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AI in Stadium Market Research Report – Segmented By Type (Digital Content Management, Stadium & Public Security, Building Automation, Event Management, Network Management, Crowd Management), Application (Government, Schools, Others), and Region – Global Industry Forecast (2022 - 2027)

Published: April, 2022
ID: 13002
Pages: 150

Artificial Intelligence (AI) in Stadium Market Size (2022 – 2027)

The Global AI in Stadium Market was worth US$ 1.4 billion in 2021 and is anticipated to reach the valuation of US$ 19.2 billion by 2027 and is predicted to register a CAGR of 30.3% during 2022-2027. The market's expansion can be ascribed to the growing need for Artificial Intelligence in stadiums owned by the government, schools, and other applications on a global scale.

Artificial Intelligence is the simulation of human intelligence processes by machines, particularly computer systems. Some examples of AI applications are Expert systems, natural language processing, speech recognition, and machine vision. In general, AI systems work by consuming vast volumes of labelled training data, analyzing the data for correlations and patterns, and then predicting future states using these patterns. By examining millions of examples, a chatbot fed examples of text chats learns to make lifelike exchanges with people, and an image recognition programme can learn to recognize and describe items in the pictures. Learning, reasoning, and self-correction are the three cognitive processes of AI programming.

The global COVID-19 pandemic of 2020, which is still wreaking havoc on the world, has not only forced the sports industry to reconsider how we build and design live sports entertainment, but it has also shaken the faith of fans who still want the power of togetherness but are concerned about the safety of attending live sports. The "return to play" has compelled everyone involved in sports, from the professionals who put on the events to the fans who cheer them on, to reconsider our values and the role that technology plays in bringing us all back together.

Stadium operators and sports properties must adapt their mindsets regarding the design of the fan experience, as well as the new pandemic-related concerns that must be addressed in order to maintain fan health, safety, and security. AI delivers a set of problem-solving tools that will play a key part in this transformation. Artificial intelligence (AI) is the future of sports stadium infrastructure, replacing traditional building and repair processes and using data solutions to offer a healthier, safer, and more secure live sports environment for fans. Sports stadiums must rethink AI technologies as a new form of infrastructure to meet the requirements of fans, solving challenges that were previously solved with brick, mortar, pipe, and personnel.


The global artificial intelligence in stadium market size is growing due to increased demand for player monitoring and tracking data, need for chatbots and virtual assistants to communicate with fans, and the need of real-time data analysis to improve performance. Rising returns on investment, technological developments, and an increase in the number of sporting events are the main drivers of industry expansion. A growing number of stadium visitors are expecting a more intuitive experience, and the host country is searching for new methods to boost the complex's return on investment.

Statistics and data analysis have always been employed in the sports industry. In sports, everything that can be quantified has previously been quantified, making it a fertile ground for artificial intelligence applications. Artificial intelligence (AI) has a daily impact on humans, and its impact on sports has remained rather consistent. Here are a few examples of how AI is affecting the esports sector. The combination of sensor technology and artificial intelligence (AI) aids in the advancement of player technology. To improve the effectiveness of each exercise for each individual, sports training AI is utilized to deliver real-time feedback and generate individualized training plans for players. Sports can benefit from AI predictive analytics to improve their health and fitness. The wearable app can also provide information about the player's tears and tensions, which can help them avoid injury.

All these factors combined together are leading to increase in global AI in Stadium Market volume.


The high initial cost appears to be the most significant impediment to this technology's adoption. This cost includes hardware, software, resources, certification, education, and personnel training. Traditional processes are more expensive in terms of money and resources than setting up systems. Due to the cancellation of sports contests and the closing of stadiums around the world, as well as government lockdown measures and other restrictions, demand for AI in sports has decreased significantly. During the pandemic, the use of chatbots and virtual assistants improved contact with fans and increased the number of followers. The amount of money spent on developing AI technology for sports has decreased significantly. Following the pandemic, investments are projected to rise.

