<![CDATA[The development of wearable device technology and Artificial Intelligence (AI) has opened new opportunities in sports science, particularly in monitoring training load and preventing injury risk. Wearable devices enable objective, real-time measurement of physiological and biomechanical parameters, while AI plays a role in analyzing complex data to identify training load patterns and predict potential injuries. The purpose of this study is to synthesize findings from 15 scientific articles related to the use of wearable devices and AI in monitoring training load and sports injury risk. The method used was a literature review of internationally reputable articles discussing the use of wearable sensors, machine learning, and deep learning in the sports context. The results of the study indicate that the integration of wearable devices and AI can improve the accuracy of training load monitoring, strengthen injury risk prediction, and support data-driven decision-making in training management. However, most research still focuses on elite athletes, so its application in the context of physical education and school sports is still limited. In conclusion, the integration of wearable devices and AI has great potential in optimizing training load and preventing injuries, and requires further development for its widespread adaptation to various populations and sports coaching contexts.]]>
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