Artificial intelligence (AI) is reshaping sports in profound ways—from enhancing athlete performance to transforming how organisations manage teams and engage fans. At University of Toledo, for example, the Athletics Department has launched a mandatory AI training programme for all coaches, staff, and administrators, signalling a shift toward technology-savvy sports operations.
On the field, AI-driven analytics and wearable sensors are empowering teams to monitor movements, simulate scenarios, optimise training loads, and prevent injuries with unprecedented precision. A systematic review across multiple sports found that AI techniques such as convolutional neural networks and predictive modelling achieved an average classification accuracy of about 88 % in performance tasks—although it also noted that real-world application remains challenging.
Off the field, AI is changing how sports organisations engage fans, manage operations and monetise their platforms. From personalised digital experiences and smart ticketing to data-driven fundraising and performance metrics, analytics are becoming central tools. At Toledo, a partnership with a digital analytics provider has been used to restructure fan-engagement, ticketing and athlete support services.
However, this integration of AI also raises ethical and practical concerns: data privacy, algorithmic transparency, the risk of bias in performance prediction, and whether human judgement will be sidelined are all real issues. As sports become more AI-driven, the challenge will be to strike a balance where machines augment rather than replace the human intuition, creativity and emotional dimension that make sport compelling.
