DATA-DRIVEN SPORTS: THE CHALLENGES OF ARTIFICIAL INTELLIGENCE IN GLOBAL SPORTS MANAGEMENT
Keywords:
Artificial Intelligence, Data-Driven Sports, Sports Analytics, Athlete Performance, Sports Technology.Abstract
The rapid integration of Artificial Intelligence (AI) into the sports industry has transformed how athletes train, teams compete, and organizations make strategic decisions. This paper examined the role of AI in enabling data-driven sports by exploring its applications in performance analysis, injury prevention, talent identification, tactical decision-making, fan engagement, and sports management. The paper argues that AI-driven technologies, including machine learning, computer vision, wearable sensors, and predictive analytics, have significantly improved the collection, processing, and interpretation of sports data, thereby enhancing athletic performance and organizational efficiency. However, the widespread adoption of AI also presents challenges related to data privacy, algorithmic bias, ethical governance, financial accessibility, and the evolving role of human expertise in decision-making. The paper maintains that while AI should be embraced as a transformative tool in modern sports, its implementation must be guided by ethical standards, transparency, and human oversight to ensure fairness and inclusivity. It concluded that the future of sports lies in a balanced partnership between artificial intelligence and human judgment, where technological innovation complements rather than replaces the expertise of coaches, athletes, officials, and sports administrators. The paper provided recommendations for policymakers, sports organizations, and researchers to promote responsible AI adoption that supports sustainable development and competitive excellence in the global sports industry.
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