Foresight in Sports Businesses: Exploring Emerging Scenarios Based on AI-Language Models and Financial Management Strategies

Purpose: The study explores the application of AI language models in scenario planning and financial management strategies for sports businesses.Methodology: This research utilizes a comprehensive scenario planning approach, guided by the Shell Scenario Method, which includes five key stages: (1) current and future perception assessment, (2) identification of driving forces, (3) visualization of future headlines and scenario elements, (4) analysis of scenario implications, and (5) formulation of strategic options. AI language models such as GPT-4 and BERT replaced traditional human stakeholders, generating detailed insights and scenario narratives based on data analysis.Findings: The findings indicate that AI language models significantly enhance the efficiency and accuracy of scenario planning in sports businesses. By analyzing large datasets, these models predict emerging trends and potential disruptions in fan behavior, technological adoption, and revenue generation. The study presents four future scenarios for the sports industry: AI-powered innovation, sustainability focus, consumer-centric tech, and traditional resilience. These scenarios provide practical insights for organizations to anticipate changes and prepare strategic responses for the next decade.Originality: The originality of this study lies in replacing human expertise with AI language models for scenario planning, offering a more efficient and data-driven approach to forecasting. Furthermore, the unique scenarios developed provide valuable foresight for sports organizations to align their strategies with future industry dynamics, particularly in adapting to technological advancements and shifting consumer demands.