THE IMPACTS OF ARTIFICIAL INTELLIGENCE ON THE TEACHING-LEARNING PROCESS IN BASIC EDUCATION

Abstract

The accelerated advance of Artificial Intelligence (AI) has driven significant transformations in education, expanding possibilities for personalized teaching through adaptive platforms, virtual tutors, and pedagogical recommendation systems. This article aims to analyze the impacts of AI on the teaching-learning process in basic education, discussing its potential, its limits, and the challenges it poses to teacher training. A qualitative approach of a bibliographic and documentary nature is adopted, grounded in reference books, scientific articles indexed in SciELO, CAPES Periódicos and ResearchGate, institutional reports from UNESCO, and Brazilian regulatory documents such as the National Common Curricular Base. The results indicate that AI offers relevant gains in personalization and support for teaching work, but that its pedagogical effectiveness depends directly on teacher preparedness, the technological infrastructure available in schools, and the maintenance of human mediation as a structuring axis of the educational process. It is also found that the uncritical incorporation of these tools may deepen existing educational inequalities if not accompanied by public policies for continuing education and the democratization of access. It is concluded that AI does not replace the role of the teacher, but can qualify it, provided its adoption is guided by pedagogical, ethical, and equity criteria.