Market Overview:
The global machine learning as a service market is expected to grow from USD 1.02 billion in 2018 to USD 7.72 billion by 2030, at a CAGR of 27.5% during the forecast period. The growth of this market can be attributed to the increasing demand for machine learning services across industries and the growing need for predictive analytics and data-driven decision-making. However, lack of skilled workforce is one of the major factors restraining the growth of this market. Based on type, the global machine learning as a service market has been segmented into private clouds machine learning as a service, public clouds machine learning as a service, and hybrid cloud machine learning as a service.
Product Definition:
Machine Learning as a Service (MLaaS) is the ability to use Machine Learning algorithms without having to create or maintain the infrastructure. It is important because it allows businesses to use Machine Learning without having the expertise in-house.
Private Clouds Machine Learning as a Service:
Private clouds machine learning as a service is a new term used to define the set of services provided by companies that have their own private cloud. The major difference between public and private clouds is that in a public cloud, the data and applications are accessible to any user with an internet connection whereas in a private cloud, the data and applications are only accessible to authorized users.
Public Clouds Machine Learning as a Service:
Public cloud machine learning as a service (MLaaS) is a set of tools and services that help in running machine learning models. It helps in reducing the time required to train the model, deploying it on third party servers, and scaling up quickly. The MLaaS market is still at its nascent stage; however, there are several companies providing products for this market such as Amazon Web Services Inc., Google LLC., IBM Corporation among others.
Application Insights:
The personal application segment dominated the global machine learning as a service market in 2017. The increasing use of smartphones, social media and other online resources has led to an increased number of applications related to health, lifestyle and relationships. This has resulted in a higher demand for data analysis services across the globe. Furthermore, technological advancements such as big data analytics have led to an increased need for advanced data processing services that can process large datasets efficiently. This is expected to drive the growth of the personal application segment over the forecast period.
The business application segment is anticipated to witness significant growth over the forecast period owing to growing adoption across various industries such as financial services, retail and e-commerce among others which require real-time decisions based on historical data sets for risk assessment or underwriting purposes leading to high demand for predictive models trained with machine learning techniques among businesses globally driving their adoption hence contributing towards market revenue share significantly over time frame mentioned above.
Regional Analysis:
North America is expected to be the key regional market over the forecast period owing to significant investments in artificial intelligence and machine learning by companies such as Google, Microsoft, IBM, Amazon. These companies are making significant strategic investments in order to gain a competitive advantage. For instance, in February 2017, Google Inc. announced its plan for developing a new generation of AI hardware called Tensor Processing Units (TPU). The company plans to use these processors for various applications including speech and image recognition.
The Asia Pacific region is projected to exhibit high growth due with increasing adoption of cloud-based services across numerous industry verticals such as healthcare & life sciences; retail & e-commerce; telecom; transportation & logistics among others In addition it has been observed that countries like China.
Growth Factors:
- Increased demand for Machine Learning as a Service from small and medium businesses (SMBs) due to the increasing awareness of the benefits of machine learning.
- The growing popularity of cloud-based machine learning services, which makes it easier for businesses to adopt these services without making significant investments in infrastructure or manpower.
- Rapid advancements in artificial intelligence (AI) and machine learning technology, which are making these technologies more accessible and user-friendly, thereby driving wider adoption among businesses.
- The increasing use of big data by businesses, which is providing valuable insights that can be used to improve business processes through machine learning algorithms deployed as a service.
- Growing demand for predictive analytics and prescriptive analytics solutions that help organizations make better decisions by predicting future outcomes based on past data trends
Scope Of The Report
Report Attributes
Report Details
Report Title
Machine Learning as a Service Market Research Report
By Type
Private Clouds Machine Learning as a Service, Public Clouds Machine Learning as a Service, Hybrid Cloud Machine Learning as a Service
By Application
Personal, Business
By Companies
Amazon, Oracle, IBM, Microsoftn, Google, Salesforce, Tencent, Alibaba, UCloud, Baidu, Rackspace, SAP AG, Century Link Inc., CSC(Computer Science Corporation), Heroku, Clustrix, Xeround
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
190
Number of Tables & Figures
133
Customization Available
Yes, the report can be customized as per your need.
Global Machine Learning as a Service Market Report Segments:
The global Machine Learning as a Service market is segmented on the basis of:
Types
Private Clouds Machine Learning as a Service, Public Clouds Machine Learning as a Service, Hybrid Cloud Machine Learning as a Service
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
Personal, Business
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:
- Amazon
- Oracle
- IBM
- Microsoftn
- Salesforce
- Tencent
- Alibaba
- UCloud
- Baidu
- Rackspace
- SAP AG
- Century Link Inc.
- CSC(Computer Science Corporation)
- Heroku
- Clustrix
- Xeround
Highlights of The Machine Learning as a Service 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:
- Private Clouds Machine Learning as a Service
- Public Clouds Machine Learning as a Service
- Hybrid Cloud Machine Learning as a Service
- By Application:
- Personal
- Business
- 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 Machine Learning as a Service 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.
