Global Artificial Intelligence in Supply Chain Market Insights, Size & Growth Forecast To 2027

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Global Artificial Intelligence in Supply Chain Market- By Application (Robotics & Factory Automation, Planning & Market Demand Forecast, Commerce & Financial data, Cyber Security, Customer service, Other), By Type (Software, Hardware, Others Services), By Function (On-premise, Off-premise), By End-user (Automotive, Aerospace, Building Construction, Chemical, Others), and By Region (North America, Europe, Asia Pacific, South America, and Middle East, & Africa)- Global forecast from 2020-2027.
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Global Artificial Intelligence in Supply Chain Market- By Application (Robotics & Factory Automation, Planning & Market Demand Forecast, Commerce & Financial data, Cyber Security, Customer service, Other), By Type (Software, Hardware, Others Services), By Function (On-premise, Off-premise), By End-user (Automotive, Aerospace, Building Construction, Chemical, Others), and By Region (North America, Europe, Asia Pacific, South America, and Middle East, & Africa)- Global forecast from 2020-2027.

Published: Apr 2021 Base Year: 2020 Report ID: IACT2124
Available Format: Historical Data: 2018 - 2019 Number of Pages: 1 - 250
Category : Information & Communications Technology
The Global Artificial Intelligence in Supply chain market spurring the market growth is due to emerging big data and the need for better decision making. The global artificial intelligence in supply chain market has the potential to grow with USD 21.2 billion and with bolstering CAGR in the forecast period from 2020-2027. The growing demand for AI in the supply chain market is mainly due to the increasing awareness of artificial intelligence, big data and analysis, and the continuous expansion of the scope of computer vision in autonomous and semi-autonomous applications.
With artificial intelligence technology embedded in a self-learning supply chain, the machine will be able to check the supply chain strategy to determine the location and cause of supply chain errors, as well as related external combination factors such as loyalty, inventory levels, weather, competition Opponent's events, market performance, traffic or socio-economic events, etc. Then, machine learning algorithms will shift through the data and understand how these factors interact to cause supply chain errors.
Moreover, the growth of the supply chain department attributed to the growing demand for strengthening factory scheduling and production planning, as well as continually developing agility and optimization of supply chain decisions. Also, digitizing existing operations and workflows to reshape the supply chain planning model also contributed to the growth in this area.

Application overview in the Global Artificial Intelligence in Supply chain Market
Based on the application, the global Artificial Intelligence in the Supply Chain market segmented into Robotics & Factory Automation, Planning & Market Demand Forecast, Commerce & Financial Data, Cyber Security, Customer service, Other. The planning and market demand segment has captured the highest market value in the worldwide artificial intelligence in the supply chain in the forecast period from 2020-2027. The supply chain uses artificial intelligence for planning and forecasting market demand to enhance the future operations ad forecasting.

Type overview in the Global Artificial Intelligence in Supply Chain Market
Based on the type, the global Artificial Intelligence in the Supply Chain market classified into Software, Hardware, Other Services. The software segment will dominate the global artificial intelligence in supply chain market. It is mainly owing to providing solutions such as inventory control management, order procurement, and other functions required for the efficient supply chain management. 

Function overview in the Global Artificial Intelligence in Supply Chain Market
Based on the function, the global Artificial Intelligence in the Supply Chain market categorized into On-premise, Off-premise. The on-premise segment will capture the largest share in the global artificial intelligence in supply chain market. The on-premise function helps in reducing the cost of storing data, improve flexibility, and scalability.

End-user Overview in the Global Artificial Intelligence in Supply Chain Market
Based on the End-user, the global Artificial Intelligence in Supply Chain market segmented into Automotive, Aerospace, Building Construction, Chemical, Others. The other (retail) segment will bolster the market share of the global artificial intelligence in the supply chain market. The retail sector is emerging is demand owing to improving customer experience and enhance the forecast of demand accurately.

Region Overview in the Global Artificial Intelligence in Supply Chain Market
Based on geography, the global Artificial Intelligence in Supply Chain market segmented into North America, Asia Pacific, Europe, South America, and Middle East & Africa. The Asia Pacific expected to hold the largest share of global artificial intelligence in the supply chain market. The rising disposable income, increasing penetration of the internet, and the emerging manufacturing and retail industry for improving the supply chain will fuel the market share of the global artificial intelligence in the supply chain market.

Global Artificial Intelligence in Supply Chain Market: Competitive Landscape
Companies such as IBM, Siemens, NVIDIA, Spotify, Microsoft, Google, Intel, Salesforce, Shell, GE Ventures, Samsung, Bloomberg Beta, RapidMiner, Tesla, and others are key players in the global Artificial Intelligence in Supply Chain market.