Segmentation Analysis

Global AI in Stadium Market - By Type:

  • Digital Content Management
  • Stadium & Public Security
  • Building Automation
  • Event Management
  • Network Management
  • Crowd Management

With the biggest market share, the Digital Content Management sector is predicted to develop significantly and dominate the global market throughout the forecast period because it helps in streamlining the digital content production and distribution.

Global AI in Stadium Market - By Application:

  • Government
  • Schools
  • Others

In the global market, the government component has the biggest market share and is expected to increase at a rapid rate between 2022 and 2027.

Global AI in Stadium Market – By Region: 

  • North America
  • Latin America
  • Europe
  • Asia Pacific
  • Middle East & Africa

Over the period 2022-2027, North America is expected to dominate the AI in stadium market in, and it is likely to continue to do so during the coming years ahead as well, owing to the availability of AI in sports solutions vendors such as Microsoft Corporation, IBM, and SAS, which are assisting the artificial intelligence in sports market's expansion.

However, due to increased technical expenditures in industries such as cloud and digital technologies, Asia-Pacific is predicted to rise significantly during the forecast period.

Key Players

  1. Allgovision Technologies Pvt.
  2. Byrom Plc
  3. Centurylink
  4. Cisco Systems
  5. Dignia Systems
  6. Ericsson Ab
  7. Fujitsu
  8. Gp Smart Stadium
  9. Hawk-Eye
  10. Huawei Enterprise

Recent Developments:

  • With the start of baseball season, a slew of new mobile payment and self-service alternatives have been announced at Major League Baseball (MLB) stadiums. Instacart announced the activation of a new POS system at Fenway Park in Boston on April 20, 2022.The Caper Counter is a system designed by Caper AI, a software startup that provides checkout systems and other artificial intelligence (AI) retail technology that Instacart bought in the fall. Consumers place their purchases on the Counter, which scans them with computer vision before allowing them to choose their payment method.
  • QTnet has announced that its eSport Challenger's Park would be powered by Juniper Networks' wired, wireless, and security solutions. With a secure Juniper AI-driven network, the Japanese telecommunications service provider claims that their facility is a place where both professional athletes and the general public may engage in sports gaming. QTnet entered the eSports market as part of its diversification plan by acquiring Sengoku Co., Ltd. in 2020, which owns Sengoku Gaming, one of Japan's top professional eSports teams. Furthermore, QTnet's building is now Sengoku Gaming's home stadium.

