Adaptive learning has emerged as a key strategy for enhancing education in digital environments, particularly in the development of complex competencies such as social entrepreneurship. This study presents the implementation of SEL4C-GPT, an artificial intelligence-based model designed to personalize the learning experience of university students in online and hybrid courses. Based on an initial assessment, the platform generates individualized learning pathways, optimizing competency acquisition through microlearning, data analytics, and real-time personalization. The research was conducted with 196 students from Mexico, Chile, Colombia, and Bolivia, analyzing the impact of SEL4C-GPT on four key sub-competencies of social entrepreneurship. The findings indicate a significant improvement in social innovation and financial sustainability, along with variations based on gender and educational context. The technology enabled content and activities to be adapted to specific needs, strengthening engagement and interaction in digital learning platforms. The results highlight the potential of adaptive learning in blended and online models, demonstrating how artificial intelligence facilitates the transition from traditional methodologies to more effective digital formats. The study concludes that automated personalization not only enhances the student experience but also drives the scalability of innovative strategies in higher education, fostering more flexible and inclusive learning environments aligned with the demands of digital-age education.
