As we look back on 2025, one thing is clear: artificial intelligence and data are no longer experimental tools sitting at the edges of organizations. They have moved decisively into the core of how businesses operate, compete, and create value. The pace of adoption tells the story. By the end of 2025, roughly one in six people worldwide had used generative AI tools, according to Microsoft’s AI Diffusion Report. In enterprises, momentum was even stronger, with nearly 70% of global organizations deploying generative AI in at least one business function by mid-year. What began as isolated pilots has rapidly evolved into embedded capabilities affecting decision-making, customer engagement, and operational efficiency.

In sport, data and AI are primarily associated with on-field performance: player analytics, tactical modelling and injury prevention. Technology has expanded the boundaries of athletic achievement, enabling athletes to push beyond previous limits. So why aren’t more sports organisations applying the same thinking to the business of sport? Sport is an intensely competitive entertainment industry where marginal gains in areas such as fan engagement, content, operations and commercial decision-making can matter as much as results.

The technology is real but immature. The trajectory is clear but the timeline is not. Most organizations deploying long-running AI in 2026 will learn expensive lessons. A few will gain genuine advantages. The difference will come down to three things: where they deploy, how they govern, and whether they understand what "autonomous" actually means in practice.

In late 2025, a technique with the absurd name "Ralph Wiggum" went viral among practitioners. The name comes from a Simpsons character—deliberately silly, because the core idea is almost embarrassingly simple.