Digital Transformation, AI, and Inclusive Education: Creating Equitable Learning Ecosystems

This article examines the complex interrelationship between digital transformation, artificial intelligence adoption, and inclusive education in creating more equitable learning environments. Through mixed-methods research combining systematic literature review, survey data from 412 educational practitioners, and 37 semi-structured interviews with diverse stakeholders, the study explores how these three forces collectively reshape educational access, engagement, and outcomes for diverse learners. Statistical analyses reveal significant correlations between implementation patterns and equity outcomes (r=0.57, p.001), with institutional commitment to inclusion (β=0.42, p.001) emerging as the strongest predictor in regression models. Findings identify five key implementation patterns that significantly influence equity outcomes, including intentional design approaches, comprehensive integration strategies, continuous evaluation practices, stakeholder participation models, and balanced innovation-support frameworks. The study identifies critical barriers to equitable implementation, including persistent digital divides, algorithmic biases, professional development gaps, and governance challenges. The research contributes an empirically grounded Education Equity Technology (EET) model conceptualizing the interaction zones where these domains converge, while providing evidence-based recommendations for educational leaders and policymakers. These findings have important theoretical implications for understanding sociotechnical systems in education and practical applications for creating more inclusive digital learning environments.