Análisis del impacto de la digitalización y la inteligencia artificial predictiva en la gestión de MYPES productoras del sector textil ubicados en el centro comercial mayorista y negocios andinos, parroquia Quitumbe, Distrito Metropolitano de Quito (2024-2025)

Abstract

This article addresses the impact of digitization and predictive artificial intelligence on the management of micro and small enterprises (MYPES) in the textile sector of the Andean Wholesale and Business Center, in the Quitumbe parish of Quito, (2024-2025). The problem lies in the limited adoption of advanced digital technologies, reflected in manual processes, innovative lag, and low knowledge of predictive AI, despite a competitive environment that demands efficiency, responsiveness, and data-driven strategies. The theoretical framework integrates contributions on Ecuadorian textile MYPES, digital transformation, business management, barriers to technology adoption, predictive AI models, and their relationship to productivity, efficiency, and competitiveness. Likewise, the overall objective is to analyze how digitization and predictive AI influence the management of these MYPES, using a crosssectional design with a mixed, descriptive, correlational, and exploratory approach. The methodology combines structured surveys of 80 employees and semi-structured interviews with 10 owners or managers, with statistical analysis (descriptive and Pearson correlations) and qualitative thematic coding. The results show a low level of knowledge and application of predictive AI, little use of basic digital tools, and a positive perception of their benefits in terms of inventory, production times, and decision-making. It is concluded that basic digitization already contributes to operational improvements, but predictive AI is still in its infancy; therefore, training strategies, financial support, and technical assistance are needed to bridge digital divides and consolidate more efficient, innovative, and competitive management in textile MYPES