Jul 19th, 2024
Beyond the Scoreboard: Unveiling the Competitive Edge of AI Technology
Artificial intelligence has many potential applications for the field of sports technology. Over the last twenty years, advances in the field of AI technology have already begun to influence the way we perform and engage with sports.
AI has applications in betting and gaming, along with player monitoring and coaching, real-time sports data analytics, and more. In this article, we’ll look at the ways AI is already being used in the sports technology industry, at the potential future applications of AI and the way it will affect the sports industry market in the coming decades.
How AI Technology is Shaping the Future of Sports Technology Industry??
There are many ways in which artificial intelligence is already influencing how the sports technology industry behaves. From entertainment companies to consumers to coaches and the players themselves, there are a range of applications that are transforming the market.
Talent Acquisition: AI predictive modeling is changing the way teams and owners think about identifying the next generation of talent. Biomechanics, measured by IoT technologies, are shifting the recruitment process as players’ skills and abilities are evaluated on a whole new level.
Game Analytics and Strategy: Sports-tech is about more than in-game play. Insights into performance and analysis of things like goals, fouls, penalties, etc. are crucial when implementing a seasonal strategy.
Artificial intelligence can also be used to supplement existing analytical models when studying past performance–either of a single player, a whole team, or even an entire league. Analyzing the effectiveness of certain plays or approaches is crucial when it comes to putting together a winning strategy for future seasons.
Player Performance:Biometrics can also be used to monitor and enhance player performance, allowing coaches to create more effective training schedules and programs. Using AI to track performance can also help tailor diet plans, prevent injury, and provide better care for players when injuries are sustained.
Equipment: Data collected and analyzed by artificial intelligence can be used to improve the performance of not only players, but the equipment they use. Sports shoes, rackets, clubs, and even courts, fields, and arenas are all ripe for innovative changes brought about by machine intelligence, from springier shoes to performance-enhancing sod.
Fan Engagement: Through immersive experiences, improvements to scheduling and ticketing systems, tailored content and promotions, fans can feel as though they are getting a truly great experience from their favorite team, and teams can leverage powerful data about their fans to improve their business models.
Journalism: Sports journalism is already benefiting from the advent of AI, especially NLP (Natural Language Processing) technologies. Journalists can leverage NLP systems like ChatGPT to generate content, analyze statistics and game data, and make the process of writing articles faster and more efficient.
Advertising: Good data is critical for successful advertising, and AI can be used to identify advertising opportunities, and present relevant ads based on demographic information. It can also be used to monitor audience response to these ads—not just at the click-tracking level, but in sophisticated ways like discerning audiences’ emotional responses.
Key trends for AI Technology in sports
The global sports analytics market is projected to reach a revenue of $22 billion by 2030—a CAGR of over 30%. The market for sports-specific AI technology is expected to grow to around $20 billion by the same date. Currently, around 70% of sports industry experts consider physical sport augmentation a key market force.
It’s likely that we’ll see a rise in the use of not only AI, but also VR (Virtual Reality) and AR (Augmented Reality) technologies in the sports industry. AR and VR could be helpful in training situations, in creating immersive experiences for fans, in allowing coaches to gain a better understanding of what’s going on in a game, and helping referees to catch fouls, penalties, and other issues.
Potential pitfalls of AI use in sports technology
The primary concern when it comes to the proliferation of machine learning and AI technology in sports is data privacy and misuse. Players’ biometric data is incredibly sensitive information and could be easily exploited.
Additionally, data gathered from fans must be protected, and game analytics, trends, etc. are also areas in which a data leak or abuse could have disastrous results. Finally, it’s not impossible to imagine a world in which the use of AI in sports technology industry must be regulated to ensure fairness, much like performance-enhancing drugs are regulated today, or in which the use of AI technology in betting and gambling is outlawed.
