ARTIFICIAL INTELLIGENCE ADOPTION AND ADMINISTRATIVE DECISION-MAKING IN UNIVERSITY SPORTS MANAGEMENT IN RIVERS STATE, NIGERIA

Abstract

This study found that AI adoption significantly predicted administrative decision-making and sports management efficiency among university sports administrators in Rivers State, Nigeria. The study adopted a cross-sectional correlational research design. The study involved sports administrators from the University of Port Harcourt, Rivers State University, Ignatius Ajuru University of Education, and Federal University of Environment and Technology. The estimated population was 160 sports administrators, from which a sample of 114 respondents was selected using the Taro Yamane formula. Eighty-nine completed questionnaires were retrieved, representing a 78% return rate. Data were collected using a structured questionnaire measuring AI adoption, administrative decision-making, and sports management efficiency. Descriptive statistics, including mean and standard deviation, were used to answer the research questions, while simple linear regression was employed to test the hypotheses at the 0.05 significance level. The findings showed that AI adoption had a strong perceived influence on administrative decision-making (grand mean = 3.03). Regression analysis further indicated that AI adoption significantly predicted administrative decision-making, R = .614, R² = .377, β = .614, F(1, 87) = 52.61, p < .001. AI adoption also demonstrated a strong perceived influence on sports management efficiency (grand mean = 3.06) and significantly predicted management efficiency, R = .638, R² = .407, β = .638, F(1, 87) = 59.72, p < .001. The study concludes that AI adoption represents a promising mechanism for improving decision quality and operational efficiency in university sports management. The study recommended, among other things, that university sports management adopt AI-supported administrative systems for planning, scheduling, information management, resource allocation, and monitoring of sporting programs.