How you may use our products:
- Correctly Positioning New Products
- Market Entry Strategies
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- Consumer Insights
- Understanding Competition Scenario
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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?
Machine learning as a service (MLaaS) is a model for delivering machine learning algorithms as a cloud-based service. MLaaS providers typically offer pre-trained models, algorithms, and other tools that allow users to deploy them quickly on their own data sets.
Some of the major companies in the machine learning as a service market are Amazon, Oracle, IBM, Microsoftn, Google, Salesforce, Tencent, Alibaba, UCloud, Baidu, Rackspace, SAP AG, Century Link Inc., CSC(Computer Science Corporation), Heroku, Clustrix, Xeround.
The machine learning as a service market is expected to register a CAGR of 27.5%.
Chapter 1 Executive Summary
Chapter 2 Assumptions and Acronyms Used
Chapter 3 Research Methodology
Chapter 4 Machine Learning as a Service 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 Machine Learning as a Service Market Dynamics 4.2.1 Market Drivers 4.2.2 Market Restraints 4.2.3 Market Opportunity 4.3 Machine Learning as a Service 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 Machine Learning as a Service 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 Machine Learning as a Service Market Size & Forecast, 2018-2028 4.5.1 Machine Learning as a Service Market Size and Y-o-Y Growth 4.5.2 Machine Learning as a Service Market Absolute $ Opportunity
Chapter 5 Global Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Type
5.2.1 Private Clouds Machine Learning as a Service
5.2.2 Public Clouds Machine Learning as a Service
5.2.3 Hybrid Cloud Machine Learning as a Service
5.3 Market Attractiveness Analysis by Type
Chapter 6 Global Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Applications
6.2.1 Personal
6.2.2 Business
6.3 Market Attractiveness Analysis by Applications
Chapter 7 Global Machine Learning as a Service 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 Machine Learning as a Service 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 Machine Learning as a Service Analysis and Forecast
9.1 Introduction
9.2 North America Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Type
9.6.1 Private Clouds Machine Learning as a Service
9.6.2 Public Clouds Machine Learning as a Service
9.6.3 Hybrid Cloud Machine Learning as a Service
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 Machine Learning as a Service Market Size Forecast by Applications
9.10.1 Personal
9.10.2 Business
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 Machine Learning as a Service Analysis and Forecast
10.1 Introduction
10.2 Europe Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Type
10.6.1 Private Clouds Machine Learning as a Service
10.6.2 Public Clouds Machine Learning as a Service
10.6.3 Hybrid Cloud Machine Learning as a Service
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 Machine Learning as a Service Market Size Forecast by Applications
10.10.1 Personal
10.10.2 Business
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 Machine Learning as a Service Analysis and Forecast
11.1 Introduction
11.2 Asia Pacific Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Type
11.6.1 Private Clouds Machine Learning as a Service
11.6.2 Public Clouds Machine Learning as a Service
11.6.3 Hybrid Cloud Machine Learning as a Service
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 Machine Learning as a Service Market Size Forecast by Applications
11.10.1 Personal
11.10.2 Business
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 Machine Learning as a Service Analysis and Forecast
12.1 Introduction
12.2 Latin America Machine Learning as a Service 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 Machine Learning as a Service Market Size Forecast by Type
12.6.1 Private Clouds Machine Learning as a Service
12.6.2 Public Clouds Machine Learning as a Service
12.6.3 Hybrid Cloud Machine Learning as a Service
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 Machine Learning as a Service Market Size Forecast by Applications
12.10.1 Personal
12.10.2 Business
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) Machine Learning as a Service Analysis and Forecast
13.1 Introduction
13.2 Middle East & Africa (MEA) Machine Learning as a Service 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) Machine Learning as a Service Market Size Forecast by Type
13.6.1 Private Clouds Machine Learning as a Service
13.6.2 Public Clouds Machine Learning as a Service
13.6.3 Hybrid Cloud Machine Learning as a Service
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) Machine Learning as a Service Market Size Forecast by Applications
13.10.1 Personal
13.10.2 Business
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 Machine Learning as a Service Market: Competitive Dashboard
14.2 Global Machine Learning as a Service Market: Market Share Analysis, 2019
14.3 Company Profiles (Details – Overview, Financials, Developments, Strategy)
14.3.1 Amazon
14.3.2 Oracle
14.3.3 IBM
14.3.4 Microsoftn
14.3.5 Google
14.3.6 Salesforce
14.3.7 Tencent
14.3.8 Alibaba
14.3.9 UCloud
14.3.10 Baidu
14.3.11 Rackspace
14.3.12 SAP AG
14.3.13 Century Link Inc.
14.3.14 CSC(Computer Science Corporation)
14.3.15 Heroku
14.3.16 Clustrix
14.3.17 Xeround