Global Machine Learning as a Service (MLaaS) Market is by Application (Marketing and Advertisement, Predictive Maintenance, Automated Network Management, Fraud Detection and Risk Analytics), Organization Size (Small and Medium Enterprises, Large Enterprises), End-User (IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI), Regional Forecasts 2021-2027
- Category: Internet & Telecom
- Published Date: Oct 2021
- Publisher: Bizwit Research
- Pages: 200
Global Machine Learning as a Service (MLaaS) Market to reach USD 16.7 billion by 2027.
Global Machine Learning as a Service (MLaaS) Market is valued approximately at USD 1.60 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 39.86% over the forecast period 2021-2027. Machine learning (ML) is a branch of artificial intelligence (AI) that involves a wide range of techniques for extracting meaningful models from raw data. It evolved from classical statistics and analysis. It takes skilled professionals to design these solutions since they are based on algorithms, model complexity, and computational complexity. The market growth is driven by the key factors such as growing adoption of Cloud-based Services, IoT and Automation. For instance, as per Statista, by the end of 2020, 79% of corporate respondents have said they were using Amazon Web Services (AWS) for public cloud usage. Hyperscalers, such as Amazon Web Services, Microsoft Azure, and Google Cloud, are among the most popular cloud computing platform providers worldwide. Also, as per the same source, In 2019, the worldwide revenue of the cloud infrastructure services industry was over 96 billion US dollars, with revenues from the preceding months including the fourth quarter of 2020 totaling 129 billion US dollars. Furthermore, the demand for MLaaS is expected to grow significantly over the forecast period, owing to the continuous growth of electronic sensors, linked devices, and equipment in the sector, which is supported by improvements in network connectivity technology. However, Privacy and Data Security Concerns, may impede market growth over the forecast period of 2021-2027.
North America is dominating the market and will continue be one over the projected period owing to the various factors such as growing use of cloud-based solutions by small and medium-sized businesses. Asia-Pacific, on the other hand, would have the greatest CAGR throughout this time period. This is due to the region's growing use of machine learning technologies and continued expansion in the IT sector.
Major market player included in this report are:
Fair Isaac Corporation (FICO)
Microsoft Corporation
Hewlett Packard Enterprise Company
Yottamine Analytics LLC
Amazon Web Services Inc.
Iflowsoft Solutions Inc.
IBM Corporation
SAS Institute Inc.
Google LLC
BigML Inc.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Application:
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
By Organization Size:
Small and Medium Enterprises
Large Enterprises
By End User:
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other End Users
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World
Furthermore, years considered for the study are as follows:
Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.
Target Audience of the Global Machine Learning as a Service (MLaaS) Market in Market Study:
Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors
Global Machine Learning as a Service (MLaaS) Market is valued approximately at USD 1.60 billion in 2020 and is anticipated to grow with a healthy growth rate of more than 39.86% over the forecast period 2021-2027. Machine learning (ML) is a branch of artificial intelligence (AI) that involves a wide range of techniques for extracting meaningful models from raw data. It evolved from classical statistics and analysis. It takes skilled professionals to design these solutions since they are based on algorithms, model complexity, and computational complexity. The market growth is driven by the key factors such as growing adoption of Cloud-based Services, IoT and Automation. For instance, as per Statista, by the end of 2020, 79% of corporate respondents have said they were using Amazon Web Services (AWS) for public cloud usage. Hyperscalers, such as Amazon Web Services, Microsoft Azure, and Google Cloud, are among the most popular cloud computing platform providers worldwide. Also, as per the same source, In 2019, the worldwide revenue of the cloud infrastructure services industry was over 96 billion US dollars, with revenues from the preceding months including the fourth quarter of 2020 totaling 129 billion US dollars. Furthermore, the demand for MLaaS is expected to grow significantly over the forecast period, owing to the continuous growth of electronic sensors, linked devices, and equipment in the sector, which is supported by improvements in network connectivity technology. However, Privacy and Data Security Concerns, may impede market growth over the forecast period of 2021-2027.
North America is dominating the market and will continue be one over the projected period owing to the various factors such as growing use of cloud-based solutions by small and medium-sized businesses. Asia-Pacific, on the other hand, would have the greatest CAGR throughout this time period. This is due to the region's growing use of machine learning technologies and continued expansion in the IT sector.
Major market player included in this report are:
Fair Isaac Corporation (FICO)
Microsoft Corporation
Hewlett Packard Enterprise Company
Yottamine Analytics LLC
Amazon Web Services Inc.
Iflowsoft Solutions Inc.
IBM Corporation
SAS Institute Inc.
Google LLC
BigML Inc.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Application:
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
By Organization Size:
Small and Medium Enterprises
Large Enterprises
By End User:
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other End Users
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World
Furthermore, years considered for the study are as follows:
Historical year – 2018, 2019
Base year – 2020
Forecast period – 2021 to 2027.
