The artificial intelligence in sports market has witnessed significant growth in recent years. AI offers various advantages in sporting areas such as improved player performance analysis, enhanced fan engagement, effective team management, injury prediction and prevention, game strategy analysis, and more. Widespread adoption of AI technologies like machine learning, deep learning, and predictive analysis aids sports teams, leagues, broadcasters, clubs, and players to enhance the overall sporting experience. The growing use of advanced analytics and increasing volume of sports data has propelled the demand for AI in sports.
The Global Artificial Intelligence in Sports Market is estimated to be valued at US$ 6.12 Bn in 2024 and is expected to reach US$ 30.98 Bn by 2031, exhibiting a compound annual growth rate (CAGR) of 26.1% from 2024 to 2031.
Key Takeaways:
Key players operating in the artificial intelligence in sports market are Amazon Web Services, Inc., Apple Inc., Catapult Group International Ltd, Fujitsu Limited, Google LLC, IBM Corporation, Intel Corporation, Microsoft Corporation, Movella Holdings Inc., NEC Corporation, Oracle Corporation, Perform Group, Qualcomm Technologies, Inc., Salesforce.com Inc., and SAS Institute, Inc.
The key opportunities in the Artificial Intelligence in Sports Market Demand include customized fan experiences through AI-powered real-time engagement, optimizing team performance through prediction of plays, recruitment through identification of talented players from data, and minimizing injuries through equipment monitoring and predictive injury risk analysis. AI also aids in game strategy analysis, automated highlights and recap generation, and enhanced broadcasting experience through virtual avatars and virtual reality.
Technological advancements such as cloud-based deployment of AI models, edge computing, advanced computer vision, deep learning, natural language processing, and advanced analytics are expanding the potential of AI in sports. Rapid growth in sports data from various sources including wearables, IoT devices, cameras, social media is facilitating the training of sophisticated AI models with high accuracy. Advancements in computer vision enable automated generation of analytics from video feeds.
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