Assessing AI adoption in the sports industry from a consumer perspective

What is it about?

This paper looks at how and why sports consumers, or fans, might choose to use artificial intelligence (AI) tools in their everyday sports experiences. It focuses not on athletes or coaches, but on regular fans who follow sports by watching games, reading news, or talking with friends, referred to as "passive sports consumers". These consumers are a huge part of the sports audience, and their habits are increasingly shaped by digital technologies. The research is based on an extended version of the Technology Acceptance Model (TAM), a well-known theory that explains why people accept or reject new technologies. In this version, the key factors are how useful and how easy to use consumers think AI tools are, but it also looks at three additional elements: social influence (what friends, family, or communities think), personal innovativeness in IT (how open someone is to trying new technologies), and team identification (how strongly a fan feels connected to their team). To test these ideas, the authors surveyed 639 sports fans in the United States, aged 18–60, and analyzed the results with structural equation modeling. The study finds that Social influence and PIIT shape how consumers perceive benefits and ease of use. Interestingly, PIIT also has a direct effect on intention to use AI, meaning that fans who naturally like to try new technology are more likely to adopt AI regardless of other factors. Team identification has a more complex role: it makes fans see more benefits in AI, but it doesn’t make AI seem easier to use. It even slightly weakens the link between ease of use and intention to use AI, showing that some highly devoted fans might be skeptical of AI if they feel it interferes with traditional fan experiences. The study also discovers differences between age groups: younger fans (Gen Z) are most strongly driven by benefits, millennials (Gen Y) are influenced by both benefits and innovativeness, and Gen X is most influenced by innovativeness. Gender differences were tested but didn’t show significant variation. Overall, the study paints a detailed picture of how personal attitudes, social context, and emotional ties to teams all shape whether fans will embrace AI applications in their sports experiences.

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Photo by julien Tromeur on Unsplash

Photo by julien Tromeur on Unsplash

Why is it important?

This research matters because AI is no longer a distant idea - it is already changing how fans experience sports, from chatbots that answer questions to personalized highlight reels, prediction tools, and statistical insights. But sports organizations often struggle to understand how to introduce these technologies without alienating fans. The findings of this study offer clear guidance. First, AI tools must be both useful and easy to use. If they do not add real value or are too complicated, sports consumers will not adopt them. This is particularly important because fans vary widely in how comfortable they are with technology. Some are eager early adopters, while others are cautious or resistant. Sports organizations therefore need to design AI tools that balance advanced features with simplicity, offering trial opportunities for tech-savvy fans while ensuring intuitive design for less experienced users. Second, the role of social influence shows that AI adoption is not simply an individual decision. Fans often look to their communities, peers, or even favorite players to validate their choices. This means organizations should embed AI tools into supporter groups, fan clubs, and trusted community spaces. If influential figures or groups use AI tools, more fans will see them as worthwhile. Another key contribution is the recognition that emotional ties to teams play a double role. On one side, team identification can make AI more appealing if it enhances fans’ emotional connection, for example through personalized team-focused content or interactive features like virtual meet-and-greets with AI player avatars. On the other side, some fans fear that technology might dilute traditional experiences, like watching games with friends or collecting physical merchandise. Sports organizations need to carefully balance innovation with tradition, showing that AI can strengthen rather than replace emotional bonds. The generational findings also highlight that a “one-size-fits-all” approach doesn’t work: younger fans may want entertainment and personalization, millennials may respond to both benefits and novelty, and older fans may need to see AI as a serious analytical tool to be convinced. By tailoring strategies to these groups, organizations can broaden adoption. Beyond theory, this study also expands academic understanding by adding psychological and social factors into TAM, enriching how we study technology in consumer sports. In practice, the results help sports organizations design AI experiences that are not only technically functional but also socially accepted, emotionally meaningful, and inclusive of different types of fans. This matters because successful AI adoption can deepen engagement, increase loyalty, and open new revenue streams, ensuring that sports organizations stay relevant in a digital age while maintaining the unique fan culture that makes sports so powerful.