Market Overview:
Artificial intelligence (AI) is a process of programming a computer to make decisions for itself. It is an umbrella term that includes machine learning, natural language processing, and computer vision. AI has the ability to learn at scale and make predictions on its own. The global artificial intelligence in manufacturing and supply chain market was valued at US$ XX Mn in 2017 and is expected to reach US$ XX Mn by 2030, registering a CAGR of XX% during the forecast period 2018-2030. The growth of the global artificial intelligence in manufacturing and supply chain market can be attributed to various factors such as increasing demand for AI-enabled products, growing number of internet users, rising adoption of cloud-based solutions among small & medium enterprises (SMEs), increasing penetration of smartphones & tablets, etc.
Product Definition:
Artificial intelligence is a field of computer science and engineering focused on the creation of intelligent agents, which are systems that can reason, learn, and act autonomously.
On-premise:
On-premise is a term used for applications that are installed and run from the original equipment manufacturer (OEM) data centers or corporate servers. On-premise software solutions have significant demand in Artificial Intelligence (AI) in Manufacturing and Supply Chain (AMSC) market owing to their benefits such as easy integration with existing systems, cost effectiveness, high performance, security of information etc.
Cloud-based:
Cloud-based solutions are software and services that provide remote access to data and applications. It is a virtual environment where any individual can connect to the network at any place, irrespective of their location. The technology helps in accessing business applications, data, and documents from a distant site with the help of internet connection. It also helps in sharing information across multiple sites thus increasing productivity by reducing time spent on traveling for documentation or information gathering process.
Application Insights:
The application segment has been further categorized into automotive, chemicals, building construction, aerospace & defense and others. The building construction segment is expected to witness the highest growth over the forecast period owing to increasing demand for smart buildings and infrastructure. Artificial intelligence in manufacturing provides solutions in areas such as predictive maintenance, advanced process control and robotics-based automation.
Automotive was estimated as one of the prominent segments with a market share of 26.1% in 2017 owing to its wide applications across various industry verticals such as safety systems (airbags), infotainment systems/vehicle electronics, ADAS/AVL integration etcetera.
Regional Analysis:
The market in North America is expected to grow at a significant rate over the forecast period. The growth can be attributed to increasing investments in R&D and growing adoption of technologies across various industries. Moreover, presence of prominent players such as IBM Corporation; Google LLC; Microsoft Corporation; and Amazon Web Services, Inc. has led to increased usage of advanced AIs solutions across several industries in the region.
The Asia Pacific regional market is anticipated to witness substantial growth over the forecast period owing to increasing industrialization and rapid urbanization resulting into rising demand for consumer electronics products such as smartphones and laptops among others which require AI-based predictive maintenance services for efficient production workflow management process along with other downstream activities such as component manufacturing or repair services etc.
Growth Factors:
- Increasing demand for AI-enabled automation in manufacturing and supply chain processes to improve efficiency and productivity.
- Growing number of AI startups focused on developing innovative solutions for manufacturing and supply chain operations.
- Rising adoption of cloud-based platforms and services for deploying AI applications in manufacturing and supply chain ecosystems.
- Proliferation of big data technologies that are helping organizations harness the power of machine learning algorithms to improve decision making in manufacturing and supply chains.
- 0 initiatives that are promoting the use of smart factories, robotics, sensors, etc., which are enhancing the potential for AI applications in Manufacturing & Supply Chain
Scope Of The Report
Report Attributes
Report Details
Report Title
Artificial Intelligence in Manufacturing and Supply Chain Market Research Report
By Type
On-premise, Cloud-based
By Application
Automotive, Aerospace, Chemicals, Building Construction, Others
By Companies
IBM, Microsoft, Oracle, Google, SAS, SAP SE, Siemens, Salesforce, Cambridge Analytica, Civis Analytics, RapidMiner
Regions Covered
North America, Europe, APAC, Latin America, MEA
Base Year
2021
Historical Year
2019 to 2020 (Data from 2010 can be provided as per availability)
Forecast Year
2030
Number of Pages
212
Number of Tables & Figures
149
Customization Available
Yes, the report can be customized as per your need.
