoh, A. J., Ibeh, C. V., Elufioye, A. E., Ilojianya, V. I., & Oyeyemi, O. P. (2024). Entrepreneurial innovations and trends: A global review: Examining emerging trends, challenges, and opportunities in the field of entrepreneurship, with a focus on how technology and globalization are shaping new business ventures. International Journal of Science and Research Archive, 11(1), 552-569. DOI: https://doi.org/10.30574/ijsra.2024.11.1.0079
Von Leipzig, T., Gamp, M., Manz, D., Schottle, K., Ohlhausen, P., Oosthuizen, G., et al. (2017). Initialising customer-orientated digital transformation in enterprises. DOI: https://doi.org/10.1016/j.promfg.2017.02.066
Zhang, M., Chen, X., Xie, H., Esposito, L., Parziale, A., Taneja, S., et al. (2024). Top of tide: Nexus between organization agility, digital capability and top management support in SME digital transformation. DOI: https://doi.org/10.1016/j.heliyon.2024.e31579