Target Audience of the Global Machine Learning as a Service (MLaaS) Market in Market Study:
Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors
Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Machine Learning as a Service (MLaaS) Market, by region, 2019-2027 (USD Billion)
1.2.2. Machine Learning as a Service (MLaaS) Market, by Application, 2019-2027 (USD Billion)
1.2.3. Machine Learning as a Service (MLaaS) Market, by Organisation Size, 2019-2027 (USD Billion)
1.2.4. Machine Learning as a Service (MLaaS) Market, by End User, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Machine Learning as a Service (MLaaS) Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Machine Learning as a Service (MLaaS) Market Dynamics
3.1. Machine Learning as a Service (MLaaS) Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Growing Adoption of Cloud-based Services
3.1.1.2. Growing Adoption of IoT and Automation
3.1.2. Market Restraint
3.1.2.1. Lack of skilled professionals
3.1.2.2. Privacy and Data Security Concerns
3.1.3. Market Opportunities
3.1.3.1. Increasing Investments in the Healthcare Industry
3.1.3.2. Emerging Options in Application Areas
Chapter 4. Global Machine Learning as a Service (MLaaS) Market: Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economic
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Machine Learning as a Service (MLaaS) Market, by Application
5.1. Market Snapshot
5.2. Global Machine Learning as a Service (MLaaS) Market by Application, Performance - Potential Analysis
5.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
5.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
5.4.1. Marketing and Advertisement
5.4.2. Predictive Maintenance
5.4.3. Automated Network Management
5.4.4. Fraud Detection and Risk Analytics
5.4.5. Other Applications
Chapter 6. Global Machine Learning as a Service (MLaaS) Market, by Organisation Size
6.1. Market Snapshot
6.2. Global Machine Learning as a Service (MLaaS) Market by Organisation Size, Performance - Potential Analysis
6.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by Organisation Size 2018-2027 (USD Billion)
6.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
6.4.1. Small and Medium Enterprises
6.4.2. Large Enterprises
Chapter 7. Global Machine Learning as a Service (MLaaS) Market, by End User
7.1. Market Snapshot
7.2. Global Machine Learning as a Service (MLaaS) Market by End User, Performance - Potential Analysis
7.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by End User 2018-2027 (USD Billion)
7.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
7.4.1. IT and Telecom
7.4.2. Automotive
7.4.3. Healthcare
7.4.4. Aerospace and Defence
7.4.5. Retail
7.4.6. Government
7.4.7. BFSI
7.4.8. Other End Users
Chapter 8. Global Machine Learning as a Service (MLaaS) Market, Regional Analysis
8.1. Machine Learning as a Service (MLaaS) Market, Regional Market Snapshot
8.2. North America Machine Learning as a Service (MLaaS) Market
8.2.1. U.S. Machine Learning as a Service (MLaaS) Market
8.2.1.1. Application breakdown estimates & forecasts, 2018-2027
8.2.1.2. Organisation Size breakdown estimates & forecasts, 2018-2027
8.2.1.3. End User breakdown estimates & forecasts, 2018-2027
8.2.2. Canada Machine Learning as a Service (MLaaS) Market
8.3. Europe Machine Learning as a Service (MLaaS) Market Snapshot
8.3.1. U.K. Machine Learning as a Service (MLaaS) Market
8.3.2. Germany Machine Learning as a Service (MLaaS) Market
8.3.3. France Machine Learning as a Service (MLaaS) Market
8.3.4. Spain Machine Learning as a Service (MLaaS) Market
8.3.5. Italy Machine Learning as a Service (MLaaS) Market
8.3.6. Rest of Europe Machine Learning as a Service (MLaaS) Market
8.4. Asia-Pacific Machine Learning as a Service (MLaaS) Market Snapshot
8.4.1. China Machine Learning as a Service (MLaaS) Market
8.4.2. India Machine Learning as a Service (MLaaS) Market
8.4.3. Japan Machine Learning as a Service (MLaaS) Market
8.4.4. Australia Machine Learning as a Service (MLaaS) Market
8.4.5. South Korea Machine Learning as a Service (MLaaS) Market
8.4.6. Rest of Asia Pacific Machine Learning as a Service (MLaaS) Market
8.5. Latin America Machine Learning as a Service (MLaaS) Market Snapshot
8.5.1. Brazil Machine Learning as a Service (MLaaS) Market
8.5.2. Mexico Machine Learning as a Service (MLaaS) Market
8.6. Rest of The World Machine Learning as a Service (MLaaS) Market
Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. Fair Isaac Corporation (FICO)
