This article examines how artificial intelligence (AI) can accelerate the transformation of digital education by enabling personalization at scale, automating routine assessment, enriching teacher learner interaction, and improving inclusion for diverse learners. Drawing on comparative analysis of initiatives in the United States, South Korea, China, and the European Union alongside current reforms in Uzbekistan, the paper synthesizes evidence on adaptive learning systems, AI-supported feedback, learning analytics, and assistive technologies (e.g., speech recognition and text-to-speech). The study outlines a practical framework that links four capability layers data infrastructure, algorithmic services, pedagogical applications, and governance showing how each layer contributes to measurable learning gains and operational efficiency. Key opportunities include individualized learning paths, rapid formative assessment, early risk detection through predictive analytics, and teacher augmentation via AI copilots for lesson design and differentiation.  

Artificial intelligence in education, digital learning, personalized learning

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