TRANSFORMATION OF THE SPORTS COACH ROLE IN THE GENERATIVE AI ERA: FROM ANALYTICS TO STRATEGY CO-CREATION
DOI:
https://doi.org/10.46793/ManagSport17-2.238BKeywords:
Generative AI, Sports Coaching, Performance Analysis, Strategic Decision-Making, Human-Computer Interaction, Coach EducationAbstract
While traditional sports analytics have focused on descriptive and predictive models to interpret historical data, the emergence of Generative Artificial Intelligence (GenAI) introduces novel capabilities for tactical simulation, content creation, and natural language interaction. This technological shift necessitates a fundamental re-evaluation of the human coach’s operational role within high-performance environments. This article critically examines the transformation of sports coaching in the GenAI era. It aims to synthesize current applications of generative models and propose a theoretical evolution from the “Human-in-the-Loop” paradigm to a “Coach-as-Editor” framework, where human expertise is applied to curate rather than originate strategic content. An integrative review of literature published between January 2016 and January 2026 was conducted using Web of Science, Scopus, PubMed, and IEEE Xplore. Following PRISMA guidelines, 39 studies were selected for synthesis across three core operational domains: tactical preparation, physiological load management, and talent identification. The analysis identifies that GenAI considerably enhances coaching efficacy through automated scenario generation, hyper-personalized training prescriptions, and globalized scouting capabilities. However, a SWOT analysis shows that while GenAI democratizes access to elite-level analytics, it introduces critical risks regarding algorithmic hallucinations, data privacy, and potential professional deskilling. The study posits that the future coaching role will transition from “strategic architect” to “sophisticated curator” of AI-generated alternatives. To steer this transition, sports organizations must adopt a phased implementation strategy that focuses on ethical governance, data literacy, and the preservation of human contextual judgment, ensuring a symbiotic rather than substitutive relationship between coach and machine.
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