IBM's new US Open features use AI to analyze every serve, summarize match momentum, and chat with fans. The tech push signals IBM's strategy to showcase watsonx to enterprise clients.
IBM and the U.S. Tennis Association rolled out new AI-powered features for the 2026 U.S. Open, the latest in a multiyear push to use the tournament as a showcase for the company's watsonx platform.
The features – a Serve Quality metric that analyzes every serve across 254 singles matches, an enhanced Match Chat assistant, and a Key Moments summary tool – are designed to keep fans engaged whether they are at the Billie Jean King National Tennis Center or watching from home. Kameryn Stanhouse, IBM's vice president of sports and entertainment partnerships, said the company treats each Grand Slam as both a product launch and a client demonstration.
"What we do is not just serve the fan experience, but we're creating unique conversation pieces for our clients. They see how IBM technology makes all of this possible and inspire what you could do with us," Stanhouse told Fox Business.
The Serve Quality tool uses limb-tracking technology developed with IBM Bob and a stream of live data managed by IBM Confluent. The AI model was trained on historical white papers and research about serves, then analyzes 21 joint points on the body – from elbow to big toe – along with racket positioning and ball landing coordinates. It takes snapshots 50 times per second. Over the tournament, IBM expects to process 1.2 billion data points to generate the Serve Quality number.
The Key Moments feature builds on the existing Likelihood to Win metric. It pulls structured and unstructured data – match statistics, media coverage, social media sentiment, broadcast commentary – to explain why momentum shifted. Stanhouse said the pre-match projection considers factors like a new coach or a lingering injury.
Match Chat, powered by watsonx Orchestrate, acts as an interactive companion. It can answer questions about Serve Quality, explain match context, or help pronounce player names. Stanhouse described it as a collection of AI agents and purpose-built models trained for fast, accurate responses.
IBM's Alpha Score sits at 48 out of 100, a Mixed rating from AlphaScala's proprietary model. The score reflects the gap between the company's enterprise AI ambitions and the market's view of its growth trajectory. IBM has been using sports partnerships – including the U.S. Open, Wimbledon, and The Masters – to demonstrate how watsonx can handle real-time data at scale. The question for investors is whether that demonstration translates into enterprise contracts.
Stanhouse said her team's work creates "tangible output that people actually see." The U.S. Open draws about 1 million in-person attendees and 14 million digital viewers over two weeks. That audience gives IBM a live test bed for its AI tools, with the added benefit of a high-profile stage.
"Everybody says my team has the best job at IBM," she said. "Each tournament that we go to is not only a learning opportunity because we're constantly thinking about how we're going to evolve things for the next year, but it's such a pay-off to see everything come to life."
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