But technology is rapidly making inroads into every aspect of the sports industry and business. According to estimates by the research firm Grand View Research, the market for AI-based solutions in sports has already reached $10.6 billion and could grow to nearly $50 billion by 2033. Algorithms are playing an increasingly active role in scouting players, preventing injuries, preparing teams, organizing broadcasts, and managing the sports business.
The company’s experts believe that the impact of AI on sports could be comparable to the revolution once brought about by television and the internet. So what are the main trends and areas of AI application in sports?
$50 billion by 2033: how a new market is taking shape
Just a few years ago, artificial intelligence in sports was associated primarily with match statistics. Today, we are talking about the formation of a new segment of the digital economy.
Major sports organizations, professional clubs, leagues, and media companies are investing in data analytics, computer vision, and machine learning technologies. The focus is not only on sports results but also on commercial effectiveness.
For club owners and investors, data is gradually becoming an asset on par with television rights, sponsorship contracts, or ticket sales revenue.
Soccer clubs were among the first to actively leverage the capabilities of artificial intelligence.
Modern platforms are capable of analyzing millions of game sequences and hundreds of metrics for each player: speed, movement intensity, passing quality, success in one-on-one situations, and pressing effectiveness.
Companies such as Stats Perform, Hudl, and Second Spectrum already provide analytical solutions to clubs in leading European leagues, the NBA, and other professional leagues.
Whereas the decision to sign a player used to depend largely on a scout’s opinion, today sports directors are increasingly relying on predictive algorithms. Artificial intelligence helps assess not only an athlete’s current level but also the likelihood of their future progress, their ability to adapt to a new team, and their risk of injury.
AI helps avoid multimillion-dollar losses
Injury prediction is considered one of the most promising areas.
Machine learning-based systems analyze athletes’ workload in near real time. Sensors record speed, acceleration, changes in direction, heart rate, and other metrics.
Based on this data, algorithms can detect signs of overexertion even before the first symptoms appear.
For clubs, this has direct financial implications. Losing a star player can result not only in on-field problems but also in multimillion-dollar losses due to a decline in performance, marketing appeal, and the player’s transfer value.
FIFA is betting on artificial intelligence
One of the most notable examples of AI implementation is the semi-automated offside detection system that FIFA uses at major international tournaments. The system was first introduced at the 2022 World Cup in Qatar.
The technology combines computer vision, artificial intelligence, and a network of specialized cameras capable of tracking dozens of parameters regarding the positions of players and the ball in real time. This significantly speeds up decision-making by referees and reduces the likelihood of errors.
In fact, the world’s largest soccer organization has become one of the driving forces behind the adoption of artificial intelligence technologies in professional sports.
Even earlier—at the 2014 World Cup in Brazil—FIFA began using Goal-Line Technology to automatically determine whether a goal had been scored.
To ensure these systems function during broadcasts of World Cup-level soccer matches, 45–50 different cameras are used, including those with ultra-slow-motion capabilities, which transmit 360-degree footage or create 3D avatars of players. All of this is a great help to referees and viewers.
A New Era for Sports Broadcasting
AI is changing more than just what happens on the field.
Television companies and digital platforms are increasingly using algorithms to automatically create video highlights, generate statistics, and personalize content.
Viewers get the opportunity to see exactly the moments and data that match their interests. For media companies, this means new monetization opportunities and more effective engagement with their audience.
As a result, sports data is becoming a standalone source of revenue, rather than just a supplement to broadcasts.
Who Will Profit from Sports AI
According to Goldman Sachs, investment in artificial intelligence infrastructure—data centers, servers, and semiconductors—has already reached approximately $400 billion annually and continues to grow.
Although these investments span the entire digital economy, the sports industry is becoming one of the fastest-growing areas for the application of new technologies.
Just as television once transformed the financial model of sports and the internet opened up access to a global audience of fans, artificial intelligence has the potential to transform the very system of sports business management.
This is not just about more accurate match analysis or talent scouting. At stake are increased productivity, reduced costs, new revenue streams, and enhanced competitive advantages for clubs and leagues.
For the sports industry, the question is no longer whether artificial intelligence will come to the stadiums. It has already become part of the game. The only question is who will be able to use it faster and more effectively than their competitors.
