Keywords
How to Cite
Abstract
Currently, despite microenterprises in the La Maná canton facing an increasingly digitized and competitive business environment, they still lag considerably behind in adopting emerging technologies, such as artificial intelligence (AI), to support managerial decision-making. Therefore, the general objective of this study was to analyze the impact of artificial intelligence on managerial decision-making in microenterprises in the La Maná canton. The methodology employed a quantitative approach with a correlational scope. The study sample consisted of an infinite population, with a 5% margin of error and a 95% confidence level, resulting in a sample of 385 microenterprises. The descriptive results indicate that microenterprises in the La Maná canton have an initial level of adoption, but already show clear signs of using technology in their daily operations. Therefore, business owners have begun using digital tools such as spreadsheets, online platforms, chatbots, AI assistants, and automated reports to review expenses, income, inventory, sales, and customer service. It was concluded that artificial intelligence is not yet fully integrated as a key component of business decision-making, although it is an emerging resource that can help improve information management and reduce uncertainty, leading to more effective decision-making in the micro-enterprises analyzed.
References
Andrés, M. B. (2022). Data-driven business models, programmatic advertising, artificial intelligence, and regulation: some reflections. Revista de Internet, Derecho y Politica, 5(2), 1–13. https://doi.org/10.7238/idp.v0i36.401947
Benbya, H., Pachidi, S., & Jarvenpaa, S. (2021). Special issue editorial: Artificial intelligence in organizations: Implications for information systems research. Journal of the Association for Information Systems, 22(2), 281–303. https://doi.org/10.17705/1jais.00662
Bravo, N., Ramirez, A., Orozco, F., & Espinoza, M. (2025). Automatización del soporte al cliente mediante un chatbot con IA integrado al CRM: caso de estudio empresa EDITRATECH. GADE: Revista Científica, 5(3), 206–219. https://doi.org/10.63549/rg.v5i3.705
Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data: Evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
Dunleavy, P., & Margetts, H. (2023). Data science, artificial intelligence and the third wave of digital era governance. Public Policy and Administration, 7(6), 1–12. https://doi.org/10.1177/09520767231198737
Espinoza, S., Jhovany, J., Urgiles, F., Humberto, C., Sacoto, Q., & Sebastián, A. (2023). Inteligencia de negocios para la toma de decisiones en empresas de envíos por courier. Pro Sciences: Revista de Producción, Ciencias e Investigación, 6(43), 338–356. https://doi.org/10.29018/issn.2588-1000vol6iss43
Gallardo, K., Gerónimo, R., Mogollón, L., & Polo, G. (2024). La personalización de UX mediante IA en el marketing digital en Latinoamérica. Revista Ciencias y Artes, 2(4).
Goswami, A., Patel, R., Mavani, C., & Mistry, H. K. (2024). Identifying Online Spam Using Artificial Intelligence. International Journal on Recent and Innovation Trends in Computing and Communication, 12(2), 1–9.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
Kumar, B. R. (2024). The Role of Artificial Intelligence in Personalized Marketing Strategies. In F. Khurshit, & N. Kapoor, (eds.). NITYA.
Loukis, E., Maragoudakis, M., & Kyriakou, N. (2020). Artificial intelligence-based public sector data analytics for economic crisis policymaking. Transforming Government: People, Process and Policy, 14(4), 639–662. https://doi.org/10.1108/TG-11-2019-0113
Murillo, A., & Vizuete, J. (2023). El impacto de la IA en el marketing de contenidos dentro del contexto del marketing 5.0. SIGMA, 11(1). https://doi.org/10.24133/yz85g716
Naslednikov, M. (2024). The Impact of Artificial Intelligence on Customer Relationship Management (CRM) Strategies. Haaga-Helia University of Applied Sciences, 16(3).
Naz, H., & Kashif, M. (2025). Artificial intelligence and predictive marketing: an ethical framework from managers’ perspective. Spanish Journal of Marketing - ESIC, 29(1), 1–24. https://doi.org/10.1108/SJME-06-2023-0154
Odilov, J. (2024). Digital Use of Artificial Intelligence in Public Administration. International Journal of Law and Policy, 3(2), 1–9.
Potla, R. T., & Consulting, S. (2025). Artificial Intelligence and Machine Learning in CRM: Leveraging Data for Predictive Analytics. Journal of Artificial Intelligence Research, 4(2), 1–21.
Salgado, O. (2018). El Papel De La Percepción En La Toma De Decisiones De La Alta Dirección. Iberoforum. Revista de Ciencias Sociales de La Universidad Iberoamericana, 6(12), 1–19.
Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257
Subadra, S., Natarajan, S., & Salma Shajahan, U. (2024). The Impact Of Artificial Intelligence (AI) On Digital Marketing. Migration Letters, 21(6), 1–12.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.