How Sports Leagues and Teams Can Create Value With AI

Professional sports organizations hold one of the richest concentrations of real-time data in any industry, and AI is turning that data into competitive and commercial advantages. Leagues and teams are already using AI to personalize fan content and enhance the fan experience, and more advanced organizations are using AI for on-field performance and organizational optimization.

The AI delta and what it means for sports organizations

AI is the latest in a succession of technology waves that have reshaped how businesses operate, from the internet to ecommerce to the app economy. The numbers reflect the moment: Global investment in AI readiness is expected to reach $200 billion in the coming year.

For sports organizations, it’s still early in the season when it comes to the “AI delta,” but the standings are starting to take shape. Teams investing in a holistic AI strategy are putting more wins on the board across fan engagement, revenue and performance, while others risk falling behind as the gap compounds (see Figure 1).

The gap is already widening. Organizations that build a holistic approach are unlocking real enterprise value, while those focused only on tactical efficiencies are capturing a fraction of the upside and those sitting out are watching it erode. For executives and investors, the decisions made now will define competitive position for years to come.

Four ways sports leagues and teams are using AI to win

For the organizations choosing to lead, the value is already showing up in four distinct pools, each with its own return profile: fan engagement, monetization of data and content rights, on-field performance, and enterprise operations (see Figure 2).

Each value pool has produced its own set of early movers, with distinct approaches and measurable results.

Engagement

For most of its history, the professional sports experience has been a mass-market event designed for the average fan. AI is changing that, giving organizations the ability to generate personalized content automatically and deliver it at an individual scale.

The results are already visible across the industry. The NBA now produces tens of thousands of individualized highlight clips per season using AI-powered video understanding. Wimbledon launched a “Live Likelihood to Win” feature giving fans continuous, match-specific insights in real time. Volleyball World uses AI-driven data capture and predictive modeling to power in-play analytics and personalized betting experiences.

Image 1: Wimbledon’s AI fan experience
Source: AI Business

For a deeper look at how fans are engaging with sports content, see our latest Sports Fan Survey.

Monetization

For many sports organizations, data and content have long been underutilized assets. AI is turning proprietary libraries and real-time streams into recurring revenue engines across multiple channels.

While early monetization efforts often focused on tactical wins like dynamic pricing, the current frontier is the commercialization of proprietary data and content rights. WWE used AI to tag decades of archived video, transforming a static library into a discoverable and licensable digital product. Sportradar monitors global betting markets in real time, turning integrity protection into a regulated, data-driven revenue stream.

The results can be striking. For example, the University of South Carolina projected a 40% increase in ticket revenue after adopting AI-driven dynamic pricing for its women’s basketball program.

Performance

On-field decisions have long relied on human intuition. AI now connects tracking data, video and sensor inputs to create a more empirical foundation for athlete management.

While baseline automation has already delivered efficiency (like Sevilla FC’s AI scouting tool that eliminates hundreds of hours of manual short-listing), the most compelling frontier involves predictive thinking partners that inform strategy and safety. The NFL’s Digital Athlete program aggregates league-wide data to predict injury risk and inform training loads and rule design. Similarly, Williams F1 has integrated Claude as an official “Thinking Partner” across race strategy and car development.

Enterprise enablement

For organizations managing multi-venue and multi-season complexity, AI is delivering meaningful operating leverage enterprise-wide by automating back-office functions where small efficiencies compound quickly.

The MLB, for example, uses AI-based optimization to generate season schedules that must balance competitive fairness, broadcast priorities and venue constraints. In team operations, the Denver Broncos have sharpened sales forecasting and optimized concession planning through AI-driven insights. Similarly, Chelsea FC is integrating AI agents across club operations to improve the fan experience at scale.

How sports organizations turn AI pilots into lasting results

Across L.E.K. Consulting’s work with sports and live entertainment organizations, four pillars define whether AI investments deliver championship-level returns or quietly fade after the first season. Success requires a fundamental reimagining of the organization, including a ground-up rebuild of roles, tasks and the metrics used to measure victory.

These pillars give leadership a practical framework for moving from isolated pilots to organization-wide transformation (see Figure 3).

Value and accountability

AI programs without clear ownership produce noise instead of measurable progress. The organizations building durable value set their game plan before deployment, connecting every initiative to a measurable business outcome with a named owner. Bringing finance leadership in early is what makes that accountability real, giving the program a line of sight to ROI from the start and a track record to learn from.

Data and technology foundation

Building AI capability on fragmented or incomplete data is like calling the game from the wrong end of the stadium. The foundation that matters is not just clean data but the right data — spanning tracking, telemetry, and commercial and operational sources — structured in a way that AI systems can actually use. Getting that right is unglamorous work, but it’s what separates programs that perform under pressure from ones that stall when it matters.

Risk, governance and trust

The organizations earning durable returns from AI have clear guardrails around how models are used, who can see what, and how compliance and reputational risks are managed. Governance established early builds the investor trust that lets programs scale. Without it, one high-profile error can set the whole program back a season.

People, operating model and change management

Even the best playbook fails without coaches and players who know how to run it. The organizations getting the most from AI redefine the metrics that drive decisions; then they rebuild roles, tasks and workflows around those new priorities. In practice, that means asking hard questions: Which jobs change? Which decisions are made by models versus people? And which historical measures of performance no longer reflect how value is created?

A strategic checklist for leadership

Establishing this foundation creates the necessary room for leadership to ask the bigger questions that define a successful AI strategy:

• Do we have a unified data infrastructure that captures value across all commercial partners and distribution channels, or are we sitting on fragmented assets that no sponsor, broadcaster or club can fully exploit?
• Have we defined how AI capability is deployed consistently across the organization, including who sets the standards, who owns the models and how accountability is maintained?
• Are we measuring AI returns against the metrics that actually drive enterprise value, including rights renewals, competitive balance and fan lifetime value?
• Have we rethought our operating model from the ground up, including the roles, decision rights and performance metrics required to compete in an AI-augmented environment?

Putting AI strategy into practice

L.E.K.’s Sports and Live Entertainment practice has extensive experience supporting clients globally across strategy, value creation and M&A, working with leagues, teams, media partners, venue operators, service providers and investors. L.E.K. brings together deep sector expertise in fan engagement, media rights, live events and data strategy with firmwide capabilities in AI and advanced analytics.

To discuss how AI can create value for your organization, contact us.

L.E.K. Consulting is a registered trademark of L.E.K. Consulting. All other products and brands mentioned in this document are properties of their respective owners. © 2026 L.E.K. Consulting