AI-driven Strategies for Enhancing MSME Sales and Business Communication: A Case Study
DOI:
https://doi.org/10.51903/jmi.v3i2.28Keywords:
Artificial Intelligence (AI) Adoption, Digitalization Challenges, Micro, Small, and Medium Enterprises (MSMEs), Operational Efficiency, Technological InnovationAbstract
This research is motivated by the challenges faced by Micro, Small, and Medium Enterprises (MSMEs) in Indonesia in adopting artificial intelligence (AI) technology to enhance sales and business sustainability. The objective of this study is to examine the impact of AI adoption on the operational efficiency and sales of MSMEs, as well as to identify the challenges encountered in implementing this technology. The research methods used include in-depth interviews with ten MSME owners and a questionnaire survey involving 50 MSME participants. The findings indicate that AI implementation, particularly through the use of chatbots and data analytics for marketing, significantly enhances operational efficiency and sales, with approximately 70% of respondents reporting increased sales. However, the study also identifies key challenges such as high implementation costs, limited technological literacy, and uneven digital infrastructure. The conclusion emphasizes the importance of support from the government and relevant institutions in providing financial incentives and training programs to encourage broader AI adoption among MSMEs.
References
Alfarizi, M., Widiastuti, T., & Ngatindriatun. (2024). Exploration of Technological Challenges and Public Economic Trends Phenomenon in the Sustainable Performance of Indonesian Digital MSMEs on Industrial Era 4.0. Journal of Industrial Integration and Management, 9(1), 65–96. https://doi.org/10.1142/S2424862223500045
Anatan, L., & Nur. (2023). Micro, Small, and Medium Enterprises’ Readiness for Digital Transformation in Indonesia. Economies, 11(6). https://doi.org/10.3390/economies11060156
Arief, H. (2022). Urban Farming Micro-Entrepreuner and Digital Marketing. ICCD, 4(1), 54–58. https://doi.org/10.33068/ICCD.V4I1.440
Azzaakiyyah, H. K. (2023). The Impact of Social Media Use on Social Interaction in Contemporary Society. Technology and Society Perspectives (TACIT), 1(1), 1–9. https://doi.org/10.61100/tacit.v1i1.33
Bagale, G. S., Vandadi, V. R., Singh, D., Sharma, D. K., Garlapati, D. V. K., Bommisetti, R. K., Gupta, R. K., Setsiawan, R., Subramaniyaswamy, V., & Sengan, S. (2023). Retracted Article: Small and Medium-Sized Enterprises’ Contribution in Digital Technology. Annals of Operations Research, 326, 3–4. https://doi.org/10.1007/S10479-021-04235-5
Bailey, D. E., Faraj, S., Hinds, P. J., Leonardi, P. M., & von Krogh, G. (2022). We Are All Theorists of Technology Now: A Relational Perspective on Emerging Technology and Organizing. Https://Doi.Org/10.1287/Orsc.2021.1562, 33(1), 1–18. https://doi.org/10.1287/ORSC.2021.1562
Baldassarre, B., Keskin, D., Diehl, J. C., Bocken, N., & Calabretta, G. (2020). Implementing sustainable design theory in business practice: A call to action. Journal of Cleaner Production, 273, 123113. https://doi.org/10.1016/J.JCLEPRO.2020.123113
Belgaum, M. R., Musa, S., Alansari, Z., Alam, M. M., & Mazliham, M. S. (2021). Impact of Artificial Intelligence-enabled Software-defined Networks in Infrastructure and Operations: Trends and Challenges. International Journal of Advanced Computer Science and Applications, 12(1), 66–73. https://doi.org/10.14569/IJACSA.2021.0120109
De Simone, V., Pasquale, V. Di, & Miranda, S. (2023). An Overview on the Use of AI/ML in Manufacturing MSMEs: Solved Issues, Limits, and Challenges. Procedia Computer Science, 217, 1820–1829. https://doi.org/10.1016/J.PROCS.2022.12.382
Elgendy, N., Elragal, A., & Päivärinta, T. (2022). DECAS: A Modern Data-Driven Decision Theory for Big Data and Analytics. Journal of Decision Systems, 31(4), 337–373. https://doi.org/10.1080/12460125.2021.1894674
