Algorithmic fandom: how generative AI is reshaping sports marketing, fan engagement, and the integrity of sport - Westerbeek, Hans (Frontiers in Sports and Active Living, 2025)
Generative artificial intelligence (AI) is rapidly transforming the landscape of sports marketing by enabling hyper-personalised fan engagement, real-time content delivery, and data-driven commercial strategies. Leveraging technologies such as machine learning, predictive analytics, and automated content generation, sports organisations are increasingly able to tailor fan experiences, anticipate behaviour, and optimise revenue models. While these advancements offer significant opportunities for enhancing interactivity and commercial growth, they also introduce complex ethical, psychological, and regulatory challenges. This paper critically examines the dual nature of generative AI in sports marketing, with a particular focus on consumer autonomy, data monetisation, and the influence of AI-driven personalisation on fan behaviour. Using narrative literature review approach, the paper draws on emerging research, industry cases, and interdisciplinary literature, and explores how algorithmic recommendation systems can manipulate fan decisions, reinforce digital echo chambers, and marginalise underrepresented sports. Special attention is given to the impact of AI on children and adolescents, who are particularly vulnerable to targeted content, gamification, and AI-curated betting environments. The integration of AI in gambling platforms and the commercialisation of fan data raise significant concerns around privacy, consent, and long-term wellbeing. The paper concludes by offering some implementation guidance for sport ecosystem stakeholders. It also outlines a future research agenda that calls for empirical investigations into the long-term effects of AI on fan behaviour, the development of regulatory frameworks to safeguard consumer rights, and interdisciplinary collaboration to design ethical AI systems. By identifying these critical issues, the paper aims to support a more inclusive, transparent, and integrity-focused application of AI in sport.