Abstract

Introduction: This study analyzes the challenges of artificial intelligence (AI) in digital education between 2019 and 2022, using a bibliometric approach. The research arose from the need to systematize existing knowledge and guide future lines of work in this emerging field. Methodology: A search was conducted in Scopus, Web of Science, Google Scholar, and ERIC, using terms such as "AI," "digital education," and "challenges." The data was filtered by year, language, and document type, and processed with tools such as VOSviewer and Bibliometrix to analyze productivity, collaborations, and thematic trends. Results: Key authors and institutions, collaborative networks, and recurring themes, such as ethics, adaptive learning, and teacher training, were identified. Scientific production showed steady growth, with a predominance of publications in English. Conclusions: The study highlights the main challenges of AI in digital education and highlights the need to investigate its ethical and pedagogical impact. The methodology employed provides a basis for future reviews.