AI isn’t new — but sports needs a smarter playbook
From front office experimentation to direct partnerships with tech firms, it feels impossible to keep up with the latest on AI. But before hitting the panic button, sports organizations should stop and realize they’re not as behind as the headlines might suggest.
For most sports organizations, AI isn’t new at all. In fact, it’s already embedded in the systems they rely on every day.
A CRM’s churn prediction for season-ticket renewals? That’s AI.
An email platform’s send-time optimization for fan engagement? Also AI.
A demand-forecasting or dynamic pricing engine? Again, AI.
Even common sponsorship valuation, fan segmentation and foot-traffic tracking tools have quietly built their businesses around structured automation for years. They just haven’t used “AI” as a marketing hook.
In contrast, this new tsunami of AI attention has largely focused on generative AI, and more specifically around large language models (LLMs) like ChatGPT, Claude and Copilot. These tools can be great at producing content and summarizing information, but they’ve also created an expectation that teams must build, train and fine-tune their own custom agents and GPTs to stay ahead.
A handful of forward-thinking sports organizations have already started piloting enterprise-wide customized systems, sometimes in partnership with........
© Sports Business Journal
