Unusual Ways The Sporting World Is Using AI
The sporting landscape in 2025 has become a hotbed for unconventional applications of artificial intelligence—far beyond performance stats and analytics. Some of these uses are quietly reshaping the business side of sport, reaching into areas one barely considers connected to AI.
One of the more curious intersections comes via fan engagement: Telegram-based communities and channels, familiar to many as messaging forums, are now doubling as casual betting networks, using gambling bots to facilitate everything from quick poll-driven wagers to slot-style games sent via chat. Telegram casinos—essentially bots that let users join promotions, spin games, or place bets without leaving the app—are being explored by clubs aiming to stay ahead of fan habits, but they also raise new questions around regulation and brand alignment.
Not far from that is AI’s entry into fan safety and logistics in stadiums. Some venues now deploy real-time crowd-monitoring AI that reads camera streams to predict bottlenecks, alert staff to possible flashpoints, or reroute flows before they become issues. Tech teams have noticed fewer stewards needed on match days, while concession managers rely on predictive dashboards to know when queue pressure will peak—so staff and drink stock can be shifted in time.
Meanwhile, kit design is getting a digital makeover. Brands are feeding thousands of images—including fan-made designs, retro jerseys, and social sketches—into generative AIs to spark fresh concepts. A few clubs have run promotional stunts where supporters vote on AI proposals. It’s less about replacing a creative director, more about crowd-sourced inspiration that doesn’t cost much and generates buzz.
Broadcasting, too, has been nudged into novelty. Imagine live commentary generated on-device in multiple languages during reserve-youth matches—AI tools trained on game footage and league archives produce context-aware commentary instantly. It’s not replacing iconic commentators, but it expands multilingual access at minimal cost, particularly for lower-tier games that attract little international exposure.
Then there’s corporate comms and sponsorships. AI tools now predict the exposure value of logos on kit fronts, broadcast overlays, or stadium billboards, estimating social media traction, camera dwell time, and even recall rates. Brands appreciate this precise modelling—it moves conversations away from gut instinct to data-informed proposals that justify sponsorship fees.
In the training ground, AI gets quietly advanced. Some clubs are building virtual opponents using data from video libraries—digital twins that simulate rival players’ patterns, habits, and decision-making tendencies. Players train against these AI versions to anticipate opposition traits. Coaches say it’s like shadow boxing in slow motion—scalable, repeatable, and arguably safer on tight schedules. It doesn’t replace team drills, but it gives a realistic edge without extra boots on the pitch.
Even behind the scenes, sports business functions are experimenting. AI is streamlining club accounting by sorting invoices from stadium suppliers or hospitality deals, flagging anomalies, and accelerating reimbursements. Legal teams use natural-language processing to scan contracts—spotting renewal deadlines or missing clauses that might otherwise go unnoticed. Small improvements, but combined, they shave days off response times across operations.
Taken together, these use cases reflect sport’s appetite for AI that stretches beyond performance. It touches sponsorship, training, safety, fan engagement, operations, and media. Nor does it follow a neat script. It’s the kind of creative chaos that happens when clubs and brands experiment to figure out what works. At its best, it unlocks smarter workflows, deeper engagement, and more agile business models—so long as governing bodies keep pace with the innovation. The next few years will likely decide which of these experiments stick and which fade out. What is certain is that sport’s relationship with AI will not return to the margins—it is now central to how the industry thinks about growth.
