Análisis Comparativo del Burnout Universitario según el Área de Estudio mediante Estadística Inferencial e IA Generativa

University burnout syndrome affects students' academic performance and mental health. This studyexamines its relationship with the field of study using the Maslach Burnout Inventory – GeneralSurvey for Students (MBI-GSS) and advanced statistical analysis techniques. For data collection,processing and analysis the ANALYTIQ SURVEYS platform was specifically developed, for thisstudy. This system automates survey data collection, performs data cleaning and preprocessing,generates descriptive and inferential statistics, and interprets results using generative artificialintelligence. Statistical tests such as ANOVA were applied to identify significant differencesamong disciplines. Findings reveal that medical students exhibit the highest levels of emotionalexhaustion, but maintain a healthier level of professional efficacy compared to Engineering andBusiness Administration students, who show a greater impact in this dimension. AI-driven analysisenabled the identification of key patterns and the generation of personalized recommendations,facilitating preventive and intervention strategies in educational institutions.