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The 2026 FIFA World Cup has recently concluded, and its most telling numbers were commercial. Nearly 7 million spectators attended 104 matches, setting a cumulative attendance record, and a Financial Times estimate put FIFA’s revenue from the tournament itself at approximately $9 billion. Much of that increase came not from what happened on the field, but from how the tournament was monetized through premium hospitality, dynamic pricing and FIFA’s own resale platform.
This reflects a broader shift. Sport is no longer judged solely by trophies or attendance; it is increasingly valued as an investable business, with tens of billions of dollars in private capital being assembled and deployed across teams, leagues, media rights and adjacent sports assets.
In Saudi Arabia, the transition from state-backed funding to institutional ownership continues, with Kingdom Holding Company agreeing to acquire a 70 percent stake in Al-Hilal at an enterprise value of SR1.4 billion ($373.3 million).
As sport becomes a more sophisticated commercial ecosystem, AI is rapidly moving to the forefront of industry discussions. Most conversations, however, focus on its impact on athletic performance, from predictive scouting and injury prevention to tactical analysis and officiating. Those applications are valuable, but they are not where AI will create the greatest economic returns. Its real opportunity lies further along the value chain, where fan engagement is transformed into sustainable monetization.
Today, three structural barriers continue to limit that potential.
First, most sports organizations lack a unified view of their fans. Data remains fragmented across ticketing, streaming, CRM, social media and merchandise platforms, making it difficult to understand fan lifetime value or deliver truly personalized experiences. Marketing remains campaign-driven rather than behavior-driven, while high-value supporters are often identified too late.
Second, audience measurement remains inconsistent. Different markets use different methodologies, currencies and reporting standards, making it difficult for rights holders to demonstrate the true value of their audiences. That weakens negotiations around media rights and sponsorships.
Third, commercial operations have not kept pace with growing fan expectations. Many organizations remain focused on delivering the next live event, while content creation, sponsorship activation and digital engagement continue to rely on manual processes that are difficult to scale.
AI changes this because, for the first time, it makes demand-side operations scalable. Rather than marketing to broad audience segments, organizations can engage millions of fans as individuals. Instead of producing one campaign, they can generate and adapt content across languages, formats and platforms at commercially viable cost. AI can also reconcile fragmented audience data into a more credible commercial proposition while helping rights holders forecast demand, optimize pricing and maximize the value of inventory before a season even begins.
None of this comes from buying a dozen disconnected AI tools. Capturing this value requires three layers working together: a governed data foundation that creates a single fan view and common metrics; intelligence services covering segmentation, lifetime value, retention, pricing and commercial-value measurement; and an activation layer that embeds decisions into ticketing, CRM, media and partner systems.
AI agents should operate within clear human approval and testing controls. Without activation, insight never reaches the point of decision. Technology is only one part of the equation; execution and organizational alignment are equally critical.
Built this way, fan engagement and monetization become a self-reinforcing flywheel. Richer first-party data increases the value of sponsorship and media rights. Higher attendance and stronger fan loyalty improve matchday revenues, hospitality and merchandising. Those returns can then be reinvested into squads, academies, venues and fan experiences, creating deeper engagement and even greater commercial value over time.
The challenge is no longer access to AI but the ability to combine sports expertise, commercial strategy and AI capabilities into one coherent model. That combination remains rare, yet it will increasingly determine which organizations outperform.
AI will undoubtedly change how athletes train and how fans experience sport. Its far greater impact, however, will be commercial. Championships will continue to be won on the pitch, but the next generation of competitive advantage will be built behind the scenes — by those who understand how AI can turn fan passion into long-term enterprise value.
- Shahid Khan is a senior partner and global head of media, entertainment, sports and culture at Arthur D. Little.