Artificial Intelligence (AI) in Sports - Thematic Intelligence
Summary
Artificial intelligence (AI) has the potential to be an important technology for the sports industry. Whilst a tried and tested use case has not yet been adopted for generative AI in sports, there is potential across the industry. AI could help tackle the challenges of fan engagement, media competition, and player safety.
Sports teams, companies, federations, and broadcasters are actively exploring the utility of artificial intelligence in the sports industry. The adoption of artificial intelligence intends to increase fan engagement, simplify business processes, and uncover insights in vast datasets. In terms of generative AI, a tried and tested, profitable use case has not yet been adopted by the sports industry.
Key Highlights
The global AI market will be worth $909 billion by 2030.
Sports AI use focuses on machine learning, computer vision.
A killer use case for generative AI in sports has not been found.
Scope
- This report provides an overview of the artificial intelligence theme and looks at its impact on the sports sector.
- The detailed value chain breaks down artificial intelligence into five categories: hardware, data management, foundational AI, advanced AI capabilities and delivery.
- The report includes a comprehensive data analysis, including market size and growth forecasts for artificial intelligence.
- It also includes selected case studies highlighting who is innovating in sport, using artificial intelligence.
- This report will help readers understand the business benefits that could be derived from artificial intelligence. In addition, the report identifies the technology vendors that are leading across the artificial intelligence market. The report uncovers the sports federations that are excelling in the artificial intelligence theme within GlobalData's thematic scorecard.
- Executive Summary
- Players
- Sports Challenges
- The Impact of AI on Sports
- How AI helps tackle the challenge of player safety
- How AI helps tackle the challenge of fan engagement
- How AI helps tackle the challenges of the decision-making process
- How AI helps tackle the challenge of sponsorship
- How AI helps tackle the challenge of media competition
- Case Studies
- The Masters uses IBM’s generative AI technology to create spoken commentary
- The DFL Deutsche Fußball Liga uses AI to give detailed statistics in real-time
- Wicket’s computer vision technology allows fans to enter stadiums without a ticket
- Twenty First Group used machine learning to help Swansea City find a new manager
- The PGA Tour is developing a media data lake to engage fans
- AI Timeline
- Market Size and Growth Forecasts
- Signals
- Mergers and acquisitions
- Patent trends
- Social media trends
- AI Value Chain
- Hardware
- Semiconductors
- Cameras
- Sensors and lasers
- Servers
- Storage devices
- Networking equipment
- Edge equipment
- Data management
- Data governance and security
- Data storage
- Data processing
- Data aggregation
- Data integration
- Foundational AI
- Data science
- Machine learning
- 3D modeling
- Knowledge representation and reasoning
- Visualization engines
- Advanced AI capabilities
- Human-AI interaction
- Decision-making
- Motion
- Creation (also known as generative AI)
- Sentience
- Delivery
- Hardware appliance
- Licensed software
- Artificial intelligence as a service
- Companies
- Leading AI adopters in sports
- Leading AI vendors
- Specialist AI vendors in sports
- Sector Scorecard
- Sporting federations sector scorecard
- Who’s who
- Thematic screen
- Glossary
- Further Reading
- GlobalData reports
- Our Thematic Research Methodology
- About GlobalData
- Contact Us
- List of Tables
- Table 1: Key challenges facing the sports sector.
- Table 2: Mergers and acquisitions
- Table 3: Leading AI adopters in sports
- Table 4: Leading AI vendors
- Table 5: Specialist AI vendors in sports
- Table 6: Glossary
- Table 7: GlobalData reports
- List of Figures
- Figure 1: Key players in AI
- Figure 2: AI-related mentions in sports on social media, July 2020 – July 2023
- Figure 3: Thematic impact assessment
- Figure 4: An example of the Bundesliga Match Facts
- Figure 5: Wicket’s facial ticketing system
- Figure 6: The AI story
- Figure 7: Global AI revenue will reach $909 billion by 2030
- Figure 8: Lululemon, an athletic apparel retailer, has filed the most patents in the AI theme in the sports sector
- Figure 9: Ice hockey was the most discussed sport in the AI theme on social media between July 2020 and July 2023
- Figure 10: The AI value chain - An overview
- Figure 11: The AI value chain - Hardware - semiconductors
- Figure 12: The AI value chain - Hardware - cameras
- Figure 13: The AI value chain - Hardware – sensors and lasers
- Figure 14: The AI value chain - Hardware – servers
- Figure 15: The AI value chain - Hardware – storage devices
- Figure 16: The AI value chain - Hardware – networking equipment
- Figure 17: The AI value chain - Hardware – edge equipment
- Figure 18: The AI value chain - Data management
- Figure 19: The AI value chain - Foundational AI – data science
- Figure 20: The AI value chain - Foundational AI – machine learning
- Figure 21: The AI value chain - Foundational AI – 3D modeling
- Figure 22: The AI value chain - Foundational AI – knowledge representation and reasoning
- Figure 23: The AI value chain - Foundational AI – visualization engines
- Figure 24: The AI value chain - Advanced AI capabilities– human-AI interaction
- Figure 25: The AI value chain - Advanced AI capabilities– decision-making
- Figure 26: The AI value chain - Advanced AI capabilities– motion
- Figure 27: The AI value chain - Advanced AI capabilities– creation
- Figure 28: The AI value chain - Advanced AI capabilities– sentience
- Figure 29: The AI value chain - Delivery
- Figure 30: Who does what in the sporting federation space?
- Figure 31: Thematic screen
- Figure 32: Our five-step approach for generating a sector scorecard
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