AI in Sport: Friend or Foe?

Introduction

Sport has always moved in step with technology, but few innovations have arrived with the speed, scale and sense of unease that now surrounds artificial intelligence. Once confined to science fiction and futuristic forecasts, AI is rapidly becoming embedded across the fabric of global sport: from performance analysis and injury prediction, to officiating, fan engagement and commercial decision-making. As AI begins to generate, manipulate, and personalise sports content in real time, fans are increasingly left to question not just what they are watching, but whether it is real at all. Its growing influence is often met with a mixture of excitement and apprehension. For some, AI represents unprecedented opportunity; for others, it signals a loss of control, authenticity and human judgement. Yet despite the concern, AI is no longer on the horizon; it is already shaping how sport is played, watched, governed and consumed.

Learning Objective

· To critically examine the growing use of artificial intelligence in sport and evaluate its impact on performance, commercial strategy and the wider sport ecosystem.

How sports organisations are using AI to improve on-field performance

Artificial intelligence now sits at the centre of modern high-performance sport, transforming how athletes train, how teams prepare for competition, and how recovery is managed across congested competitive calendars (we all hear players and managers complain of fixture congestion, don’t we?) By combining biometric data, GPS tracking, video analysis and online databases, AI enables competitors to move from reactive decision-making to predictive, real-time performance management. I have even seen some clubs use AI to schedule their flights and dinnertime menu! Rather than relying solely on intuition and historical trends, performance staff can now anticipate fatigue, optimise tactical output and protect player welfare with unprecedented precision.

Individual Player performance

It is now routine to see footballers, rugby players and endurance athletes wearing GPS vests, heart-rate monitors and biometric sensors in both training and competition. While these technologies generate vast amounts of data on workload, intensity and fatigue, for many athletes, this information risks becoming little more than numbers on a spreadsheet unless it is interpreted with expert guidance. And sometimes, that expertise and guidance can take years of experience and multiple degrees to interpret. AI systems now integrate physiological output with lifestyle and recovery behaviours across all sports. In football and rugby, training load and collision data are combined with sleep tracking to manage fatigue across congested fixture periods. In endurance sport and golf, AI can analyse sleep quality, recovery rate and daily readiness to guide technical and physical preparation. Nutrition is also increasingly AI-supported, with algorithms generating individualised dietary plans based on energy expenditure, recovery needs and performance goals. I have even seen some nutritional plans linked to weather and time zone changes!

This marks a shift from isolated performance monitoring to a holistic, continuous performance model in which training, nutrition, recovery and lifestyle are aligned through real-time feedback. However, without sufficient data literacy, there remains a risk that even the most sophisticated systems overwhelm players with information rather than empower them. AI has the potential to profoundly enhance individual performance and well-being, but only when athletes and practitioners understand how to translate data into intelligent action.

Team performance and strategy

AI now plays a central role in how teams prepare, adapt and compete across elite sport. In football and rugby, machine learning systems analyse pressing patterns, defensive structure, transition speed and spatial occupation to inform tactical planning and opposition analysis. Teams can now model likely build-up patterns, set-piece routines and attacking tendencies before a match is played rather than relying solely on retrospective video analysis.

In cricket and baseball, AI evaluates batter, bowler and pitcher tendencies to optimise field placements and tactical match-ups. In Formula One, vast streams of live telemetry data are processed by AI to guide race strategy, including tyre degradation, fuel management, pit-stop timing and overtaking probability in real time. While these systems enhance collective performance and strategic precision, they also shift greater influence towards the algorithm in shaping how teams play. The central challenge is ensuring that AI sharpens tactical intelligence without diminishing coaching intuition, creativity and the unpredictability that defines sporting competition. After all, we do not want robotic matches – it would be like watching ChatGPT having a conversation with Co-Pilot.

AI and Commercialisation of sport

Artificial intelligence is no longer just enhancing sport; it is actively reshaping how it is sold, packaged and monetised. From dynamic ticket pricing and targeted sponsorship to personalised marketing and automated content distribution, AI now sits at the heart of modern sports revenue models across all departments. Fans are no longer simply supporters; they are data points within predictive commercial systems designed to maximise engagement and spending. For example, in football, basketball and Formula One, AI is used to forecast demand, tailor merchandise offers, optimise hospitality sales and deliver highly targeted digital advertising. AI now tracks sponsor visibility across broadcasts and social media with precision, turning every second of screen time into measurable commercial value. Being able to alter advertising boards and screens based on geographical location, demographic and Google search, advertisers can target more people and command a higher fee for sponsorship packages. The result is a hyper-efficient commercial ecosystem where emotion, loyalty and behaviour are continuously analysed and monetised.

