PROFILE OF LATO SENSU SPECIALIZATION COURSES IN ARTIFICIAL INTELLIGENCE IN BRAZIL: A QUANTITATIVE ANALYSIS OF THE E-MEC SYSTEM

Abstract

Artificial Intelligence (AI) has grown globally and has become a strategic technology across multiple sectors, increasing the demand for specialized training. In this context, lato sensu postgraduate education plays a relevant role in professional upskilling. This study aimed to analyze the profile of lato sensu specialization courses related to AI in Brazil. We conducted a quantitative and descriptive study based on administrative data from the e-MEC system, identifying 2,762 active courses. The analyses examined course distribution by field of knowledge, mode of delivery, workload, duration, number of vacancies, and regional location. The results show a strong concentration of courses in Computing-related fields, even though AI has a transversal character and high application potential in areas such as education, health, business, and engineering. Distance education predominates, and course offerings concentrate in the Southeast and South regions of the country. The findings also reveal substantial heterogeneity in training models, particularly regarding course duration and number of vacancies. Overall, the results indicate that the current offer of AI specialization courses still reproduces historical patterns of educational concentration. This study provides a national overview of AI training and offers empirical evidence to support educational planning and public policy formulation in emerging technologies.