Towards personalized primary education with AI: possibilities, limits, and pedagogical horizons

Abstract

Artificial intelligence (AI) offers a promising opportunity to personalize learning in primary education by adapting content and processes to each student’s individual characteristics. This article critically reflects on the possibilities and limitations of implementing AI in real-world contexts, particularly within the Mexican education system. From a teaching-oriented and theoretical perspective, it examines applications such as adaptive platforms, intelligent tutoring systems, and automated assessments, as well as the associated risks: digital inequality, the displacement of the teacher's role, algorithmic bias, and data surveillance. The article proposes integrating AI with a humanistic pedagogical approach, emphasizing teacher training, equitable technological inclusion, and the ethical design of educational tools. It concludes that AI should not replace teachers but rather become an ally in building more equitable and meaningful learning experiences. This reflection calls for a critical adoption of AI in basic education, centered on students’ well-being and holistic development.