Machine learning as a Service Market

Machine learning as a Service Market by Application (Marketing and Advertising, Fraud Detection and Risk Management, Predictive analytics, Augmented and Virtual reality, Natural Language processing, Computer vision, Security and surveillance, Others), by Organization Size (Large Enterprises, Small and Medium Enterprises), by Component (Solution, Services), by End-Use Industry (Aerospace and Defense, IT and Telecom, Energy and Utilities, Public sector, Manufacturing, BANKING, FINANCIAL SERVICES, and INSURANCE, Healthcare, Retail, Others): Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2031

ICT & Media | 21 December 2022 | Report ID: EMR0017 | Pages: 330

The global machine learning as a service market size was valued at $14.95 billion in 2022, and is projected to reach $352.66 billion by 2031, growing at a CAGR of 39.2% from 2023 to 2031. Machine learning is a computing technology that offers computers the ability to learn and modify their analytical functionalities when exposed to new data sets, without being explicitly programmed. There are several factors that trigger the growth of the machine learning industry and its associated advanced computing and analytics markets. Some of them are rising demand for mapping customer behavior, especially by the marketing and advertising sectors, increasing concerns for security, and the growing need for applications to provide support during emergencies.

Market Growth

The market for machine learning as a service is sustaining huge growth due to technological advances and a rise in the number of research and development efforts all around the world. Another important factor driving market growth is the growing adoption of cloud-based platforms. Moreover, the rising emphasis on customer-centric behaviour is driving overall growth. The Global Machine Learning As A Service Market report offers a comprehensive analysis of the market. The report offers a comprehensive analysis of key segments, trends, drivers, restraints, the competitive landscape, and factors that are playing a substantial role in the market.

A major consideration assisting the growth of the global Machine learning as a service market is embracing cloud-based advancements and innovative advancements in digital scenarios. Machine learning as a service is a set of management practices that delivers machine learning to devices as part of a cloud computing service. Service machine learning companies offer different tools such as APIs, natural language processing, data visualization, deep learning, and predictive analytics. This is one of several factors that influence the target market. The machine learning as a service market is expected to grow significantly in the coming years, owing to rapid mechanical advancements and the more fundamental need to understand customer behavior. Furthermore, in terms of machine learning, the expansion aimed at understanding customer behaviors is driving the global machine learning as a service market over the forecast period.

Market Growth Factors

  • Increased Cloud Computing Demand and a Big Data Boom.

The industry is expanding as cloud computing technologies and social media platforms become more popular. All companies that provide enterprise storage solutions now use cloud computing. Data analysis is carried out online using cloud storage, allowing for the evaluation of real-time data collected on the cloud.

  • Use of Machine Learning As a service to Fuel Artificial Intelligence Systems.

Machine learning as a service is used to fuel reasoning, learning, and self-correction in artificial intelligence (AI) systems. Expert systems, speech recognition, and machine vision are examples of AI applications. The rise in popularity of AI is due to current efforts such as big data infrastructure and cloud computing.

COVID-19 IMPACT Analysis

The COVID-19 pandemic has had a significant impact on the health, economic, and social systems of many countries. It has killed millions of people worldwide and destroyed the world's economic and financial systems. Individuals can benefit from understanding and coping with their psychological, emotional, and social well-being by learning about individual-level susceptibility variables.

The application of artificial intelligence (AI) technology is expected to help combat the COVID-19 pandemic. Several countries are using population surveillance methods to track and trace COVID-19 cases for instance, in South Korea, researchers use surveillance camera footage and geo-location data to track COVID-19 patients. Using this data, data scientists leverage machine intelligence algorithms to predict the location of the next outbreak and inform the responsible authorities, helping to track disease in real-time. Such active initiatives are expected to surge demand for machine intelligence (MI) solutions during the forecast period.


Report Attribute


Projected Market Value (2031)

14.95 Billion

Estimated Market Value (2022)

352.66 Billion

Base Year


Forecast Years

2023 - 2031

Scope of the Report

Historical and Forecast Trends, Industry Drivers and Constraints, Historical and Forecast Market Analysis by Segment- Component, Organization size, End-use Industry, Application, Region

Segments Covered

By Organization Size, By Component, By Application, By weight, By End-Use Industry and Region

Forecast Units

Value (USD Billion), and Volume (Units)

Quantitative Units

Revenue in USD million/billion and CAGR from 2023 to 2031

Regions Covered

North America, Europe, Asia Pacific, Latin America, and Middle East & Africa, and Rest of World

Countries Covered

U.S., Canada, Mexico, U.K., Germany, France, Italy, Spain, China, India, Japan, South Korea, Brazil, Argentina, GCC Countries, and South Africa, among others

Report Coverage

Market growth drivers, restraints, opportunities, Porter’s five forces analysis, PEST analysis, value chain analysis, regulatory landscape, market attractiveness analysis by segments and region, company market share analysis, and COVID-19 impact analysis.

