The interaction of big data and artificial intelligence (AI) is revolutionising the sports industry, unlocking unprecedented insights into athlete performance, injury prevention, and tactical optimisation. This chapter highlighted how AI-driven technologies and methodologies, such as deep learning, robotics, machine learning, and computer vision, have impacted sports in athletic training, performance analysis, sports science research, and competition strategies. From real-time biometric analysis to predictive analysis of sports results, AI today facilitates the availability of large, complex datasets previously unavailable to the general population and can now serve as a basis for decision-making. Wearable technology, tracking devices, video analysis, and other technologies that have revolutionised how data is obtained in sports allow for accurate measurement of essential variables such as workload, fatigue levels, and biomechanics. This technology allows for large amounts of data that require specific techniques to collect, store and integrate them into decision-making processes. Techniques such as data mining allow for taking large and complex data and rescuing only representative variables, allowing athletes, coaches, and trainers to manage key performance indicators more effectively and efficiently. However, integrating AI into sports brings great challenges that we will explore in the chapter. This chapter presents relevant information for individuals interested in sports, enabling them to identify, select, and apply artificial intelligence while considering the characteristics of their datasets.