Liverpool FC has signed a multiyear deal with SAS to overhaul its digital marketing infrastructure. The partnership centers on AI-powered fan engagement - delivering real-time, data-driven communications to a global supporter base. It's a concrete example of sports marketing technology being deployed at enterprise scale. For IT leaders evaluating martech investments, the specifics are worth unpacking.
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What Liverpool FC Is Actually Building with SAS
Liverpool FC is deploying SAS Customer Intelligence 360 as its primary martech platform. Alongside it sits SAS Viya, which handles the advanced analytics and AI modeling layer. Together, they give the club a unified view of fan data across web, mobile, and social channels.
Three use cases have been confirmed for the initial deployment. The first is personalized merchandising — using AI-driven insights to tailor product recommendations based on fan interests and engagement patterns. The second is journey optimization — applying analytics to identify friction points across digital properties. The third is fan engagement modeling — using AI to predict fan behavior and sharpen the relevance of communications.
Chris Jennions, VP of Marketing at Liverpool FC, described the commercial logic:
"With SAS Customer Intelligence 360 we can deliver AI-powered real-time, individualized digital fan experiences, serving our supporters better than ever before."
He added that success will be measured through "engagement, conversion and fan sentiment." The significance here is that AI-powered fan engagement is being tied directly to measurable business outcomes, not just experience improvement.
The platform also enables what the club calls "always-on" engagement — meaning personalized digital experiences are not limited to matchdays or campaign windows. Data flows continuously, and interactions are triggered by behavior rather than calendar.
How AI Agents Factor Into the Roadmap
The second phase of the LFC-SAS deployment involves AI agents embedded within SAS Customer Intelligence 360. These are automated tools that can perform specific marketing tasks without constant human input.
According to SAS, the agents will handle three functions. First, creating and iteratively improving audience segments using adaptive learning. Second, optimizing fan journeys continuously based on behavior, context, and engagement signals. Third, generating operational and performance insights from within the platform itself.
The distinction SAS draws is between AI-assisted and AI-orchestrated marketing. Jonathan Moran, Head of Martech Solutions Marketing at SAS, explained the difference:
"With the AI agents embedded in SAS Customer Intelligence 360, LFC can begin coordinating intelligent audience creation, designing customer journeys and decisions in real time."
He added that "marketers remain firmly in control of strategy, approvals, and guardrails."
That framing matters for IT leaders assessing sports marketing technology platforms. AI-assisted tools surface recommendations for humans to act on. AI-orchestrated systems execute decisions within pre-defined parameters. The architecture is different, the governance requirements are different, and the vendor evaluation criteria should reflect that.
It is worth noting that this second phase is forward-looking. LFC is laying the foundation now. The AI agent capability has not yet been fully deployed. That's a relevant distinction when benchmarking this as a case study for AI-powered fan engagement.
AI-Powered Fan Engagement Across The Sports Ecosystem
The LFC-SAS announcement sits within a broader pattern. Several major sports organizations have moved toward sports marketing technology built around AI and data unification in recent months. Two cases are particularly relevant for IT leaders.
Formula 1 and Salesforce: Scale and Autonomous Query Handling
Formula 1 and Salesforce expanded their existing partnership in March 2026 to launch an AI-powered fan companion agent on the official F1 website. The agent runs on Agentforce 360 technology and draws on over 100 trusted F1 data sources.