Global Artificial Intelligence in Manufacturing and Supply Chain Market Report Segments:
The global Artificial Intelligence in Manufacturing and Supply Chain market is segmented on the basis of:
Types
On-premise, Cloud-based
The product segment provides information about the market share of each product and the respective CAGR during the forecast period. It lays out information about the product pricing parameters, trends, and profits that provides in-depth insights of the market. Furthermore, it discusses latest product developments & innovation in the market.
Applications
Automotive, Aerospace, Chemicals, Building Construction, Others
The application segment fragments various applications of the product and provides information on the market share and growth rate of each application segment. It discusses the potential future applications of the products and driving and restraining factors of each application segment.
Some of the companies that are profiled in this report are:
- IBM
- Microsoft
- Oracle
- SAS
- SAP SE
- Siemens
- Salesforce
- Cambridge Analytica
- Civis Analytics
- RapidMiner
Highlights of The Artificial Intelligence in Manufacturing and Supply Chain Market Report:
- The market structure and projections for the coming years.
- Drivers, restraints, opportunities, and current trends of market.
- Historical data and forecast.
- Estimations for the forecast period 2030.
- Developments and trends in the market.
- By Type:
- On-premise
- Cloud-based
- By Application:
- Automotive
- Aerospace
- Chemicals
- Building Construction
- Others
- Market scenario by region, sub-region, and country.
- Market share of the market players, company profiles, product specifications, SWOT analysis, and competitive landscape.
- Analysis regarding upstream raw materials, downstream demand, and current market dynamics.
- Government Policies, Macro & Micro economic factors are also included in the report.
We have studied the Artificial Intelligence in Manufacturing and Supply Chain Market in 360 degrees via. both primary & secondary research methodologies. This helped us in building an understanding of the current market dynamics, supply-demand gap, pricing trends, product preferences, consumer patterns & so on. The findings were further validated through primary research with industry experts & opinion leaders across countries. The data is further compiled & validated through various market estimation & data validation methodologies. Further, we also have our in-house data forecasting model to predict market growth up to 2030.
Regional Analysis
- North America
- Europe
- Asia Pacific
- Middle East & Africa
- Latin America
Note: A country of choice can be added in the report at no extra cost. If more than one country needs to be added, the research quote will vary accordingly.
The geographical analysis part of the report provides information about the product sales in terms of volume and revenue in regions. It lays out potential opportunities for the new entrants, emerging players, and major players in the region. The regional analysis is done after considering the socio-economic factors and government regulations of the countries in the regions.
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8 Reasons to Buy This Report
- Includes a Chapter on the Impact of COVID-19 Pandemic On the Market
- Report Prepared After Conducting Interviews with Industry Experts & Top Designates of the Companies in the Market
- Implemented Robust Methodology to Prepare the Report
- Includes Graphs, Statistics, Flowcharts, and Infographics to Save Time
- Industry Growth Insights Provides 24/5 Assistance Regarding the Doubts in the Report
- Provides Information About the Top-winning Strategies Implemented by Industry Players.
- In-depth Insights On the Market Drivers, Restraints, Opportunities, and Threats
- Customization of the Report Available
Frequently Asked Questions?
Artificial intelligence (AI) is a subset of machine learning that uses computer programs to make decisions, typically in the absence of human input. In manufacturing and supply chain contexts, AI can be used to automate decision-making processes or help identify potential problems before they become major issues.