1. Introduction                                 

                1.1 Market Definition                    

                1.2 Scope of the report                 

                1.3 Study Assumptions                 

                1.4 Base Currency, Base Year and Forecast Periods                           

2. Research Methodology                                           

                2.1 Analysis Design                         

                2.2 Research Phases                      

                                2.2.1 Secondary Research           

                                2.2.2 Primary Research 

                                2.2.3 Data Modelling     

                                2.2.4 Expert Validation  

                2.3 Study Timeline                          

3. Report Overview                                        

                3.1 Executive Summary                

                3.2 Key Inferencees                       

4. Market Dynamics                                       

                4.1 Impact Analysis                        

                                4.1.1 Drivers      

                                4.1.2 Restaints 

                                4.1.3 Opportunities        

                4.2 Regulatory Environment                       

                4.3 Technology Timeline & Recent Trends                            

5. Competitor Benchmarking Analysis                                    

                5.1 Key Player Benchmarking                     

                                5.1.1 Market share analysis         

                                5.1.2 Products/Service 

                                5.1.3 Regional Presence

                5.2 Mergers & Acquistion Landscape                      

                5.3 Joint Ventures & Collaborations                        

6. Market Segmentation                                              

                6.1 AI in Stadium Market , By Type                          

                                6.1.1 Digital Content Management         

                                6.1.2 Stadium & Public Security

                                6.1.3 Building Automation          

                                6.1.4 Event Management            

                                6.1.5 Network Management      

                                6.1.6 Crowd Management          

                                6.1.7 Market Size Estimations & Forecasts (2022-2027)   

                                6.1.8 Y-o-Y Growth Rate Analysis              

                                6.1.9 Market Attractiveness Index           

                6.2 AI in Stadium Market , By Application                              

                                6.2.1 Government          

                                6.2.2 Schools     

                                6.2.3 Others      

                                6.2.4 Market Size Estimations & Forecasts (2022-2027)   

                                6.2.5 Y-o-Y Growth Rate Analysis              

                                6.2.6 Market Attractiveness Index           

7. Geographical Landscape                                         

                7.1 Global AI in Stadium Market , by Region                        

                7.2 North America - Market Analysis (2022-2027)                              

                                7.2.1 By Country              



                                7.2.2 By Type    

                                7.2.3 By Application       

                7.3 Europe                         

                                7.3.1 By Country              






                                       Rest of Europe

                                7.3.2 By Type    

                                7.3.3 By Application       

                7.4 Asia Pacific                  

                                7.4.1 By Country              




                                       South Korea

                                       South East Asia

                                       Australia & NZ

                                       Rest of Asia-Pacific

                                7.4.2 By Type    

                                7.4.3 By Application       

                7.5 Latin America                            

                                7.5.1 By Country              




                                       Rest of Latin America

                                7.5.2 By Type    

                                7.5.3 By Application       

                7.6 Middle East and Africa                           

                                7.6.1 By Country              

                                       Middle East


                                7.6.2 By Type    

                                7.6.3 By Application       

8. Key Player Analysis                                    

                8.1 Allgovision Technologies Pvt.                              

                                8.1.1 Business Description           

                                8.1.2 Products/Service 

                                8.1.3 Financials 

                                8.1.4 SWOT Analysis      

                                8.1.5 Recent Developments       

                                8.1.6 Analyst Overview 

                8.2 Byrom Plc                    

                8.3 Centurylink                

                8.4 Cisco Systems                           

                8.5 Dignia Systems                         

                8.6 Ericsson Ab                 

                8.7 Fujitsu                          

                8.8 Gp Smart Stadium                   

                8.9 Hawk-Eye                   

                8.10 Huawei Enterprise                

9. Market Outlook & Investment Opportunities                                 


                List of Tables                     

                List of Figures                   

  1. Global AI in Stadium Market By Region, From 2022-2027 ( USD Billion )
  2. Global AI in Stadium Market By Type, From 2022-2027 ( USD Billion )
  3. Global Digital Content Management Market By Region, From 2022-2027 ( USD Billion )
  4. Global Stadium & Public Security Market By Region, From 2022-2027 ( USD Billion )
  5. Global Building Automation Market By Region, From 2022-2027 ( USD Billion )
  6. Global Event Management Market By Region, From 2022-2027 ( USD Billion )
  7. Global Network Management Market By Region, From 2022-2027 ( USD Billion )
  8. Global Crowd Management Market By Region, From 2022-2027 ( USD Billion )
  9. Global AI in Stadium Market By Application, From 2022-2027 ( USD Billion )
  10. Global Government Market By Region, From 2022-2027 ( USD Billion )
  11. Global Schools Market By Region, From 2022-2027 ( USD Billion )
  12. Global Others Market By Region, From 2022-2027 ( USD Billion )

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How will the AI in Stadium Market change in the next five years?

The AI in Stadium Market is expected to register a CAGR of 30.3% and reach the valuation of US$ 19.2 billion by the year 2027.

Mention the market which has the largest share in the AI in Stadium market?

Currently, North America dominates the market and is expected to do the same in the coming years.

Which regional market will show the highest growth rate during the forecast period?

For the time period 2022-2027, Asia Pacific is predicted to rise significantly in the AI in Stadium Market.

What is the major effecting factor in the global AI in stadium market?

Growing expectations of spectators for a better stadium experience is driving the AI in Stadium Market growth.




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