Farida, I., & Setiawan, D. (2022). Business Strategies and Competitive Advantage: The Role of Performance and Innovation. Journal of Open Innovation: Technology, Market, and Complexity, 8(3), 163. https://doi.org/10.3390/JOITMC8030163
Giua, C., Materia, V. C., & Camanzi, L. (2022). Smart Farming Technologies Adoption: which Factors Play A Role in the Digital Transition? Technology in Society, 68, 101869. https://doi.org/10.1016/J.TECHSOC.2022.101869
Haleem, A., Javaid, M., Singh, R. P., Suman, R., & Khan, S. (2023). Management 4.0: Concept, applications and advancements. Sustainable Operations and Computers, 4, 10–21. https://doi.org/10.1016/J.SUSOC.2022.10.002
Ingalagi, S. S., Mutkekar, R. R., & Kulkarni, P. M. (2021). Artificial Intelligence (AI) Adaptation: Analysis of Determinants among Small to Medium-sized Enterprises (SME’s). IOP Conference Series: Materials Science and Engineering, 1049(1), 012017. https://doi.org/10.1088/1757-899X/1049/1/012017
Jamwal, A., Agrawal, R., Sharma, M., Kumar, V., & Kumar, S. (2021). Developing A sustainability framework for Industry 4.0. Procedia CIRP, 98, 430–435. https://doi.org/10.1016/J.PROCIR.2021.01.129
Kulkarni, A. V., Joseph, S., & Patil, K. P. (2024). Artificial intelligence technology readiness for social sustainability and business ethics: Evidence from MSMEs in developing nations. International Journal of Information Management Data Insights, 4(2), 100250. https://doi.org/10.1016/J.JJIMEI.2024.100250
Lihong, Z. (2023). Study on Fiscal Policies for Small and Micro Enterprises under the Economic Crisis. Financial Engineering and Risk Management, 6(3), 34–40. https://doi.org/10.23977/FERM.2023.060306
Mahardhani, A. J. (2023). The Role of Public Policy in Fostering Technological Innovation and Sustainability. Journal of Contemporary Administration and Management (ADMAN), 1(2), 47–53. https://doi.org/10.61100/adman.v1i2.22
Opazo-Basáez, M., Vendrell-Herrero, F., & Bustinza, O. F. (2022). Digital Service Innovation: a Paradigm Shift in Technological Innovation. Journal of Service Management, 33(1), 97–120. https://doi.org/10.1108/JOSM-11-2020-0427/FULL/XML
Ordonez-Ponce, E., Clarke, A. C., & Colbert, B. A. (2021). Collaborative Sustainable Business Models: Understanding Organizations Partnering for Community Sustainability. Business and Society, 60(5), 1174–1215. https://doi.org/10.1177/0007650320940241
Rizvi, A. T., Haleem, A., Bahl, S., & Javaid, M. (2021). Artificial Intelligence (AI) and Its Applications in Indian Manufacturing: A Review. Lecture Notes in Mechanical Engineering, 52, 825–835. https://doi.org/10.1007/978-981-33-4795-3_76
Santosa, A. D., & Surgawati, I. (2024). Artificial Intelligence ( AI ) Adoption as Marketing Tools among Micro , Small , and Medium Enterprises ( MSMEs ) in Indonesia. Jurnal Sosial Humaniora (JSH), 17(1), 91–102. https://doi.org/10.12962/j24433527.v17i1.20520
Sharma, P., Shah, J., & Patel, R. (2022). Artificial Intelligence Framework for MSME Sectors with Focus on Design and Manufacturing Industries. Materials Today: Proceedings, 62(P13), 6962–6966. https://doi.org/10.1016/J.MATPR.2021.12.360
Suryani, U., Arief, M., Bramantoro, S., & Hamsal, M. (2022). The Impact of Digital Literacy and E-Commerce Adoption with O2O Business Adoption on The Performance of Small and Medium Enterprises. International Journal of Ebusiness And Egovernment Studies, 14(2), 199–223. https://doi.org/10.34109/ijebeg.
Taques, F. H., López, M. G., Basso, L. F., & Areal, N. (2021). Indicators used to Measure Service Innovation and Manufacturing Innovation. Journal of Innovation & Knowledge, 6(1), 11–26. https://doi.org/10.1016/J.JIK.2019.12.001
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Journal of Management and Informatics
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.