SCHOOL MANAGEMENT AND ARTIFICIAL INTELLIGENCE: CHALLENGES AND PERSPECTIVES FOR EDUCATIONAL INNOVATION

Abstract

This article analyzes the challenges and strategies for integrating Artificial Intelligence (AI) into school management, based on an integrative literature review conducted in the CAPES Periodicals Portal, with access to the SciELO database, within the time frame of 2015 to 2025. The research, of a qualitative, exploratory, and bibliographic nature, used descriptors in Portuguese, English, and Spanish related to AI, school management, data-driven decision making, management training, ethics, and data governance. After applying inclusion and exclusion criteria, a representative and relevant corpus was obtained, allowing for a critical systematization of recent academic production. The synthesis of the findings is organized into four axes: (i) data governance and ethics, with emphasis on protection, transparency, and accountability; (ii) training and management skills, highlighting enhanced digital literacy, leadership for change, and critical interpretation of evidence; (iii) data-driven decision-making processes, involving indicators, learning analytics, and integration into pedagogical routines; (iv) barriers and facilitators, which include infrastructure, data integration, organizational culture, and pilot projects with formative evaluation. The results indicate that the effectiveness of AI in school management requires robust institutional frameworks of information governance, continuous training programs, data standardization and quality, as well as incremental implementation, focusing on equity and student learning.