Delivery Format

Delivered as an attached PDF and Excel through email, according to the purchase option.


Component Insights

Based on component, the service sector led machine learning as a service market share in 2022, and this dominance is expected to continue in the years ahead. This is due to factors such as the expansion of application domains and the development of end-use industries in emerging markets, which are expected to drive the machine learning as a service market. Participants in the industry are focusing on implementing technologically advanced solutions to improve the use of machine learning services.

Application Insights

The marketing and advertising category had the largest revenue share in the market for machine learning as a service in 2021. The goal of a recommendation system is to present clients with goods that they are currently interested in. The following is the marketing work algorithm: Hypotheses are created, tested, judged, and analysed by marketing professionals. Because information changes every second, this endeavour is time-consuming and labor-intensive, and the results are occasionally incorrect.

Marketers may use machine learning to make quick decisions based on large amounts of data. Because of machine learning, businesses can now respond to changes in traffic quality caused by advertising initiatives more quickly. As a result, the company will have more time to devote to hypothesis generation rather than menial tasks.

Organization Size Insights

The small and medium business sector will hold a significant revenue share in the market for machine learning as a service in 2021. Because the machine learning application provides dynamic data, SMBs use MLaaS. In addition to providing real-time data, machine learning algorithms can predict future events using predictive analytics. Machine learning technologies can help SMBs fine-tune their supply chain by forecasting product demand and recommending the time and volume of supplies needed to meet consumers' expectations.

Target Audience

  • Education.
  • Banking and Financial services.
  • Insurance.
  • Automotive and Transportation.
  • Defense.
  • Healthcare.
  • Retail and e-Commerce.
  • Media and Entertainment.
  • Telecom
  • Others (Industrial Manufacturing, Mining, Agriculture, Utilities (Water/Energy/Oil & Gas), and Hospitality)

Regional Analysis

North America is the fastest growing region in the global market for machine learning as a service in terms of technical breakthroughs and acceptance. It has a well-equipped infrastructure and the financial resources to pay for a machine learning as a service solution. Furthermore, the market is expected to expand during the forecast period due to increased defence spending and technological advancements in the telecommunications sector. The market for machine learning services is expected to be heavily influenced by government data security regulations.

However, Asia-Pacific is expected to have the highest CAGR and the fastest growth over the forecast period. Leading companies are focusing their efforts on the Asia-Pacific region to expand their operations because the BFSI (banking, financial services, and insurance) industry is expected to see significant growth in the deployment of security services in this region. The CAGR for Asia-Pacific is expected to be the highest during the forecast period, making it the region with the fastest growth.

Machine Learning as a Service Market Share, By Region, 2021 (%)


Revenue Share in 2021 (%)

North America


Asia Pacific




Latin America














Competitive Landscape

The high level of market consolidation has increased competition among prominent players such as Microsoft, IBM, Google, and Amazon. To capture a significant share of the market, other players are actively expanding their product portfolios and geographical presence.

  • FICO

Recent Development

  • Telecom giant AT&T and AI company H2O have collaborated to launched an artificial intelligence feature store for enterprises businesses. This delivers a repository for collaborating, sharing, reusing, and discovering machine learning features to speed AI project deployments and increase ROI.
  • AWS announced six new Amazon SageMaker capabilities, which will make machine learning even more accessible and cost-effective. This brings together powerful new capabilities, including a no-code environment for creating accurate machine learning predictions and more accurate data labeling use of highly skilled annotators.


  • Computer vision
  • Security and surveillance
  • Others
  • Marketing and Advertising
  • Fraud Detection and Risk Management
  • Predictive analytics
  • Augmented and Virtual reality
  • Natural Language processing

By Organization Size        

  • Large Enterprises
  • Small and Medium Enterprises

By Component       

  • Solution
  • Services
  • By End-Use Industry           
  • Aerospace and Defense
  • IT and Telecom
  • Energy and Utilities
  • Public sector
  • Manufacturing
  • Healthcare
  • Retail
  • Others

By Region

Asia Pacific

  • China
  • Japan
  • India
  • South Korea
  • Australia
  • Indonesia
  • Others


  • Norway
  • Netherlands
  • Sweden
  • United Kingdom
  • France
  • Germany
  • Others

North America

  • United States
  • Canada

Middle East and Africa

  • Turkey
  • Saudi Arabia
  • Iran
  • United Arab Emirates
  • Others

Latin America

  • Brazil
  • Mexico
  • Argentina
  • Colombia
  • Others

Questions and Answers About This Report

Q1. What are the upcoming trends of Machine learning as a Service Market in the world

  1. Key impacting factors of the machine learning as a service include growth in demand for cloud-based solutions, including growth in demand for cloud computing, rise in adoption of analytical solutions, growth of artificial intelligence & cognitive computing market, increased application areas, and dearth of trained professionals.

