The current study was conducted to identify the impact of artificial intelligence on sports marketing (applications and limitations). This research is a sequential mixed-methods study (qualitative-quantitative). The participants in qualitative phase consisted of 15 sport management experts who were interviewed. In the quantitative section, the statistical population included members of the sports management academic community that was selected through random sampling approach. Kolmogorov-Smirnov test, confirmatory factor analysis, and path analysis were used in the quantitative part of the study. The structural equation method with partial least squares method was used to measure the validity of the model, and the research hypotheses. According to the results of the study, there are 8 effective factors of artificial intelligence applications in sports marketing, including predicting sales and prices of sports products/services, identifying revenue growth opportunities, automating sales processes of sports products/services, personalized recommendation systems through analyzing customer behavior of sports products/services, tracking satisfaction with sports products/services, and advertising. Additionally, there are 5 factors identified as limitations of artificial intelligence in sports marketing, including limited understanding of human elements, concerns about data privacy, costs, and technical issues. The findings can help sports marketers to better utilize artificial intelligence for better delivery and customer satisfaction of sports products and services.
