Sports Teams and AI: Real Results and Real Challenges

We were excited to sit down with Jennifer Pelino, Chief Commercial Officer and President at Sports Innovation Lab (SIL), to discuss how AI is transforming the ultracompetitive sports industry. In this Q&A, Jennifer shares her insights on the current state of AI adoption, key trends, challenges and the tangible business benefits sports organizations are realizing with AI-powered solutions and third-party data. 

Q: Please tell me about Sports Innovation Lab and your role in leading its data and AI initiatives within the sports industry.

A: Sports Innovation Lab is a leading fan intelligence and data company that helps brands, properties and media platforms unlock growth through a deeper understanding of modern fan behaviors. As CCO and President, I guide our commercial and operations strategy, with a focus on how our data, analytic and audience solutions drive smarter sponsorships, media buying and fan engagement. My role centers on scaling our proprietary data solutions and forging strategic partnerships — including with Snowflake — to make these insights actionable across the sports and entertainment ecosystem.

Q: From your perspective, how is AI transforming the sports industry? What are some priority AI use cases that the sports industry is actively implementing or planning for the near future?

A: AI is reshaping the way sports organizations interact with fans, optimize media performance and measure ROI. The top priorities today include predictive fan engagement, dynamic sponsorship evaluation and media targeting. We’re also seeing rising interest in AI for content personalization and operational analytics. AI helps turn fragmented fan data into precision insights that directly impact business outcomes.

Q: How would you characterize the current state of AI adoption in the sports industry, and what key trends do you anticipate emerging in the next one to two years?

A: The industry is in the early stages of meaningful AI adoption. While there’s a lot of experimentation, few organizations have integrated AI at scale. In the next one to two years, I expect we’ll see growth in AI-powered fan segmentation, content creation and personalization, and predictive and optimized media planning. Partnerships with cloud platforms like Snowflake are key to unlocking this next phase since brands and teams can use data like Sports Innovation Lab’s with their own 1P data in an interoperable manner.

Q: What are some of the key challenges sports organizations face when trying to implement AI solutions, and how can these challenges be overcome?

A: Data fragmentation, limited internal capabilities and legacy systems are the biggest hurdles. Many sports organizations lack the data infrastructure or clean, interoperable data sets needed for scalable AI. Overcoming this requires strong data governance, cloud-based integration (like with Snowflake) and trusted partners who can simplify AI implementation through turnkey tools and enriched data.

Q: How is SIL currently using AI in its solutions, and are you using Snowflake Cortex AI?

A: We use AI to power our Fluid Fan Graph™ which takes millions of passively collected deterministic buy, attend and view behaviors to fuel behavior prediction, and develop our dynamic fluid fan™ communities. Snowflake Cortex AI enhances our speed to insight by enabling scalable ML workflows directly in the Snowflake ecosystem. This lets us operationalize fan insights faster and deliver them directly into brand and agency workflows.

Q: Could you provide a specific example or case study of how a sports organization has successfully applied AI through your solutions and Snowflake to achieve a significant business outcome?

A case study that is top of mind is our Taking Pole Position case study used by leading car racing organizations.  

Taking Pole Position details

• Sports Innovation Lab’s Sports Data Cloud, leveraging Snowflake, integrates billions of individual records — transactional data from teams, leagues, venues, brands, merchants and publishers. Through our proprietary Fluid Fan Graph™ ontology, we map dynamic fan communities across sports, media, commerce and entertainment.

• Leveraging Snowflake’s near real-time, scalable infrastructure, we executed multiple AI/ML models across more than 500 million records using Cortex AI — achieving inference speeds of 200 million rows per minute while optimizing cost and performance with Snowpark.

• Clients like NASCAR tap into this intelligence via Snowflake Marketplace to uncover new sponsorship opportunities, drive ticket sales and boost fan acquisition by understanding fan spend and behavior.

• SIL is redefining audience intelligence by combining the Fluid Fan Graph™ and Snowflake’s Interoperable Connected Ecosystem — fusing quality consumer data, advanced data science and addressable demand to predict and activate fan behaviors, ultimately unlocking new revenue and deeper engagement.

Q: How is AI being used to enhance the fan experience, and what are some future possibilities for improving fan engagement through AI?

A: AI allows organizations to deliver hyperpersonalized content, promotions and experiences. It powers smarter event recommendations, targeted messaging and predictive offers. In the future, AI will enable real-time customization of fan journeys — whether digital or in-stadium — making every interaction more meaningful and monetizable. This is where SIL’s data sets will help drive that accuracy.

Q: What tangible business benefits are your customers realizing with your AI-powered solutions and proprietary data sets?

A: Customers are seeing improved campaign ROI, faster insights and more efficient sponsorship planning that in turn drives greater value for brand sponsors and teams/leagues. For example, AI-driven fan targeting has reduced media waste by up to 40% and increased fan conversion rates for a number of brands using our audiences to connect with the right consumers within their consideration set programmatically. Our proprietary data gives them an edge by identifying opportunities traditional CRM data simply can’t with only a limited data set and view.

Q: In a competitive sports market, how does leveraging AI effectively translate to a distinct competitive advantage for organizations?

A: In today’s fragmented and fast-moving sports landscape, AI gives organizations a measurable edge by enabling real-time, data-driven decisions. It helps decode complex fan behavior, personalize engagement at scale, and optimize media and sponsorship performance with speed and precision. At Sports Innovation Lab, we’re focused on operationalizing AI through adaptive fan journeys, dynamic media targeting, and real-time sponsorship valuation—so rights holders and brands don’t just keep up, they stay ahead.

Q: What’s the role of third-party data in AI? How important is it to sports analytics?

A: Third-party data plays a critical role in bridging the gaps left by first-party sources — especially when it comes to understanding anonymous or casual fans. At Sports Innovation Lab, our fan data sets go beyond basic demographics, capturing deep and rich behavioral signals across the long tail of the sports ecosystem — often in places traditional sources can’t reach. These data sets power our ontological methodology, which classifies fans not through a rigid taxonomy but based on nuanced patterns of behavior. This allows us to identify whether someone is, for example, a high-value pickleball fan, a big-event football viewer or a youth sports baseball or hockey parent. By integrating these insights, brands can make smarter decisions — like tailoring the right streaming package for the upcoming NBA season based on actual fan demand. AI is essential in unlocking the scale and complexity of these insights, enabling personalized, high-impact strategies that weren’t previously possible.

Q: Please talk to me about SIL’s proprietary data listings on Snowflake Marketplace. What competitive advantages do they deliver to customers?

A: Our listings offer high-quality, preclustered fan data with behavioral signals and commercial intent scores — ready for activation. What makes it unique is the combination of sports- and entertainment-specific insights and real-time readiness. Clients can drop it into their own environments and begin planning or targeting immediately. We also can create private listings based on the client’s need and granularity. Because Sports Innovation Lab’s data is already housed in Snowflake, we can in almost real time provide the customized request.

Learn more about how Snowflake powers a competitive edge in the sports industry through the Snowflake AI Data Cloud for Sports.