If an AI assistant cannot find your results, your sport barely exists to the next generation of fans. That is the uncomfortable reality facing federations and long-tail sports as AI in sports moves from experiment to everyday habit. The biggest leagues have years of clean, structured data feeding the tools fans now use to ask questions, while many smaller sports still keep their history in PDFs, spreadsheets and the memories of long-serving volunteers.
Interest is climbing fast. US searches for "ai in sports" have grown by about 178% over three years, according to DataForSEO search volume data from October 2026, and the conversation has moved well beyond analysts and front offices. The question for every federation is whether its sport will be part of the answers these systems give, or quietly missing from them.
AI Answers Only Cover What They Can Find
Search behaviour is shifting underneath everyone. A Pew Research Center study of 68,879 Google searches made by 900 US adults found that 18% of searches produced an AI summary. When one appeared, users clicked a traditional result in 8% of visits, compared with 15% when there was no summary. The summary is increasingly the destination, and it is assembled from sources the system can read and trust.
For a sport with thin or messy data, that is a real risk. A fan asking about last season's champions in a smaller sport gets a confident answer only if structured results exist somewhere to draw on. Where they do not, the answer is vague or simply wrong, and the sport loses a little visibility every time someone asks.
Federations Are Already Turning Archives Into Assets
Some federations are moving early. Ahead of Milan Cortina 2026, the International Luge Federation launched an AI assistant called LAIA, built on a database of more than 42,000 race results, with archives going back to 1950 for some formats. Its head of AI, Julian von Schleinitz, described it as "real added value for athletes, teams, media and fans."
Chess has gone further still. FIDE's partnership with Salesforce, announced in September 2026, introduces an AI agent that replaces manual rating processes with near real-time ratings across 204 national federations and 1.5 million rated players. Motor sport is heading the same way, with the FIA naming AWS its official AI and cloud partner in October and promising support that reaches "the grassroots clubs."
What these examples share is a starting point in organised data. Deloitte's 2026 sports industry outlook puts the question plainly: "Are critical datasets consolidated, governed, and trusted enough to support enterprisewide use cases?" For most long-tail sports the honest answer is not yet, and that is exactly where the work should begin.
The DSG Advantage: Structured Data for Every Level of Sport
- Coverage of more than 80 sports and thousands of competitions, well beyond the headline leagues
- Historical archives built over two decades, going back to the 1800s in some sports
- Pre-match, live and post-match data in consistent structures that AI tools can read
- Delivery through APIs with 99.99% uptime
Making Smaller Sports Visible in the AI Era
Many fans will meet a sport for the first time through an AI answer rather than a broadcast or a match programme. Federations that put their results, fixtures and history into structured, licensable form now will shape how their sport is described for years to come. Data Sports Group has spent two decades covering exactly that long tail, and we believe every sport deserves data good enough to tell its story properly.
