The Role of AI in Early Educational Settings : A Systematic Review with a Methodological Exploration of an AI-Assisted Review Workflow

Background Early educational settings, such as child care, preschool, kindergarten, and early school classrooms, are important contexts for supporting young children’s development. Artificial intelligence (AI)-based activities are being introduced into these settings, yet evidence on how they are used and what developmental outcomes their use is associated with remains limited. Objectives This review provides a narrative synthesis of the empirical studies examining AI-based activities in early educational settings, using an AI-assisted workflow to support data extraction during evidence synthesis. Methods We identified 13 empirical studies through searches of seven academic databases, including PsycINFO and ERIC. Information was extracted on study characteristics, AI-based tools and activities, and child developmental outcomes. Given heterogeneity in study designs, tool and activity types, and child outcomes, findings, including statistical ones, were synthesized results narratively. Results Diverse tools were identified, including Speech recognition Systems (n = 5), AI-Powered Robots (n = 4), Adaptive Learning Systems (n = 4), AI-Enhanced Extended reality (n = 3), and Conversational AI and Chatbot (n = 2), demonstrating potential benefits across cognitive, language, literacy, social, emotional, and fine motor domains. Most associations were found between AI and children’s language (n = 5) and literacy (n = 3). Author’s Conclusions AI-based activities in early educational settings show preliminary promise, particularly for language and literacy, but the evidence base is limited and heterogeneous. More rigorous studies are needed to examine developmental outcomes, equity, safety, and sustained effects. Researchers should specifically address equity issues and potential adverse effects when conducting research in this area.