Artificial Intelligence (AI) has become an integral part of modern life, presenting significant challenges and responsibilities for its ethical use. Its integration into higher education is crucial, as institutions work to incorporate AI into curricula and teaching-learning processes, ensuring its effective and appropriate application. While its use has sparked debates in academic circles, the consensus is clear: AI is a powerful tool for creating innovative content that aligns with course objectives and transforms traditional educational practices.

Determining students' learning styles helps us understand how they process and retain information. Models such as VARK and Gardner's Multiple Intelligences identify sensory preferences, categorizing learners into visual, auditory, and kinesthetic groups. Neuro-Linguistic Programming adds depth by exploring how sensory channels influence mental representations.

Mindset theory, as formulated by Dweck, categorizes individuals into those with a fixed mindset (who view intelligence as static) or a growth mindset (who see intelligence as malleable and improvable through effort). Recent updates recognize "mixed mindsets," shaped by context and individual experiences, highlighting the need for flexible and personalized educational interventions.

Similarly, this study explores the use of AI to identify students' learning styles and mindsets, with the aim of improving academic performance and closing knowledge gaps. By simplifying data analysis, AI enables educators to design personalized activities that meet the diverse needs of student populations. Conducted with 47 university students from disciplines such as Business, Engineering, Art and Design, Social Sciences, and Health Sciences, the study focused on courses like Entrepreneurship and Innovation and Food Service Management. ChatGPT was the primary analytical tool, streamlining data processing and improving existing course activities.

The results revealed that 70.2% exhibited mixed mindsets, combining fixed and growth orientations, with a dominant leaning toward growth in 90.9% of the cases. The remaining students exclusively identified with a growth mindset. Learning style preferences showed that 57.45% of students were auditory learners, 25.53% were visual learners, and 17.02% were kinesthetic learners.

The value of AI in education lies in its ability to quickly analyze students' needs and simplify the creation of adaptive, personalized learning activities. By identifying key mindsets and learning styles, educators can use AI to design experiences that align with their students' unique profiles. While critics argue that relying on AI may oversimplify educational personalization, this study highlights its potential to revolutionize learning when applied ethically and thoughtfully. With responsible implementation, AI can foster dynamic, accessible, and effective educational environments that promote both academic achievement and personal growth.

Thus, this study demonstrated how AI can be used and leveraged by educators to simplify the analysis process of recognizing the type of student population, processing and analyzing data obtained through the same tool, and, in a second stage, redesigning activities based on the results obtained, incorporating the use of AI in the process of student development.

Keywords: Artificial intelligence, learning styles, mindset, innovation.