Future of Language Learning: Unveiling the Power of AI‐Driven Adaptive Platforms to Tailor Language Learning Based on Learners' Needs, Proficiency and Learning Styles

ABSTRACT This study investigates the interplay between EFL students' needs, proficiency levels, learning styles and AI‐powered adaptive learning platforms in fostering academic engagement. A positive and significant relationship was observed, demonstrating that AI‐powered platforms effectively cater to EFL students' individual needs, proficiency levels and learning styles, thereby enhancing their engagement. Among the variables studied, learning styles showed a stronger correlation with academic engagement compared to proficiency levels. The findings also highlight varying degrees of mediation by the examined factors. Learners' needs emerged as the strongest mediator, suggesting that platforms tailored to specific educational requirements significantly boost academic engagement. Learning styles were identified as another substantial mediator, with platforms aligning their instructional methods to students' preferences contributing to enhanced engagement. Conversely, proficiency levels served as a weaker mediator, indicating that platform features may not substantially differ across varying proficiency groups. These insights emphasise the critical role of personalisation in AI‐driven educational platforms and its implications for optimising learning outcomes in EFL contexts.