Today, teams, leagues, venues, and brands are using AI to understand fans, improve performance, and grow revenue. AI is affecting sports on three levels: the fan experience, team and league operations, and sports marketing. It also raises some ethical questions that future business leaders will need to consider.

The Fan Experience

If you watch televised or streamed sports today, you may already be interacting with several AI-driven tools without realizing it. Streaming platforms can deliver personalized content recommendations based on your demographics and watch history. Apps can show real-time statistics, recommended clips, and highlights chosen specifically for you. Social media algorithms constantly suggest content from teams and athletes you have engaged with in the past.

Industry analysts estimate that global sports generate around half a trillion dollars in revenue each year, according to Morgan Stanley, and a growing share of that comes from digital experiences. Younger fans, especially those under 35, are pushing this shift. They spend more time online, follow individual athletes as much as, if not more than, teams, and expect content that feels tailored to them. Surveys suggest that younger fans are more willing to spend money when the experience starts digital first rather than with traditional television. AI helps sports organizations deliver this kind of experience. 

Some leagues are testing features like customized stat feeds, alternate camera angles, and even player point-of-view shots using computer vision and sensor data. AI can track what fans click, how long they watch, and what they share with friends, then use that information to recommend similar content.

The stadium experience is changing too. So-called smart venues can use AI to adjust ticket prices in real time based on demand, weather, and the strength of the opposing team. Facial recognition systems can speed up entry or allow fans to pay for food without pulling out a wallet. Facial authentication technology is already in use at six Major League Baseball parks.

League Operations

AI is also reshaping how teams make decisions about players. In basketball, for example, the Golden State Warriors use a machine learning model that combines player statistics, physical measurements, and the coach’s preferred style of play. The system can estimate how many extra wins a player might add if he joins the team. When the Warriors traded for star forward Jimmy Butler, this model suggested that his passing, defense, and ability to get to the free-throw line would fit well with players already on the team. The team still relied on human judgment, such as scouting and personal experience, but AI provided an extra layer of evidence.

In American football, professional and college teams use AI to predict injury risk and to identify comparable players when they lose someone to the transfer portal or free agency. AI models can quickly scan thousands of players and clips to find those who move or play in similar ways. Some teams have even experimented with AI for in-game decision making. In minor league baseball, the Oakland Ballers let an AI app generate lineups and suggest pitching changes during a real game.

AI is spreading beyond professional sports. A youth soccer club in California uses Darkhorse AI and Beyond Pulse wearable technology in conjunction with video analysis, wearable sensors, and heart rate monitors to evaluate players based on performance and health data. Coaches can use this data to help players improve and to create highlight reels. Club leaders also use the data in conversations with parents about playing time. 

Sports Marketing

From a business perspective, AI can help teams and brands figure out who their fans are, what they want, and how to get them to spend more time and money with the sport. AI-driven marketing systems can analyze browsing histories, app usage, social media engagement, and purchase data to predict what each fan is likely to buy. They can help with targeting, deciding which fans should receive offers for premium tickets, which fans might respond to a discount, and which fans are most likely to subscribe to streaming packages.

Sponsorship deals also benefit from AI. Instead of only looking at broad demographic data like age and location, marketers can now target very specific segments such as “fans who watch women’s soccer highlights on mobile and buy team merchandise online.” AI-powered tools can then generate personalized ads that appear during those fans’ favorite content, increasing the value of sponsorships and improving the return on investment for advertisers.

AI also plays a role in fantasy sports, esports, and sports betting. Predictive models can suggest which players to pick, estimate win probabilities, and push real-time offers that encourage fans to place more bets or enter more contests. This can significantly increase revenue for betting companies and leagues that partner with them.

Ethics Risks

AI-driven marketing depends on collecting and monetizing huge amounts of fan data. Sports organizations increasingly share data with technology vendors, sponsors, and advertising platforms. This ecosystem allows very precise targeting, but it also creates concerns about how fan data is collected, stored, and sold, and whether fans truly understand how their information is being used.

On the surface, personalized recommendations feel helpful and convenient. Behind the scenes, however, AI systems are designed to maximize engagement and revenue, not necessarily to protect fan wellbeing. For example, if a fan usually watches highlight clips from one team or one type of sport, AI systems will keep showing more of the same. Over time, the fan might see less content about other teams, leagues, or sports. The fan’s world of sports becomes narrower and narrower. 

There are also concerns about misinformation. Generative AI systems can create realistic sports stories, statistics, and highlight descriptions that look authentic but are not accurate. In a fast-moving sports news environment, false information can spread before it is corrected, which can damage reputations and mislead fans.

Younger fans are more vulnerable to persuasive technology and less experienced at recognizing when they are being targeted. AI-assisted marketing uses psychological triggers such as rewards, streaks, and limited-time offers to keep users engaged. Some governments are already responding. For example, in Australia there are rules that limit when gambling ads can appear around live sports broadcasts, especially during hours when children are likely to be watching. Other regions, such as the European Union, have broader AI rules that make certain uses of AI, including biometric surveillance in stadiums, subject to extra oversight. 

Sports executives, technology companies, regulators, and educators will need to decide how far personalization and monetization should go, especially when the audience includes children and other vulnerable groups.

In the Classroom

This article can be used to discuss ethics (Chapter 2: Business Ethics and Social Responsibility) and buying behavior (Chapter 11: Customer-Driven Marketing).

Discussion Questions

  1. In what ways is AI changing how fans watch and interact with sports, both at home and in the stadium?

  2. How do teams like the Golden State Warriors and youth clubs like the Mustang Soccer League use AI to make decisions about players? What are the advantages and potential concerns of these approaches?

  3. Describe some of the ethical considerations when AI is used in sports marketing and revenue generation, and identify additional ethical concerns that might arise that are not discussed in the article.

This article was developed with the support of Kelsey Reddick for and under the direction of O.C. Ferrell, Linda Ferrell, and Geoff Hirt.

Sources

Cesar Medina, “How AI Is Driving the Digital Revolution in Sports [Podcast],” Morgan Stanley: Thoughts on the Market, August 11, 2025, https://www.morganstanley.com/insights/podcasts/thoughts-on-the-market/sports-industry-technology-adoption-cesar-medina

Emily Sanderson, "Reds Launch New Facial Authentication System for Fans Entering Ballpark," WLWT, August 13, 2024, https://www.wlwt.com/article/reds-new-facial-recognition-system-go-ahead-entry-ballpark/61866328

Hans Westerbeek, “Algorithmic Fandom: How Generative AI Is Reshaping Sports Marketing, Fan Engagement, and the Integrity of Sport,” Frontiers in Sports and Active Living, May 8, 2025;7:1597444. doi: 10.3389/fspor.2025.1597444.

Ron Kroichick, "From Warriors' Jimmy Butler Trade to Your Kid's Playing Time, How AI Is Changing Sports," San Francisco Chronicle, November 13, 2025, https://www.sfchronicle.com/sports/article/ai-artificial-intelligence-data-sports-21125263.php