Teaching with technology and AI in sport management

Digital learning platforms, virtual collaboration tools, and AI-powered tutoring systems offer opportunities to personalise learning, enhance engagement, and build essential digital competencies demanded across sport organisations. Adaptive AI feedback, automated assessment processes, and learning analytics frameworks support students in developing critical skills in areas such as sport marketing, event management, governance, and performance analysis, while also improving retention and progression. However, this technological shift introduces significant challenges. Digital access inequalities risk excluding students in under-resourced institutions, international cohorts, and widening-participation groups. Algorithmic bias embedded in AI systems can reproduce inequities across race, gender, language, and disability, issues of relevance when sport management programmes prioritise inclusivity and global employability. Generative AI complicates traditional assessment practices, requiring educators to design authentic, industry-embedded tasks that emphasise human judgment, ethical reasoning, and contextual decision-making central to sport sector professions. Ethical integration further demands robust data privacy safeguards, transparent institutional policies, and sustained educational development. These complexities highlight the need for evidence-led, equitable, and pedagogically grounded approaches to AI adoption that does not diminish the preparation of sport management graduates for contemporary professional practice.