This research was conducted with the aim of presenting a model for the development of sports tourism based on artificial intelligence. Given the novelty of the subject and the lack of previous conceptual frameworks, this research was developed as a fundamental type with practical capabilities. The research method used was the grounded theory approach with the Glaser strategy. This method was selected due to its exploratory nature and the need to generate theory from data. The statistical population included university professors, experts in the sports tourism industry, managers, government officials, and related entrepreneurs who were selected through purposive sampling. Data were collected and analyzed through 17 semi-structured interviews (including 7 key questions) until theoretical saturation was achieved. The validity of the research was ensured by the member review method and reliability by the research audit strategy (including researcher sensitivity and methodological coherence), and data analysis was performed with Max Quda software. Qualitative data analysis led to the identification of a central model that explains the development of AI-based sports tourism around three general categories: analytical functions (including analysis, efficiency accuracy, and financial advantage), special advantages of AI (including acceleration, efficiency, facilitation, and intelligence), and ancillary services of AI (including special services, technology development, and value-added). The findings indicate that successful development requires the integration of AI into analytical processes for optimal decision-making, the exploitation of operational advantages to enhance the tourist experience, and the creation of added value through technological innovations. This model provides a comprehensive framework for policymakers to guide investment towards the sustainability and competitiveness of the sports tourism industry.