Adaptive learning systems, which tailor content, pacing, and feedback to individual students’ unique needs, offer personalized learning experiences. This customization is enabled by sophisticated learning analytics that continuously collect and analyse students’ performance and interactions with learning materials to optimize the learning process. As a result, students benefit from self-paced and self-directed learning opportunities, fostering greater engagement and autonomy. This article examines the architecture and functioning of adaptive learning systems with a particular focus on leveraging artificial intelligence (AI) and machine learning. It explores the practical applications of these systems in language classrooms and beyond, addressing both the opportunities and challenges they present. The article concludes with suggestions for future directions in the field.