Some of the major players in the artificial intelligence in manufacturing and supply chain market are IBM, Microsoft, Oracle, Google, SAS, SAP SE, Siemens, Salesforce, Cambridge Analytica, Civis Analytics, RapidMiner.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Artificial Intelligence in Manufacturing and Supply Chain Market Overview 4.1 Introduction 4.1.1 Market Taxonomy 4.1.2 Market Definition 4.1.3 Macro-Economic Factors Impacting the Market Growth 4.2 Artificial Intelligence in Manufacturing and Supply Chain Market Dynamics 4.2.1 Market Drivers 4.2.2 Market Restraints 4.2.3 Market Opportunity 4.3 Artificial Intelligence in Manufacturing and Supply Chain Market - Supply Chain Analysis 4.3.1 List of Key Suppliers 4.3.2 List of Key Distributors 4.3.3 List of Key Consumers 4.4 Key Forces Shaping the Artificial Intelligence in Manufacturing and Supply Chain Market 4.4.1 Bargaining Power of Suppliers 4.4.2 Bargaining Power of Buyers 4.4.3 Threat of Substitution 4.4.4 Threat of New Entrants 4.4.5 Competitive Rivalry 4.5 Global Artificial Intelligence in Manufacturing and Supply Chain Market Size & Forecast, 2020-2028 4.5.1 Artificial Intelligence in Manufacturing and Supply Chain Market Size and Y-o-Y Growth 4.5.2 Artificial Intelligence in Manufacturing and Supply Chain Market Absolute $ Opportunity
Chapter 5 Global Market Analysis and Forecast by Type
5.1 Introduction
5.1.1 Key Market Trends & Growth Opportunities by Type
5.1.2 Basis Point Share (BPS) Analysis by Type
5.1.3 Absolute $ Opportunity Assessment by Type
5.2 Market Size Forecast by Type
5.2.1 On-premise
5.2.2 Cloud-based
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Market Analysis and Forecast by Applications
6.1 Introduction
6.1.1 Key Market Trends & Growth Opportunities by Applications
6.1.2 Basis Point Share (BPS) Analysis by Applications
6.1.3 Absolute $ Opportunity Assessment by Applications
6.2 Market Size Forecast by Applications
6.2.1 Automotive
6.2.2 Aerospace
6.2.3 Chemicals
6.2.4 Building Construction
6.2.5 Others
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Artificial Intelligence in Manufacturing and Supply Chain Market Analysis and Forecast by Region
