91影视破解版

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Sport AI & Society Chair

The Research Chair explores the impact of artificial intelligence and data analytics on the sports industry. It examines innovation, emerging business models, and the societal challenges shaping the future of sport.

Background

Clayton Christensen鈥檚 disruptive innovation theory (Harvard Business School) explains how imperfect but radically more accessible solutions open markets to people who were previously excluded, then improve until they challenge 鈥減erfect鈥� high鈥慹nd offerings. In this view, disruption is less about top performance and more about accepting lower initial quality in exchange for broad access and low cost.

Applied to AI in contexts such as women鈥檚 sports or women鈥檚 football, truly disruptive tools are those that are 鈥済ood enough鈥� but affordable and usable for every club and fan, helping close performance, visibility, and funding gaps rather than serving only elite men鈥檚 teams.

Vision and Purpose

To harness Artificial Intelligence as a catalyst for inclusion and equity within the global sports ecosystem.

Mission

The Sport AI & Society Chair explores the beneficial applications of AI to reduce inequalities鈥攕uch as the gap between women’s and men’s sports. We believe that integrating AI into sports economics, business, and marketing drives virtuous innovation and creates a more inclusive future for sport.

Goals

  • Use AI and data analysis to find innovative solutions to concrete sport business issues (e.g., new revenues and new business models) that are compatible with sustainable development, social responsibility (CSR/ESG) and inclusion.
  • Foster information flow in an interdisciplinary (e.g., sport+health) and international sport context: Asia – North America – Europe – Africa, Middle East, etc.

Six Research Axes

Performance

AI and data in sports and sports marketing management: performance, scouting, health/injuries.

Innovation

AI-generated virtual influencers, serious games, mobile apps, digital transformation, technical clothing, health/sports medicine, e-sport, AI tools, mental preparation (psychology, music, etc.)

Globalization

of sports markets, import/export of best practices.

New Business Models

New revenues, branding, territorial marketing, link between performance and revenue (entertainment), performance levers, sponsorship effectiveness and ROI.

Women’s Sports

Gender equality, sport and sexism.

ESG

Societal issues in sports, inclusion, sustainability and eco-responsibility (stadia, arenas, etc.), discrimination, career transition of elite athletes, sport and education, sport and health (eg., at the workplace/QWL), ethics, legal issues (doping, fraud, online betting, etc.)

Past and current projects

Participation in four AI and Sports Working Groups

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November 2025 – January 2026

Organized by the French SporTech network () and commissioned by the French Ministry of Sports, Youth, and Community Life

  • AI & Sustainable Major Events
  • AI & Promoting Sports Participation for All
  • AI & Athlete Performance/ Health
  • AI & Fan / Spectator Experience

AI and Women鈥檚 sports: Opportunities, Challenges and New Business Models (June 2026)

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AI and High Performance in Olympic Games and the FFN (January 2025)

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Digital Activation of Sponsoring in the Retail Industry (March 2024)

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91影视破解版鈥檚 first international conference on AI & Sports Marketing (June 10 & 11, 2026)

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Featuring world-class speakers from UCLA, Columbia Business School, HEC, St Gallen University, Rotterdam School of Management, University of New England, University of Lausanne, etc.

Additional Info

Sport and society: evolution and trends

1. Redefining young people’s relationship with sport

  • New technologies: streaming platforms (growing by 8.5% a year), e-sports, social networks, mobile apps and more
  • Younger fans are driving stadium attendance growth (Source: Research brief – Capgemini Research Institute 2025. Beyond the Game)

2. The changing role of women

Behind but also in front of the screen(s): growth in female audiences and women’s sport.

3. Digital transformation / innovation in sport

  • Mobile applications, social media, e-commerce, connected stadiums, in line with the branding strategy of professional sports clubs (territorial marketing)
  • Fans want a balance between technology/innovation and authenticity (Capgemini Research Institute 2025)

4. Ever-growing volume of (big) data

  • Fans trust AI tools to access sports info (54%) and generate sports content (59%).
  • 27% would pay +8% extra for AI-enhanced viewing experiences (compete against real sports players virtually during a live game + stats and real-time data; Capgemini Research Institute 2025)
  • AI for everyone (coaching apps).

5. Finer segmentation of the sports market

Sports equipment and supplies, nutrition/health, online sports betting, eSports, professional clubs/organizations, etc.

6. CSR / ESG, SD, environment, inclusion and sport

SD requirements/audits, social issues such as gender parity and equity, textiles/clothing and sports competitions, parasports, sport and education, sport and racism/discrimination, the recent issue of transgender athletes in the USA, natural grass/synthetic turf, etc.

AI & Sport Market Growth

AI and sport: global market value x 3.5 over 2023-2030 (+17%/year)

Growing use of AI (generative/IAG and other types of AI) in sport:

Sports performance in the strict sense (individual, team and e-sports)

Sports economics, sports marketing, sports business in the broadest sense:

  • AI and talent detection (scouting / aiScout or Wyscout apps) => impact on player transfer markets
  • AI and sports performance enhancement (nutrition, injury prevention)
  • AI and improved fan experience (XC) => customer engagement + increased revenues
  • NBA: for teams (strategy and player performance) and fans (VR, AR, stats, team info, behind-the-scenes info)
  • NFL: personalized interactive virtual tours of the Dallas Cowboys stadium
  • Intel at the Paris 2024 Olympics
  • Strongest growth in Asia
  • Social issues/trends, ethics, personal data protection, etc.

Numerous applications of AI/Data analysis in sports

  • Player performance analysis + scouting (e.g., JuniStat, Opta, etc.)
  • Fan engagement/fan experience
  • Injury prevention and rehabilitation
  • Team/game strategy/tactics and coaching solutions + events during game
  • Content distribution and personalization (broadcast management)
  • Ticketing and pricing optimization
  • Sponsoring and marketing analysis
  • Virtual training programs (coaching apps)