Abstract

Artificial intelligence (AI) is rapidly transforming sport sciences through machine learning, computer vision, wearable technologies, generative models, and decision-support systems. This editorial argues that the central challenge is no longer whether AI will enter sport sciences, but whether educational programmes, professional roles, and governance structures will adapt sufficiently to ensure its responsible use. Although AI can enhance performance analysis, injury-risk assessment, training design, physical-activity promotion, and sport management, algorithmic outputs remain dependent on data quality, validation, population representativeness, and contextual interpretation. Sport-science professionals therefore require competencies extending beyond routine technology use, including data literacy, critical appraisal, ethical reasoning, interdisciplinary collaboration, and the ability to evaluate uncertainty, bias, fairness, and external validity. Curricula should integrate AI across sport-science disciplines, while assessment should increasingly emphasise judgement, evidence verification, and context-specific decision-making. Professional roles must also shift from producing and reporting information toward interpreting evidence, governing technology, and assuming responsibility for decisions. Responsible adoption further requires clear standards for privacy, transparency, accountability, equity, and human oversight. Ultimately, AI should augment rather than replace professional expertise. The future of sport sciences will depend on professionals who combine computational literacy with scientific knowledge, contextual understanding, ethical judgement, and human-centred decision-making.