7.1 Introduction
7.1.1 Key Market Trends & Growth Opportunities by Region
7.1.2 Basis Point Share (BPS) Analysis by Region
7.1.3 Absolute $ Opportunity Assessment by Region
7.2 Artificial Intelligence in Manufacturing and Supply Chain Market Size Forecast by Region
7.2.1 North America
7.2.2 Europe
7.2.3 Asia Pacific
7.2.4 Latin America
7.2.5 Middle East & Africa (MEA)
7.3 Market Attractiveness Analysis by Region
Chapter 8 Coronavirus Disease (COVID-19) Impact
8.1 Introduction
8.2 Current & Future Impact Analysis
8.3 Economic Impact Analysis
8.4 Government Policies
8.5 Investment Scenario
Chapter 9 North America Analysis and Forecast
9.1 Introduction
9.2 North America Market Size Forecast by Country
9.2.1 U.S.
9.2.2 Canada
9.3 Basis Point Share (BPS) Analysis by Country
9.4 Absolute $ Opportunity Assessment by Country
9.5 Market Attractiveness Analysis by Country
9.6 North America Market Size Forecast by Type
9.6.1 On-premise
9.6.2 Cloud-based
9.7 Basis Point Share (BPS) Analysis by Type
9.8 Absolute $ Opportunity Assessment by Type
9.9 Market Attractiveness Analysis by Type
9.10 North America Market Size Forecast by Applications
9.10.1 Automotive
9.10.2 Aerospace
9.10.3 Chemicals
9.10.4 Building Construction
9.10.5 Others
9.11 Basis Point Share (BPS) Analysis by Applications
9.12 Absolute $ Opportunity Assessment by Applications
9.13 Market Attractiveness Analysis by Applications
Chapter 10 Europe Analysis and Forecast
10.1 Introduction
10.2 Europe Market Size Forecast by Country
10.2.1 Germany
10.2.2 France
10.2.3 Italy
10.2.4 U.K.
10.2.5 Spain
10.2.6 Russia
10.2.7 Rest of Europe
10.3 Basis Point Share (BPS) Analysis by Country
10.4 Absolute $ Opportunity Assessment by Country
10.5 Market Attractiveness Analysis by Country
10.6 Europe Market Size Forecast by Type
10.6.1 On-premise
10.6.2 Cloud-based
10.7 Basis Point Share (BPS) Analysis by Type
10.8 Absolute $ Opportunity Assessment by Type
10.9 Market Attractiveness Analysis by Type
10.10 Europe Market Size Forecast by Applications
10.10.1 Automotive
10.10.2 Aerospace
10.10.3 Chemicals
10.10.4 Building Construction
10.10.5 Others
10.11 Basis Point Share (BPS) Analysis by Applications
10.12 Absolute $ Opportunity Assessment by Applications
10.13 Market Attractiveness Analysis by Applications
Chapter 11 Asia Pacific Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Market Size Forecast by Country
11.2.1 China
11.2.2 Japan
11.2.3 South Korea
11.2.4 India
11.2.5 Australia
11.2.6 South East Asia (SEA)
11.2.7 Rest of Asia Pacific (APAC)
11.3 Basis Point Share (BPS) Analysis by Country
11.4 Absolute $ Opportunity Assessment by Country
11.5 Market Attractiveness Analysis by Country
11.6 Asia Pacific Market Size Forecast by Type
11.6.1 On-premise
11.6.2 Cloud-based
11.7 Basis Point Share (BPS) Analysis by Type
11.8 Absolute $ Opportunity Assessment by Type
11.9 Market Attractiveness Analysis by Type
11.10 Asia Pacific Market Size Forecast by Applications
11.10.1 Automotive
11.10.2 Aerospace
11.10.3 Chemicals
11.10.4 Building Construction
11.10.5 Others
11.11 Basis Point Share (BPS) Analysis by Applications
11.12 Absolute $ Opportunity Assessment by Applications
11.13 Market Attractiveness Analysis by Applications
Chapter 12 Latin America Analysis and Forecast
12.1 Introduction
12.2 Latin America Market Size Forecast by Country
12.2.1 Brazil
12.2.2 Mexico
12.2.3 Rest of Latin America (LATAM)
12.3 Basis Point Share (BPS) Analysis by Country
12.4 Absolute $ Opportunity Assessment by Country
12.5 Market Attractiveness Analysis by Country
12.6 Latin America Market Size Forecast by Type
12.6.1 On-premise
12.6.2 Cloud-based
12.7 Basis Point Share (BPS) Analysis by Type
12.8 Absolute $ Opportunity Assessment by Type
12.9 Market Attractiveness Analysis by Type
12.10 Latin America Market Size Forecast by Applications
12.10.1 Automotive
12.10.2 Aerospace
12.10.3 Chemicals
12.10.4 Building Construction
12.10.5 Others
12.11 Basis Point Share (BPS) Analysis by Applications
12.12 Absolute $ Opportunity Assessment by Applications
12.13 Market Attractiveness Analysis by Applications
Chapter 13 Middle East & Africa (MEA) Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Market Size Forecast by Country
13.2.1 Saudi Arabia
13.2.2 South Africa
13.2.3 UAE
13.2.4 Rest of Middle East & Africa (MEA)
13.3 Basis Point Share (BPS) Analysis by Country
13.4 Absolute $ Opportunity Assessment by Country
13.5 Market Attractiveness Analysis by Country
13.6 Middle East & Africa (MEA) Market Size Forecast by Type
13.6.1 On-premise
13.6.2 Cloud-based
13.7 Basis Point Share (BPS) Analysis by Type
13.8 Absolute $ Opportunity Assessment by Type
13.9 Market Attractiveness Analysis by Type
13.10 Middle East & Africa (MEA) Market Size Forecast by Applications
13.10.1 Automotive
13.10.2 Aerospace
13.10.3 Chemicals
13.10.4 Building Construction
13.10.5 Others
13.11 Basis Point Share (BPS) Analysis by Applications
13.12 Absolute $ Opportunity Assessment by Applications
13.13 Market Attractiveness Analysis by Applications
Chapter 14 Competition Landscape
14.1 Artificial Intelligence in Manufacturing and Supply Chain Market: Competitive Dashboard
14.2 Global Artificial Intelligence in Manufacturing and Supply Chain Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 IBM
14.3.2 Microsoft
14.3.3 Oracle
14.3.4 Google
14.3.5 SAS
14.3.6 SAP SE
14.3.7 Siemens
14.3.8 Salesforce
14.3.9 Cambridge Analytica
14.3.10 Civis Analytics
14.3.11 RapidMiner