AI Applications in Sports: Evaluating Adoption Among LU Student-Athletes

Artificial Intelligence (AI) is revolutionizing the sports industry, offering advanced tools for performance analytics, training optimization, and injury prevention. While AI-driven technologies such as video analysis, biometric wearables, and predictive modeling have been widely adopted in professional sports, their integration within collegiate athletics remains underexplored (Wang et al., 2024). Figure 1 illustrates AI’s role in processing data streams, while Figures 2 and 3 highlight AI-driven training, injury prediction, real-time performance forecast and decision-making frameworks. Despite increasing interest in AI applications in sports, limited research investigates how these tools are utilized in student-athlete training and competition. Understanding AI adoption among collegiate athletes is crucial for optimizing performance and ensuring equitable access to emerging technologies. Existing research primarily focuses on professional athletes, leaving a critical gap in AI adoption at the collegiate level. While some NCAA programs have implemented AI for player tracking and injury prevention, adoption varies significantly across institutions and sports disciplines (IBM Sports Analytics Report, 2023). This study aims to address this gap by evaluating AI adoption among Liberty University (LU) student-athletes, examining factors influencing accessibility, implementation, and perceived usefulness. By assessing AI application levels, this research bridges the divide between professional and collegiate AI integration, providing LU Athletics with data-driven insights for strategic decision-making. The study employs a survey-based primary data collection approach, gathering quantitative data from LU student-athletes to assess AI adoption trends, barriers, and facilitators. The research will analyze athlete perceptions of AI’s accessibility and effectiveness, contributing to a broader understanding of AI’s role in collegiate athletics. Findings will inform LU’s approach to AI integration, supporting the development of evidence-based strategies to enhance training efficiency, injury prevention, and athletic performance. This study benefits LU Athletics and contributes to the growing discourse on AI's impact on collegiate sports, guiding future research on technology adoption in athlete development.