Artificial Intelligence (AI), and in particular Machine Learning (ML), has emerged as a key technology in the development and application of wearable systems. Wearable devices such as smartwatches, fitness trackers, and biomedical sensors generate continuous streams of multimodal data, including physiological, behavioral, and contextual information. Machine Learning methods provide the computational framework to process, model, and interpret these large and complex datasets. This enables not only the extraction of meaningful patterns but also the prediction of user states and the personalization of feedback. In healthcare, ML-enhanced wearables support early detection of anomalies, monitoring of chronic conditions, and data-driven decision-making. Beyond medical applications, they also contribute to sports science, ergonomics, and human–computer interaction. As such, the integration of AI into wearable technology represents a transformative step toward more adaptive, intelligent, and preventive data-driven systems.