“AI Calling the Shots and Making the Calls” — FIFA Turns the World Cup Into a Full-Scale Testbed for Sports AI After Years of Technological Buildout

FIFA to Deploy Broad Range of AI-Based Systems at the World Cup in Partnership With Lenovo
AI Use in Sports Continues to Expand From Tactical Planning to Training and Recruitment
Stadium Operations Also Moving Toward Automation as Fan Experiences Become Faster and More Seamless

Fédération Internationale de Football Association (FIFA) is set to comprehensively integrate artificial intelligence (AI) technologies into the 2026 FIFA World Cup, scheduled to begin in June. The initiative spans a wide range of applications, including tactical analysis, officiating, player condition management, and stadium security operations. Market observers increasingly view the tournament as a critical proving ground for sports AI systems that have undergone years of gradual development and refinement.

AI-Driven World Cup Infrastructure

According to a report by the South China Morning Post (SCMP) on the 18th local time, every national team participating in the 2026 FIFA World Cup will be granted access to “Football AI Pro,” a system developed by FIFA’s official technology partner Lenovo. The platform utilizes a football-specialized large language model trained on FIFA’s vast proprietary database and is capable of processing more than 2,000 football-related metrics in real time, including pressing intensity, player movement, tactical formations, and offensive-defensive transitions during matches. On-site tactical analysts will use the system to instantly compare and analyze opposing play patterns, while coaching staffs will be able to forecast how tactical adjustments may impact opponents during live matches. Players will also receive individualized post-match performance reports immediately after games.

The tournament will also feature the implementation of the Semi-Automated Offside Technology (SAOT) system. Dozens of specialized cameras installed throughout stadiums track the ball and 29 body points of each player multiple times per second, generating AI-based 3D avatars in real time. The AI system analyzes the data and immediately alerts the Video Operation Room (VOR) when an offside situation occurs. Decisions that previously required several minutes can now be completed within seconds, allowing accurate rulings without significantly disrupting match flow. In addition, inertial measurement unit (IMU) sensors embedded inside the official match ball precisely measure ball position and point of contact before transmitting the information to the AI system. The data is used not only for offside rulings but also for controversial situations involving goal-line decisions and handball infractions.

AI is also being actively integrated into match analysis. FIFA’s “Enhanced Football Intelligence” system instantly displays advanced metrics such as sprint speed, pass completion probability, and pressing intensity on live broadcasts, helping viewers better understand tactical dynamics during matches. Tournament organizers also plan to monitor wearable device signals from spectators, crowd movement flows, terrorism-related security risks, and players’ vital health data in real time through “Digital Twin” systems — virtual replicas that mirror the operations of actual stadiums.

AI Applications Across the Sports Industry

AI systems in sports have steadily evolved over the past several years. One representative example is “TacticAI,” jointly developed by Google DeepMind and English Premier League club Liverpool FC. First unveiled in the academic journal Nature Communications in 2024, TacticAI was trained on roughly 7,000 corner-kick scenarios provided by Liverpool and analyzes player positioning, movement, and physical attributes to predict which player is most likely to touch the ball first, the probability of a shot attempt, and the optimal player arrangement. In blind evaluations conducted with Liverpool coaches and data analysts, nearly 90% of the AI-generated tactical recommendations were assessed as equal to or superior to strategies proposed by human coaches.

Such AI- and data-driven training systems are rapidly expanding beyond experimental stages into practical deployment. Premier League clubs use GPS tracking systems developed by British sports data company STATSports to analyze player movement distances, speed, and activity patterns, utilizing the data for playing-time management and recovery planning. Luton Town of the English Championship uses Australian sports technology company Catapult’s GPS and video analysis systems to manage player workload and recovery conditions. Major League Soccer (MLS) club Chicago Fire adjusts training intensity using real-time training data gathered through Spanish sports tech company RealTrack Systems’ “WIMU Pro” platform, while Portugal’s Primeira Liga side Vitória Guimarães also employs the same system to operate customized training programs.

AI is increasingly being used in psychological analysis and player recruitment as well. Premier League club Brighton analyzes players’ facial expressions and body language from match footage to quantify emotional control capabilities and responses under pressure. Sevilla FC of Spain’s La Liga has partnered with global IT company IBM to build an AI scouting system called “Scout Advisor.” The platform compiles global match data, reports, and video footage to automatically identify player candidates that fit the club’s tactical framework. The AI generates summary reports covering player style, work rate, and passing tendencies, after which coaching staffs make final recruitment decisions.

AI Expanding Into Ecosystem Operations and Management

AI is also reshaping the broader operational structure of the sports industry and the fan experience itself. Several teams in the National Basketball Association (NBA) and National Hockey League (NHL) already operate personalized highlight video and content recommendation services based on fan consumption patterns and viewing data. Industry observers believe such systems will eventually evolve into fully personalized live broadcasts reflecting preferred teams, players, and viewing histories.

Fan question-and-answer systems utilizing large language models (LLMs) are also becoming more common. AI systems automatically interpret complex rulebooks, match regulations, and disciplinary guidelines before responding to fan inquiries in real time. AI is also widely used for global market expansion strategies. European football leagues and North American sports franchises use generative AI to automatically produce marketing content tailored to local cultures while strengthening overseas social media operations through real-time translation capabilities. Some global sports brands have also adopted generative AI advertising systems to deliver country-specific marketing campaigns.

Stadium operations and organizational management are increasingly moving toward automation as well. Certain stadiums in the United States and Europe have introduced “smart stadium” systems in which AI aggregates real-time congestion levels, traffic conditions, and crowd movement data to guide spectators along optimized routes. The systems disperse pedestrian traffic to reduce bottlenecks at specific exits after matches while also providing integrated parking and public transportation information. On the operational side, AI analyzes financial, attendance, and revenue data to generate profit forecasts and optimize ticket pricing strategies. AI has effectively established itself as core infrastructure underpinning the entire sports ecosystem. The upcoming World Cup is expected to serve as a large-scale test of the practical effectiveness of these systems.