Artificial intelligence (AI) is rapidly moving from theory to practice in football. Once limited to scouting databases and GPS tracking, AI now promises to reshape how clubs design tactics, recruit talent, prevent injuries, and manage careers. A recent feature in The Athletic explored this future, interviewing leading practitioners and innovators to outline where the breakthroughs — and the challenges — may come next.
Tactical Development and Game Simulation
One of AI’s most striking applications lies in tactical simulation. Lee Mooney, former Head of Data Insights at City Football Group, noted that an AI agent could feasibly simulate “more football in 24 hours than has ever been played professionally in the 150-year history of the game.”
This power allows coaches to test formations, pressing structures, and substitution strategies in a “safe playground” before risking them on the pitch. In real time, AI could even recommend substitutions by detecting when players are tiring or making suboptimal decisions.
There are already practical steps in this direction: Liverpool partnered with Google DeepMind to use AI in refining corner-kick strategies — a glimpse of what tactical co-pilots may look like.
Recruitment and Talent Identification
Recruitment has long been a test bed for data, but AI is raising the stakes. Large language models (LLMs) are being used to summarize hundreds of scouting reports, highlight contradictions, and accelerate the filtering process. Today, “not a Premier League club among the 20 now who do not use data as the first filter in their scouting operation.”
The next frontier is predictive fit: visualising how a potential signing would perform in a club’s specific tactical system. As one recruitment source noted, scouts could start to be replaced by AI within two years. While this raises job displacement concerns, Mooney stresses that AI still cannot capture contextual nuances such as decision-making under pressure or body language cues. The future is therefore a human–machine co-dependency: structured insights from AI, validated by expert human judgement.
Injury Prevention and Player Longevity
Perhaps the most transformative frontier is health and longevity.
- Zone7, already used by Liverpool, Napoli, and Rangers, employs AI to predict muscle injury risks by analysing performance data.
- Barcelona’s Innovation Hub is investing in genomics, metabolomics, and immune data to build predictive health profiles. Through partnerships with companies like Made of Genes, they can simulate the external load a player will face and forecast injury risk with much greater accuracy.
- Omniscope, another Barcelona partner, uses AI to analyse millions of immune cells from a single blood sample, producing an “inflammation score” to diagnose early-stage issues and track recovery in real time.
The long-term vision includes regenerative AI therapies: engineering immune cells or banking healthy ones to be reintroduced later, effectively extending players’ peak careers. Omniscope CEO Vijay Vaswani believes these tools will arrive within five years, as AI accelerates the pace of sports medicine.
Challenges and Cultural Barriers
The technology exists, but execution remains difficult. Mooney emphasizes that applying AI at scale requires leadership stability and investment — two resources often scarce in football. Ted Knutson of StatsBomb recalls that even basic event-data analytics took a decade to gain acceptance, reflecting football’s resistance to change.
There is also a credibility gap: many analysts lack coaching backgrounds, making it difficult for their recommendations to gain traction in dressing rooms. Ethical and privacy concerns further complicate biomedical applications — Omniscope itself insists on strict data-protection protocols.
Finally, the competitive dimension cannot be ignored. As Mooney notes, an AI “arms race” is already underway. Clubs like Brighton and Brentford treat their proprietary models as strategic assets, guarding them from outsiders.
Lessons from the Past: The Analytics Revolution
The rise of AI mirrors the analytics revolution. A decade ago, clubs resisted event-data metrics. Today, xG and set-piece models are common. The same will likely happen with AI — first pioneered by specialists outside football, then embedded inside clubs.
AI is likely to follow a similar trajectory: pioneered by external specialists, gradually absorbed into club structures, and only later fully embedded in football culture.
Outlook: What the Next Five Years Could Bring
AI is poised to redefine football across three dimensions:
- Tactics – unlimited simulations creating new strategic possibilities.
- Recruitment – faster, more precise filtering of talent pools.
- Performance & Longevity – predictive health systems extending careers.
The critical barrier is not the technology but the willingness of football clubs to embrace it with clarity, discipline, and governance. Just as the analytics revolution reshaped set pieces, squad planning, and recruitment models, AI will become the next competitive frontier.
Transfers will continue to dominate the headlines.
But behind the scenes, AI-driven strategy and player longevity could decide which clubs build lasting success.
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