Yet this commercial power needs to be treated with caution, as algorithms increasingly dictate what fans see, buy and value, long-held notions of authenticity, community and supporter identity come under pressure. The challenge for the sports industry is stark: AI can drive unprecedented commercial growth, but unless it is governed with transparency and restraint, it risks reducing the soul of sport to nothing more than a revenue-generating dataset.

Gambling

Bookmakers use AI to analyse vast real-time data streams including player performance, in-game events, weather conditions, betting behaviour and market movement to generate live odds with extraordinary speed and precision. In-play betting markets, which now dominate online wagering, are entirely driven by algorithmic modelling rather than human traders.

At the same time, fans themselves are increasingly turning to AI to inform their betting behaviour. Tipster algorithms, prediction bots and AI-driven statistical models promise to identify value bets, forecast scorelines and simulate match outcomes. On social media and betting platforms, supporters are now encouraged to “trust the data” rather than instinct, gut feeling or sporting knowledge. Gambling, once rooted in uncertainty and intuition, is becoming a contest of competing algorithms. The results of consumers trusting AI for betting is becoming more successful, with people now having the best analysts at their touch of their fingers, look at this story here. Carson Szeder took $5 and turned it into $1000 pretty quickly, before taking his learning and starting his own AI gambling company. These new age AI gambling tools attempt to tackle an old age problem. While bookmakers deploy highly sophisticated AI to protect profit margins, consumers often rely on simplified predictive tools marketed as “smart betting assistance”. The power imbalance used to be start, but could it become slowly more even? As betting becomes increasingly automated, faster and more personalised, the risks of addiction, financial harm and behavioural manipulation intensify. The central danger is that AI does not merely predict fan behaviour in gambling markets, it actively shapes and accelerates it.

The growing reliance on AI within gambling markets has profound implications for sporting integrity and regulation. As betting algorithms become faster and more sophisticated, they place increased pressure on integrity units to detect match-fixing, micro-manipulation and suspicious in-play activity in real time. Governing bodies now deploy their own AI systems to monitor abnormal betting patterns, yet regulation continues to lag behind the speed of technological change. This creates an algorithmic arms race between bookmakers, bettors and regulators. Without stronger oversight, transparent data sharing and robust ethical governance, AI-driven gambling risks embedding deeper corruption vulnerabilities into sport while simultaneously distancing responsibility from human decision-makers behind the technology.

Conclusion

Artificial intelligence is now embedded across every layer of the sporting ecosystem, from individual performance optimisation and team strategy to commercialisation, gambling and global media production. Its capacity to enhance performance, personalise fan experiences and drive unprecedented commercial growth is undeniable. Yet this same power is also reshaping the ethical foundations of sport, challenging long-held assumptions about fairness, integrity, data ownership and human judgment.

AI promises marginal gains, efficiency and competitive advantage, but it also introduces new forms of surveillance, algorithmic control and commercial exploitation. As athletes, fans and organisations become increasingly “datafied”, the risk is not that AI will replace sport, but that it will quietly redefine it in ways that prioritise optimisation over authenticity and profit over protection. Following players and teams on X nowadays, you see xG, pressure zones, high line %, and win ratio – these figures are more suited to a spreadsheet than to the beautiful, passionate game I love. Whilst AI is around for the now and the future, we cannot forget that human emotion, interaction and passion is what built our great sports to its current position.

Reflective Questions for Students

· Why has AI adoption accelerated so rapidly within elite and professional sport?

· How is AI reshaping performance analysis and athlete welfare?

· What ethical and governance challenges does AI introduce to the sports industry?

· Will AI enhance or undermine the human essence of sport in the long term?

Suggested Supplementary Materials

·         How AI is powering Sport

·         The Role of Artificial Intelligence in Sports Analytics: A Systematic Review and Meta-Analysis of Performance Trends

·         AI in Sport – Opportunity, Excitement, Progression and Acceleration