Artificial intelligence (AI) has emerged as a transformative force in English Language Teaching (ELT), providing new opportunities for personalized learning and adaptive instruction. AI-based personalized learning systems analyze learners’ proficiency levels, linguistic challenges, learning styles, and progress patterns to create individualized learning pathways. Through technologies such as machine learning algorithms, natural language processing (NLP), intelligent tutoring systems, automated feedback tools, and adaptive testing, AI enables real-time assessment and customized content delivery. These tools enhance learner engagement by offering tailored vocabulary practice, grammar exercises, reading materials, pronunciation training, and writing feedback based on each learner’s needs. Moreover, AI supports teachers by reducing routine workloads, enabling data-informed decision-making, and facilitating a more student-centered pedagogical approach. Personalized learning not only improves linguistic accuracy and fluency but also increases learner autonomy, motivation, and long-term retention. Despite significant advantages, AI integration in ELT also raises challenges, including issues related to data privacy, digital literacy, teacher preparedness, and potential overreliance on technology. Nevertheless, current research indicates that AI-based personalized learning can substantially enhance the efficiency and effectiveness of English language teaching when implemented responsibly. This article examines the theoretical foundations, technological applications, benefits, and limitations of AI-driven personalization in ELT, offering insights into future pedagogical innovations.

Artificial intelligence, personalized learning, English language teaching, adaptive learning, machine learning, natural language processing, intelligent tutoring systems, automated feedback, learner autonomy, digital pedagogy.

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