Artificial intelligence skill demand in the spectator sports industry: an analysis of job postings data

Purpose Recent advances in the capabilities of generative artificial intelligence (AI) have led to increased interest from sport organizations and sport educators. However, the sport management scholarship currently lacks empirical analyses into the scope and areas of application of generative AI use in the sport industry workforce. Framed in economic theories on the impacts of automation on the workforce, we address this gap using job postings data. Design/methodology/approach Using a proprietary dataset of 251,684 spectator sport industry job postings from 2010 to 2025, and 253,799 postings from other industries, we estimate regressions testing for how advances in generative AI technologies have impacted skill demand in sport, relative to other industries. We then estimate regressions to test for what posting characteristics are predictive of employers seeking generative AI skills in sport. Findings The release of ChatGPT led to a 0.1 percentage-point increase in generative AI skill demand by spectator sport industry firms, with larger increases among postings requiring college education, and larger increases for nonsport firms. We find a positive association between the likelihood of sports industry postings requiring generative AI skills, education level and required experience. Demand for generative AI skills also varied across job types. Practical implications Our findings provide insights into how AI is impacting the sport industry workforce, how interaction between humans and AI is taking place in the industry, and insights for educators. Originality/value To our knowledge, this is the first study to empirically examine how generative AI is impacting sport industry worker demand.