Enhancing Safety and Quality in College Sports Management Through Big Data and Artificial Intelligence (AI)

Abstract

The purpose of this study is to explore how artificial intelligence (AI) and big data can be used to solve the twin issues of athlete safety and sports event quality in a college sports environment. Furthermore, this study attempts to fill the literature vacuum regarding the application and effectiveness of artificial intelligence and big data in improving safety and quality in collegiate sports administration by investigating possible synergies between these elements and the implementation of developed technologies. This qualitative study used a sampling method to conduct in-depth interviews with 18 sports administrators and commentators. Using coding and classification methods, the data were evaluated thematically with a focus on artificial intelligence and big data applications. Research has found that artificial intelligence and big data play a key role in proactively reducing injuries, optimizing athlete performance and enabling data-driven decision-making. It also identifies barriers and opportunities for integrating these technologies, revealing their dynamic potential. This study provides new perspectives on the relationship between safety and quality and the application of artificial intelligence and big data in collegiate sports management. It also highlights the ways in which these technologies have transformative potential in sport. The findings have important implications for educational programs and policy development aimed at managing responsible technology integration and preparing future professionals in the field of sport management.