In recent years, technological progress has taken over, changing the habits and ways of life of society. There has been a boom in digital platforms, apps and technological devices that, in addition to marking our daily lives, collect from each of us an incredible amount of profiling data, sometimes without us noticing. This data is stored and contributes to feeding the technological systems of AI, or Artificial Intelligence. 

What is Artificial Intelligence?

It is an emerging technology that aims to assimilate the behaviours of human intelligence to insert them into particular hardware and software systems and equip machines with typically human characteristics; such as recognizing objects, making decisions, driving a car, and generating marketing functions. All in total autonomy, without human intervention, but simply learning from his behaviour and data acquired through the various technological supports. AI is now present in every device we use, from mobile to computer, from tablet to car, and from Netflix to Alexa.  

The influence of AI on Sport

The sports industry has been strongly influenced by AI due to the abundance of data and quantifiable elements at its disposal, which make it a very fertile ground for the development of this technology. With the increasing popularity of sports among youth, post-graduation in sports management is a smart choice for those who want to gain knowledge about Sports Industry Laws on a professional level. 

Below are several applications that use AI in the sports landscape:

  1. Umpiring: Support to match judges and referees in making the right decisions during a match, through tools that we have now learned to know, such as the VAR (Video Assistant Referee) in football or the hawk-eye in tennis, or the Video Check in volleyball;
  2. Training and coaching: support athletes and their coaches during training sessions, to monitor their physical condition and sports performance. The data collected, often with the help of wearable technology (smart watch, applications, GPS, etc.) allow you to schedule training sessions aimed at achieving certain physical objectives and the correct preparation for the match;
  3. Scouting and recruiting: Support in assessing the potential of an athlete by estimating their market value and thus helping sports clubs to make the smartest decisions in terms of talent acquisition;
  4. Broadcasting: support in optimizing the way fans enjoy the live event. AI helps to select the best shots that make the viewing experience more authentic and immersive for supporters. Moreover, thanks to this technology, it is possible to provide the viewer with live statistical data relating to performance or technical choices, calculated in real-time (as already happens in Formula 1) for an increasingly effective audience involvement;
  5. Media and fan experience: Clubs are increasingly using virtual assistants such as chatbots to answer fan questions about competitions, statistics, ticketing or parking at the stadium. At the same time, AI is used to make the most interesting video highlights by exploiting the peaks of reaction of the audience recorded during the course of the event.

A postgraduate diploma in sports management in India allows the learner to develop skills related to finance, management, and marketing in the sports industry. Athletic director, fitness manager, contract manager, sports agent, athletic coach and event coordinator are some highly paid jobs that are offered after completing PG courses in sports management from NASM

What should you expect from the future of sports and AI?

The increasing use of AI will bring major changes at multiple levels:

  1. Apply the rules in a predictive mode, avoiding attitudes and behaviours that can harm other sportspersons, detecting the possible risks in advance like recourse of doping and blatant simulations. 
  2. Better interaction with the public and supporters: AI can provide a better user experience through real-time subscription packages.
  3. Provide real-time data to technicians and coaches: The data collected from the analysis of training sessions is intersected with the multiple sources of information. In this way, the customized data can be directly projected to the audience in real-time.