On Friday September 12, the Columbia–Dream Sports AI Innovation Center, hosted the second annual Sports AI Symposium, convening leading researchers, industry leaders, and innovators to explore how AI is transforming the way fans engage, how organizations make strategic decisions, and how technology is reshaping competition and performance across sports. it was sponsored by Dream Sports, India’s foremost sports technology company. Our colleague Karthik Iyer was on site and gave us a sumamry of the days learnings…
PANEL A: Keynote: Priya Narasimhan, Professor of Electrical & Computer Engineering, Carnegie Mellon University
- Build to use: Bridging the gap between theoretical invention and real-world impact. The true value of research is realized when it is implemented and used in practice, rather than just read in a paper. Technology is a tool for solving real problems, prioritizing utility and tangible outcomes over purely theoretical contributions.
- Fan Experience: A tailored approach, recognizing that a one-size-fits-all model is ineffective. For instance, an international fan’s needs are different from a local fan’s, and the technology should reflect that. Commemorative tickets is a prime example of turning transactional data into a sentimental, long-term asset for the fan. AR Portals further showcase how technology can create immersive, virtual experiences that transcend physical location. A move from passive consumption to active, personalized engagement. The focus is on creating emotional connections and memorable moments, which builds brand loyalty far more effectively than basic content delivery.
- It’s still a business: A pragmatic checklist for anyone in sports technology: market, business plan, cost of goods analysis, and revenue. This shows that technical innovation must be paired with sound business principles to be successful. A reminder that a great idea isn’t enough; you need a viable business model to scale and sustain a product.
- AI replica of coaches? A future direction in sport? The focus remains on applying AI to solve specific, high-value problems in sports, such as performance analysis or coaching accessibility. A provocative idea that could revolutionize training and strategy.
——————————————————————————————————————————-
PANEL B: From Insight to Impact: AI’s Role in Reimagining the Fan Experience & the Business of Sports.
(Mark Floriani, CEO & Co-Founder, FloSports Julie Souza, Global Head of Sports, AWS; Saj Cherian, Chief of Staff, Fanatics Head of Fanatics Ventures; Shripal Shah, Chief Digital Officer, Next League)
A tension between the ease of building new tech and the strategic challenges of its implementation.
- Race to the Bottom? Question the economics of the vendor ecosystem. The ease of building new sports tech could lead to a ‘race to the bottom’ for vendors. The democratization of content is made possible by a reduction in costs. This benefits underserved sports, which can now afford the technology needed for high-quality broadcasts and fan engagement that was once out of reach.
- Choose your own adventure: What are we trying to solve for with the data that we have? A warning against chasing fads and emphasis that the in-game experience itself is not broken. Emphasize strategic intent over technological capability. With the overwhelming volume of data available, the true challenge isn’t collecting it but rather formulating the right questions to extract meaningful insights.
The most successful AI applications will be those that create a seamless loop between engagement, insight, and commerce, turning passive viewers into active participants and customers.
——————————————————————————————————————————-
PANEL C: AI as a Competitive Edge: MLS’s Vision for an Intelligent Sport
John Nicastro, Chief Technology Officer, MLS
- AI not as a gimmick: MLS views AI as a tool to expand its reach in every aspect of the business, from fan engagement to commercial operations. The goal of ‘seamlessness’ suggests that MLS wants technology to be so integrated into the fan experience that it becomes invisible. The technology should enhance the sport and the experience, not distract from it. This is a common theme among leading tech companies – the best user experience is often one where the user isn’t even aware of the underlying technology.
- His specific point, ‘immersed in the action in the stadium, not on your mobile phone,’ signals a move away from just building mobile apps to creating deeply integrated, on-site experiences. This could involve using AI for things like real-time in-stadium stats displays, personalized concessions, or enhanced security, all aimed at improving the actual physical event rather than pulling fans’ attention to their devices.
——————————————————————————————————————————-
PANEL D: Data Science & Analytics Across Sporting Ecosystems
(Ilari Paasivirta Dream Sports; Ozan Adiguzel Principal AI Engineer, Finster AI ; Konstantinos Pelechrinis, Prof. Informatics & Network Systems, University of Pittsburgh, Data Analytics Consultant – Dallas Mavericks; Jorge Ortiz, Associate Professor, Electrical & Computer Engineering, Rutgers University CV/AI Lead NY Yankees)
- The Translator: The position point to a crucial communication gap in sports analytics. This new role is a bridge between the highly technical analytics team and the strategic, intuitive world of coaching. LLMs can be used to write coach-friendly reports, showing how AI is being used to solve a human communication problem.
- What’s lacking in sports data collection? The next frontier of sports analytics. ‘Clutch moments’ and ‘team synergy’ are qualitative, almost intangible concepts that are difficult to measure with traditional stats. The future of sports analytics lies in moving beyond simple performance metrics to more complex, behavioral, and psychological data points. AI and machine learning will be essential in modeling these abstract concepts.
- What should you learn? Foundational skills like coding, mathematics, statistics, and system design.
Updating The Circle of Relevance…