AI in Sport: What Nike, adidas, and Under Armour Are Actually Building in Their R&D Labs

Nike, adidas, Under Armour, Puma — the major sport brands have figured out that AI isn’t a communications gadget to be bolted onto press releases. It’s a foundational tool that touches product design, performance analysis, and the customer relationship.

What’s happening in their R&D labs right now is worth examining concretely.

Computer-aided design goes to the next level

Shoe manufacturing has always involved back-and-forth between physical prototype and field testing. Generative AI changes the dynamic: designers can now simulate thousands of sole, upper, and cushioning configurations virtually, before building a single physical prototype.

Nike has invested heavily in this type of workflow — the FlyLeather project and several other lines were developed with optimization algorithms. adidas uses similar tools within its Futurecraft division. The result is shorter development cycles and the ability to test more ambitious hypotheses without the cost of a full physical prototype.

Personalizing performance

Beyond design, AI allows brands to offer performance personalization at a scale previously reserved for professional teams.

Under Armour has developed running analysis applications that use machine learning to deliver personalized training recommendations. Nike offers gait analysis via its apps to guide customers toward the right shoe model. The promise is clear: your equipment knows you and adapts to you — not the other way around.

AI in marketing and trend forecasting

Less visible but equally significant: brands are using AI to anticipate color, silhouette, and category trends ahead of the market. By analyzing millions of signals — social posts, sales data, browse behavior — they can direct production decisions with increasing precision.

That’s a significant competitive advantage in an industry where a bad color or silhouette bet can lead to expensive unsold inventory.

What it doesn’t replace

The best running shoes in the world are worthless if they’re not tested and refined by real athletes on real terrain. AI accelerates and improves the process — it doesn’t replace human iteration or the expertise of senior designers.

The brands succeeding in this transition are the ones treating AI as a human-talent amplifier, not a substitute. The algorithm race doesn’t win in the long run if the human team behind those tools isn’t up to the task.