1. Research Strategic Development
1.1. Market Modelling
1.2. Product Analysis
1.3. Market Trend and Economic Factors Analysis
1.4. Market Segmental Analysis
1.5. Geographical Mapping
1.6. Country Wise Segregation

2. Research Methodology
2.1. Identification of Target Market
2.2. Data Acquisition 
2.3. Refining of Data/ Data Transformations
2.4. Data Validation through Primary Techniques
2.5. Exploratory Data Analysis
2.6. Graphical Techniques/Analysis
2.7. Quantitative Techniques/Analysis
2.8. Visual Result/Presentation 

3. Executive Summary

4. Market Insights
4.1. Economic Factor Analysis 
4.1.1. Drivers
4.1.2. Trends
4.1.3. Opportunities
4.1.4. Challenges
4.2. Competitors & Product Analysis
4.3. Regulatory Framework
4.4. Company market share analysis, 2019
4.5. Porter’s Five forces analysis
4.6. New Investment Analysis
4.7. PESTEL Analysis

5. Global Artificial Intelligence in Supply Chain Market Overview
  • 5.1. Market Size & Forecast, 2016-2027
  • 5.1.1. Demand
  • 5.1.1.1. By Value (USD Million)
  • 5.2. Market Share & Forecast, 2016-2027
  • 5.2.1. By Application
  • 5.2.1.1. Robotics & Factory Automation
  • 5.2.1.2. Planning & Market Demand Forecast
  • 5.2.1.3. Commerce & Financial data
  • 5.2.1.4. Cyber Security
  • 5.2.1.5. Customer service
  • 5.2.1.6. Other
  • 5.2.2. By Type
  • 5.2.2.1. Software
  • 5.2.2.2. Hardware
  • 5.2.2.3. Others Services
  • 5.2.3. By Function
  • 5.2.3.1. On-premise
  • 5.2.3.2. Off-premise
  • 5.2.4. By End-User
  • 5.2.4.1. Automotive
  • 5.2.4.2. Aerospace   
  • 5.2.4.3. Building Construction 
  • 5.2.4.4. Chemical
  • 5.2.4.5. Others 
  • 5.2.5. By Region
  • 5.2.5.1. Europe
  • 5.2.5.2. North America
  • 5.2.5.3. Asia Pacific
  • 5.2.5.4. South America 
  • 5.2.5.5. Middle East & Africa 

6. Europe Artificial Intelligence in Supply Chain Market Overview
6.1. Europe Artificial Intelligence in Supply Chain Market Size & Forecast, 2016-2027
6.1.1. Demand
6.1.1.1. By Value (USD Million)
6.2. Europe Artificial Intelligence in Supply Chain Market Share & Forecast, 2016-2027
6.2.1. By Application
6.2.1.1. Robotics & Factory Automation
6.2.1.2. Planning & Market Demand Forecast
6.2.1.3. Commerce & Financial data
6.2.1.4. Cyber Security
6.2.1.5. Customer service
6.2.1.6. Other
6.2.2. By Type
6.2.2.1. Software
6.2.2.2. Hardware
6.2.2.3. Others Services
6.2.3. By Function
6.2.3.1. On-premise
6.2.3.2. Off-premise
6.2.4. By End-User
6.2.4.1. Automotive
6.2.4.2. Aerospace   
6.2.4.3. Building Construction 
6.2.4.4. Chemical
6.2.4.5. Others 
6.2.5. By Country
6.2.5.1. Germany
6.2.5.2. UK
6.2.5.3. France
6.2.5.4. Italy
6.2.5.5. Rest of Europe
6.2.6. Company Market Share (Top 3-5)
6.2.7. Economic Impact Study on Europe Artificial Intelligence in Supply Chain Market 

7. North America Artificial Intelligence in Supply Chain Market Overview
7.1. North America Artificial Intelligence in Supply Chain Market Size & Forecast, 2016-2027
7.1.1. Demand
7.1.1.1. By Value (USD Million)
7.2. North America Artificial Intelligence in Supply Chain Market Share & Forecast, 2016-2027
7.2.1. By Application
7.2.1.1. Robotics & Factory Automation
7.2.1.2. Planning & Market Demand Forecast
7.2.1.3. Commerce & Financial data
7.2.1.4. Cyber Security
7.2.1.5. Customer service
7.2.1.6. Other
7.2.2. By Type
7.2.2.1. Software
7.2.2.2. Hardware
7.2.2.3. Others Services
7.2.3. By Function
7.2.3.1. On-premise
7.2.3.2. Off-premise
7.2.4. By End-User
7.2.4.1. Automotive
7.2.4.2. Aerospace   
7.2.4.3. Building Construction 
7.2.4.4. Chemical
7.2.4.5. Others 
7.2.5. By Country
7.2.5.1. US
7.2.5.2. Canada
7.2.5.3. Mexico
7.2.6. Company Market Share (Top 3-5)
7.2.7. Economic Impact Study on North America Artificial Intelligence in Supply Chain Market 