Q2. What is the current size of machine learning as a service market

  1. The global machine learning as a service market size was accounted at USD 14.95 billion in 2022 and it is expected to reach around USD 352.66 billion by 2031.

Q3. Which are the top key players in Market

  1. The top key players in the market are Microsoft (Washington, US), Amazon Web Services (Washington, US), Hewlett Packard Enterprises (California, US), Google, Inc.(California, US), BigML Inc. (Oregon, US), FICO(California, US), IBM Corporation (New York, US), AT&T (Dallas, US), (Montreal, Canada), Yottamine Analytics (Washington, US), Ersatz Labs (California, US), Sift-Science (California, US).

Q4. Which Region Lead Machine Learning as a Service Market

  1. North America region Takes Lead in the Machine Learning as a Service Market.


Research Methodology

Our research methodology has always been the key differentiating reason which sets us apart in comparison from the competing organizations in the industry. Our organization believes in consistency along with quality and establishing a new level with every new report we generate; our methods are acclaimed and the data/information inside the report is coveted. Our research methodology involves a combination of primary and secondary research methods. Data procurement is one of the most extensive stages in our research process. Our organization helps in assisting the clients to find the opportunities by examining the market across the globe coupled with providing economic statistics for each and every region.  The reports generated and published are based on primary & secondary research. In secondary research, we gather data for global Market through white papers, case studies, blogs, reference customers, news, articles, press releases, white papers, and research studies. We also have our paid data applications which includes hoovers, Bloomberg business week, Avention, and others.

Data Collection

Data collection is the process of gathering, measuring, and analyzing accurate and relevant data from a variety of sources to analyze market and forecast trends. Raw market data is obtained on a broad front. Data is continuously extracted and filtered to ensure only validated and authenticated sources are considered. Data is mined from a varied host of sources including secondary and primary sources.

Primary Research

After the secondary research process, we initiate the primary research phase in which we interact with companies operating within the market space. We interact with related industries to understand the factors that can drive or hamper a market. Exhaustive primary interviews are conducted. Various sources from both the supply and demand sides are interviewed to obtain qualitative and quantitative information for a report which includes suppliers, product providers, domain experts, CEOs, vice presidents, marketing & sales directors, Type & innovation directors, and related key executives from various key companies to ensure a holistic and unbiased picture of the market. 

Secondary Research

A secondary research process is conducted to identify and collect information useful for the extensive, technical, market-oriented, and comprehensive study of the market. Secondary sources include published market studies, competitive information, white papers, analyst reports, government agencies, industry and trade associations, media sources, chambers of commerce, newsletters, trade publications, magazines, Bloomberg BusinessWeek, Factiva, D&B, annual reports, company house documents, investor presentations, articles, journals, blogs, and SEC filings of companies, newspapers, and so on. We have assigned weights to these parameters and quantified their market impacts using the weighted average analysis to derive the expected market growth rate.

Top-Down Approach & Bottom-Up Approach

In the top – down approach, the Global Batteries for Solar Energy Storage Market was further divided into various segments on the basis of the percentage share of each segment. This approach helped in arriving at the market size of each segment globally. The segments market size was further broken down in the regional market size of each segment and sub-segments. The sub-segments were further broken down to country level market. The market size arrived using this approach was then crosschecked with the market size arrived by using bottom-up approach.

In the bottom-up approach, we arrived at the country market size by identifying the revenues and market shares of the key market players. The country market sizes then were added up to arrive at regional market size of the decorated apparel, which eventually added up to arrive at global market size.

This is one of the most reliable methods as the information is directly obtained from the key players in the market and is based on the primary interviews from the key opinion leaders associated with the firms considered in the research. Furthermore, the data obtained from the company sources and the primary respondents was validated through secondary sources including government publications and Bloomberg.

Market Analysis & size Estimation

Post the data mining stage, we gather our findings and analyze them, filtering out relevant insights. These are evaluated across research teams and industry experts. All this data is collected and evaluated by our analysts. The key players in the industry or markets are identified through extensive primary and secondary research. All percentage share splits, and breakdowns have been determined using secondary sources and verified through primary sources. The market size, in terms of value and volume, is determined through primary and secondary research processes, and forecasting models including the time series model, econometric model, judgmental forecasting model, the Delphi method, among Flywheel Energy Storage. Gathered information for market analysis, competitive landscape, growth trends, product development, and pricing trends is fed into the model and analyzed simultaneously.

Quality Checking & Final Review

The analysis done by the research team is further reviewed to check for the accuracy of the data provided to ensure the clients’ requirements. This approach provides essential checks and balances which facilitate the production of quality data. This Type of revision was done in two phases for the authenticity of the data and negligible errors in the report. After quality checking, the report is reviewed to look after the presentation, Type and to recheck if all the requirements of the clients were addressed.