NFL, AWS drive football modernization with cloud, AI

The Indianapolis Colts and Atlanta Falcons played at the venerable Olympiastadion in Berlin earlier this month as part of the NFL’s international series.

Prior to the event, Amazon Web Services held a small analyst event to talk about the partnership between AWS and the NFL and what that has meant for the evolution of the game. Like many organizations, the NFL has turned to the cloud, and AI has enabled the league to rapidly evolve, be more agile and create new experiences.

In the 2025 season, the NFL hosted seven international games, which included its first regular season games in Spain and Ireland and opening weekend in Sao Paulo, Brazil. This itself poses some challenges as the technology used to power each game needs to be brought to every location for a single game. At a most basic level, moving infrastructure to the AWS cloud makes technology significantly more portable than having to stand up truckloads of IT infrastructure in every location. This helps create a consistent experience for the fans and teams regardless of whether the game is being played in a modern stadium, like SoFi in LA, or at an 89-year-old facility with hand-carved stone, like the one in Berlin.

Beyond acting as an IT accelerator, the partnership between the NFL and AWS has helped modernize the game more in the past few years than at any other time in the history of the league. During a panel, NFL Deputy CIO Aaron Amendolia and Julie Souza, Global Head of Sports for AWS, discussed the role that data and analytics has played in the modernization effort, which includes the following.

Global expansion and fan engagement

The NFL’s international series demonstrates a data-backed strategy, enabled by AWS technology, targeting existing avid fan bases to spur new growth. Other leagues have attempted to play international games, but the NFL has been the most successful because of the following:

• Localization: Data and AI enable personalized experiences, such as local language content and adapting to regional customs.
• Unique product for local markets: American football is well understood in North America but not in other markets. Cloud producing the game lets the NFL create different versions of the broadcast for various markets. As an example, games broadcast in Australia would have a heavy emphasis on explaining basic rules to that audience.
• Data-driven targeting: The location of the international games is guided by data on fan locations and avidity, ensuring games are placed where they will have the highest impact. The NFL can use this data to have US teams create a “home market” in European cities. As an example, the Seattle Seahawks have a significant fan base in Berlin, which is why the team set up “Seahawks Haus” there.

In-game data and next-gen stats

Almost every sport is now highly data driven, and the NFL is no different. The panel discussion underscored the leagues of integrating technology into the game itself, moving from initial manual systems to sophisticated tracking.

• AWS Next Gen Stats: Initially used for player participation tracking (replacing manual photo-taking), Next Gen Stats uses sensors to capture center-of-mass and contact information, which is then used to generate performance insights.
• Computer vision: Computer vision was initially insufficient, but the technology has improved greatly over the past few years. The NFL has now embraced computer vision, notably using six 8k cameras in every stadium to measure first downs. This replaced the 100-year tradition of using physical sticks connected with a chain to determine first downs. This blended approach of using sensors and computer vision maximizes data capture for complex plays where one source may not be enough.
• Advanced data use cases: The massive influx of data supports officiating, equipment testing, rule development, player health and safety (e.g., concussion reduction), and team-level strategy/scouting (“Moneyball”).

Generative AI: From efficiency to hyper-personalization

Very quickly, generative AI has shifted from a “shiny new thing” to a mainstream tool focused on operational efficiency and content maximization. Use cases mentioned include:

• Data governance: A key internal challenge is the NFL’s disparate data silos (sensor, video, rules, business logic) and applying governance layers so that Gen AI agents (for media, officiating, etc.) can operate consistently and effectively without needing constant re-tooling.
• Operational efficiency: Gen AI is used to streamline tasks like sifting through policy documents and, notably, in marketing. Campaigns that once took weeks can now iterate hundreds of versions in minutes, offering contextual localization, language translation, and featuring the most relevant players for specific global markets.
• Content maximization: Gen AI is used to create derivatives of long-form content (e.g., TikTok and Twitter versions) efficiently. There’s also innovation in using data feeds to generate automated commentary and context, creating new, scalable audio/visual experiences.

Solving hard-to-solve problems

The NFL/AWS partnership is something companies in all industries should look at as the collaboration has resulted in the ability to solve problems that are challenging or, in some cases, historically unsolvable. Some examples are:

• Scheduling complexity: The NFL schedule, with 26,000 factors resulting in one quadrillion potential schedules, highlights the application of intense compute for complex optimization—a challenge common in manufacturing or logistics.
• Simulation for safety: Kickoffs at NFL games have been something that the league has continually tweaked since it’s the play that has resulted in a high rate of injury. Kickoffs see twice the injury rate and four times the concussions of standard run/pass plays. Simulating 10,000 seasons worth of data allowed the NFL to alter the kickoff format, leading to the lowest concussion rate ever and a 79% increase in kickoff returns by Week 9, demonstrating data-informed safety and game quality improvements. In fact, kickoff injury percentage is in line with typical passing and running plays.
• Fan data consolidation: By structuring and cleaning up over 100 data sources, the NFL increased visibility from 12 million to 70 million fans, enabling better-targeted marketing campaigns that resulted in 2-3x open rates.

Balancing innovation, integrity, and adoption

One of the challenges for all businesses is balancing innovation with privacy and other issues. The league maintains a cautious approach to ensure technology enhances, rather than diminishes, the integrity and quality of the game.

• Maintaining integrity: Automation must not lower accuracy. Technology’s goal is to assist officials with factual, non-contextual decisions (like player count), freeing them up for complex, contextual judgments (like ball control). Over-automating penalties would stop the game and degrade the product. As an example, camera vision could likely detect a penalty on every play but that could create an unwatchable product.
• Ecosystem approach: Innovation requires collaborating with partners. New workflows are presented to broadcasters in a way that benefits the entire ecosystem, showing a scalable, reliable path (like cloud adoption) rather than forcing high-risk, expensive physical infrastructure changes on partners.
• Fan adoption: Getting fans to adopt new innovations, such as using Rapid Recap on Thursday Night Football on Prime Video, which provides viewers with a two-minute highlight reel of the game for those that join late. Data can help the league know which features are attracting fans versus those that are not.

While sports use cases are fun and appeal to a broad set of individuals, the lessons learned apply to all industries. Amendolia talked about keeping an open mind and never being afraid to revisit something. He cited the example of camera vision, where the league once deemed it not useful and moved on to sensors. As the technology improved, the league took another look, and the combination of the two provided more value than one alone. Technology changes faster today than ever before. It’s important to continually understand what’s possible as that will provide the competitive edge all businesses are looking for.