8. Asia Pacific Artificial Intelligence in Supply Chain Market Overview
8.1. Asia Pacific Artificial Intelligence in Supply Chain Market Size & Forecast, 2016-2027
8.1.1. Demand
8.1.1.1. By Value (USD Million)
8.2. Asia Pacific Artificial Intelligence in Supply Chain Market Share & Forecast, 2016-2027
8.2.1. By Application
8.2.1.1. Robotics & Factory Automation
8.2.1.2. Planning & Market Demand Forecast
8.2.1.3. Commerce & Financial data
8.2.1.4. Cyber Security
8.2.1.5. Customer service
8.2.1.6. Other
8.2.2. By Type
8.2.2.1. Software
8.2.2.2. Hardware
8.2.2.3. Others Services
8.2.3. By Function
8.2.3.1. On-premise
8.2.3.2. Off-premise
8.2.4. By End-User
8.2.4.1. Automotive
8.2.4.2. Aerospace   
8.2.4.3. Building Construction 
8.2.4.4. Chemical
8.2.4.5. Others 
8.2.5. By Country
8.2.5.1. China
8.2.5.2. India
8.2.5.3. Japan
8.2.5.4. Australia
8.2.5.5. Rest of Asia Pacific
8.2.6. Company Market Share (Top 3-5)
8.2.7. Economic Impact Study on Asia Pacific Artificial Intelligence in Supply Chain Market 

9. South America Artificial Intelligence in Supply Chain Market Overview
9.1. South America Artificial Intelligence in Supply Chain Market Size & Forecast, 2016-2027
9.1.1. Demand
9.1.1.1. By Value (USD Million)
9.2. South America Artificial Intelligence in Supply Chain Market Share & Forecast, 2016-2027
9.2.1. By Application
9.2.1.1. Robotics & Factory Automation
9.2.1.2. Planning & Market Demand Forecast
9.2.1.3. Commerce & Financial data
9.2.1.4. Cyber Security
9.2.1.5. Customer service
9.2.1.6. Other
9.2.2. By Type
9.2.2.1. Software
9.2.2.2. Hardware
9.2.2.3. Others Services
9.2.3. By Function
9.2.3.1. On-premise
9.2.3.2. Off-premise
9.2.4. By End-User
9.2.4.1. Automotive
9.2.4.2. Aerospace   
9.2.4.3. Building Construction 
9.2.4.4. Chemical
9.2.4.5. Others 
9.2.5. By Country
9.2.5.1. Brazil
9.2.5.2. Argentina
9.2.5.3. Rest of South America
9.2.6. Company Market Share (Top 3-5)
9.2.7. Economic Impact Study on South America Artificial Intelligence in Supply Chain Market

10. Middle East & Africa Artificial Intelligence in Supply Chain Market Overview
10.1. Middle East & Africa Artificial Intelligence in Supply Chain Market Size & Forecast, 2016-2027
10.1.1. Demand
10.1.1.1. By Value (USD Million)
10.2. Middle East & Africa Artificial Intelligence in Supply Chain Market Share & Forecast, 2016-2027
10.2.1. By Application
10.2.1.1. Robotics & Factory Automation
10.2.1.2. Planning & Market Demand Forecast
10.2.1.3. Commerce & Financial data
10.2.1.4. Cyber Security
10.2.1.5. Customer service
10.2.1.6. Other
10.2.2. By Type
10.2.2.1. Software
10.2.2.2. Hardware
10.2.2.3. Others Services
10.2.3. By Function
10.2.3.1. On-premise
10.2.3.2. Off-premise
10.2.4. By End-User
10.2.4.1. Automotive
10.2.4.2. Aerospace   
10.2.4.3. Building Construction 
10.2.4.4. Chemical
10.2.4.5. Others 
10.2.5. By Country
10.2.5.1. Saudi Arabia
10.2.5.2. UAE
10.2.5.3. South Africa
10.2.5.4. Rest of Middle East & Africa
10.2.6. Company Market Share (Top 3-5)
10.2.7. Economic Impact Study on Middle East & Africa Artificial Intelligence in Supply Chain Market

11. Competitor Analysis
11.1. Company Description
11.2. Financial Analysis
11.3. Key Products
11.4. Key Management Personnel 
11.5. Contact Address
11.6. SWOT Analysis
11.7. Company Profile
11.7.1.1. IBM
11.7.1.2. Siemens
11.7.1.3. NVIDIA
11.7.1.4. Spotify
11.7.1.5. Microsoft
11.7.1.6. Google
11.7.1.7. Intel
11.7.1.8. Salesforce
11.7.1.9. Shell
11.7.1.10. GE Ventures
11.7.1.11. Samsung
11.7.1.12. Bloomberg Beta
11.7.1.13. RapidMiner
11.7.1.14. Tesla
11.7.1.15. Other players

SPER Market Research’s methodology uses great emphasis on primary research to ensure that the market intelligence insights are up to date, reliable and accurate. Primary interviews are done with players involved in each phase of a supply chain to analyze the market forecasting. The secondary research method is used to help you fully understand how the future markets and the spending patterns look likes.

The report is based on in-depth qualitative and quantitative analysis of the Global Product Market. The quantitative analysis involves the application of various projection and sampling techniques. The qualitative analysis involves primary interviews, surveys, and vendor briefings.  The data gathered as a result of these processes are validated through experts opinion. Our research methodology entails an ideal mixture of primary and secondary initiatives.

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