Neuroeducation integrates knowledge from neuroscience, psychology, and pedagogy to inform evidence-based teaching strategies, especially during early childhood—a stage of heightened brain plasticity and foundational learning. Concurrently, artificial intelligence (AI) offers adaptive and personalized tools that can support neurocognitive development through data-driven educational interventions. This systematic review examines the empirical convergence between neuroeducation and AI in early childhood education, analyzing how AI-enabled tools reflect and apply neuroeducational principles. The review followed the PRISMA protocol to ensure methodological rigor. A total of 735 records were initially identified across five major databases (Scopus, Web of Science, PubMed, PsycINFO, and Elsevier). After applying strict inclusion and exclusion criteria, 18 peer-reviewed studies published between 2020 and 2025 were selected for final analysis. Each study was classified according to a four-part taxonomy of AI interaction modalities: embodied robots, screen-based systems, voice-only interfaces, and multimodal environments. The findings reveal that AI-supported interventions can enhance executive functions, cognitive flexibility, attention regulation, and socioemotional development when designed in alignment with neurodevelopmental needs. Embodied and multimodal AI systems demonstrated effectiveness in fostering engagement, interaction, and social cognition, while screen-based and voice-only systems proved useful for cognitive and linguistic skills. Ethical challenges were also identified, including privacy concerns, emotional dependency, equity of access, and developmental appropriateness. This study highlights that the integration of AI and neuroeducation requires careful interdisciplinary collaboration among educators, technologists, and policymakers. Beyond summarizing current evidence, the review underscores the importance of adopting developmentally appropriate practices, ensuring ethical safeguards, and fostering teacher training in AI-informed pedagogy. By synthesizing empirical research, this work provides a conceptual and practical foundation for advancing early childhood education through a neuroeducational framework enriched by AI technologies.