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. Microsoft Corporation
9.2.3. Hewlett Packard Enterprise Company
9.2.4. Yottamine Analytics LLC
9.2.5. Amazon Web Services Inc.
9.2.6. Iflowsoft Solutions Inc.
9.2.7. IBM Corporation
9.2.8. SAS Institute Inc.
9.2.9. Google LLC
9.2.10. BigML Inc.
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Machine Learning as a Service (MLaaS) Market, by region, 2019-2027 (USD Billion)
1.2.2. Machine Learning as a Service (MLaaS) Market, by Application, 2019-2027 (USD Billion)
1.2.3. Machine Learning as a Service (MLaaS) Market, by Organisation Size, 2019-2027 (USD Billion)
1.2.4. Machine Learning as a Service (MLaaS) Market, by End User, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Machine Learning as a Service (MLaaS) Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Machine Learning as a Service (MLaaS) Market Dynamics
3.1. Machine Learning as a Service (MLaaS) Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Growing Adoption of Cloud-based Services
3.1.1.2. Growing Adoption of IoT and Automation
3.1.2. Market Restraint
3.1.2.1. Lack of skilled professionals
3.1.2.2. Privacy and Data Security Concerns
3.1.3. Market Opportunities
3.1.3.1. Increasing Investments in the Healthcare Industry
3.1.3.2. Emerging Options in Application Areas
Chapter 4. Global Machine Learning as a Service (MLaaS) Market: Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2027)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economic
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
Chapter 5. Global Machine Learning as a Service (MLaaS) Market, by Application
5.1. Market Snapshot
5.2. Global Machine Learning as a Service (MLaaS) Market by Application, Performance - Potential Analysis
5.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
5.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
5.4.1. Marketing and Advertisement
5.4.2. Predictive Maintenance
5.4.3. Automated Network Management
5.4.4. Fraud Detection and Risk Analytics
5.4.5. Other Applications
Chapter 6. Global Machine Learning as a Service (MLaaS) Market, by Organisation Size
6.1. Market Snapshot
6.2. Global Machine Learning as a Service (MLaaS) Market by Organisation Size, Performance - Potential Analysis
6.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by Organisation Size 2018-2027 (USD Billion)
6.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
6.4.1. Small and Medium Enterprises
6.4.2. Large Enterprises
Chapter 7. Global Machine Learning as a Service (MLaaS) Market, by End User
7.1. Market Snapshot
7.2. Global Machine Learning as a Service (MLaaS) Market by End User, Performance - Potential Analysis
7.3. Global Machine Learning as a Service (MLaaS) Market Estimates & Forecasts by End User 2018-2027 (USD Billion)
7.4. Machine Learning as a Service (MLaaS) Market, Sub Segment Analysis
7.4.1. IT and Telecom
7.4.2. Automotive
7.4.3. Healthcare
7.4.4. Aerospace and Defence
7.4.5. Retail
7.4.6. Government
7.4.7. BFSI
7.4.8. Other End Users
Chapter 8. Global Machine Learning as a Service (MLaaS) Market, Regional Analysis
8.1. Machine Learning as a Service (MLaaS) Market, Regional Market Snapshot
8.2. North America Machine Learning as a Service (MLaaS) Market
8.2.1. U.S. Machine Learning as a Service (MLaaS) Market
8.2.1.1. Application breakdown estimates & forecasts, 2018-2027
8.2.1.2. Organisation Size breakdown estimates & forecasts, 2018-2027
8.2.1.3. End User breakdown estimates & forecasts, 2018-2027
8.2.2. Canada Machine Learning as a Service (MLaaS) Market
8.3. Europe Machine Learning as a Service (MLaaS) Market Snapshot
8.3.1. U.K. Machine Learning as a Service (MLaaS) Market
8.3.2. Germany Machine Learning as a Service (MLaaS) Market
8.3.3. France Machine Learning as a Service (MLaaS) Market
8.3.4. Spain Machine Learning as a Service (MLaaS) Market
8.3.5. Italy Machine Learning as a Service (MLaaS) Market
8.3.6. Rest of Europe Machine Learning as a Service (MLaaS) Market
8.4. Asia-Pacific Machine Learning as a Service (MLaaS) Market Snapshot
8.4.1. China Machine Learning as a Service (MLaaS) Market
8.4.2. India Machine Learning as a Service (MLaaS) Market
8.4.3. Japan Machine Learning as a Service (MLaaS) Market
8.4.4. Australia Machine Learning as a Service (MLaaS) Market
8.4.5. South Korea Machine Learning as a Service (MLaaS) Market
8.4.6. Rest of Asia Pacific Machine Learning as a Service (MLaaS) Market
8.5. Latin America Machine Learning as a Service (MLaaS) Market Snapshot
8.5.1. Brazil Machine Learning as a Service (MLaaS) Market
8.5.2. Mexico Machine Learning as a Service (MLaaS) Market
8.6. Rest of The World Machine Learning as a Service (MLaaS) Market
Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. Fair Isaac Corporation (FICO)
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. Microsoft Corporation
9.2.3. Hewlett Packard Enterprise Company
9.2.4. Yottamine Analytics LLC
9.2.5. Amazon Web Services Inc.
9.2.6. Iflowsoft Solutions Inc.
9.2.7. IBM Corporation
9.2.8. SAS Institute Inc.
9.2.9. Google LLC
9.2.10. BigML Inc.
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption
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