| Sumario: | AbstractObjectivesMethodsResultsConclusionsThis narrative review aims to explore the current applications of AI in monitoring and improving educational performance in children with autism, while identifying associated benefits, challenges, and research gaps.A narrative review design was employed to analyze peer-reviewed literature published between 2015 and 2025. A comprehensive search was conducted across PubMed, Scopus, Web of Science, IEEE Xplore, and ERIC using targeted keywords. Eligible studies focusing on the educational use of AI for children with autism were assessed through thematic synthesis.Findings revealed that AI technologies, including intelligent tutoring systems, computer vision, and conversational agents, enhance educational engagement, communication skills, and academic outcomes among autistic learners. AI-enabled tools also support educators by offering real-time feedback and data-driven insights. However, barriers such as data privacy concerns, algorithmic bias, infrastructural limitations, and insufficient training hinder widespread adoption. Moreover, a lack of longitudinal studies and standardized outcome measures were noted.AI holds significant potential to transform autism education by promoting personalized and inclusive learning. However, ethical safeguards, stakeholder involvement, and sustained research efforts are essential to ensure effective, equitable, and responsible integration.
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