Machine learning is designed to incorporate functionalities of artificial intelligence (AI) and cognitive computing involving a series of algorithms and is used to understand the relationship between datasets to obtain a desired output. Machine learning as a service (MLaaS) incorporates a range of services that offer machine learning tools through cloud computing services.
The global machine learning as a service market report covers various parameters of the machine learning industry. The market is segmented based on component, organization size, end-use industry, application, and geography. The component segment is bifurcated into software and services. Based on organization size, it is divided into large enterprises and small & medium enterprises. The application segment is categorized into marketing & advertising, fraud detection & risk management, predictive analytics, augmented & virtual reality, natural language processing, computer vision, security & surveillance, and others. Based on end-use industry, it is classified into aerospace & defense, IT & telecom, energy & utilities, public sector, manufacturing, BFSI, healthcare, retail, and others.
This report features information on machine learning services offered by key vendors. Based on region, the global machine learning as a service market is segmented across North America, Europe, Asia-Pacific, and LAMEA. Further, the report also highlights the altered strategies of key market players to improve the market share and sustain competition.
Key players operating in the market include Google Inc., SAS Institute Inc., FICO, Hewlett Packard Enterprise, Yottamine Analytics, Amazon Web Services, BigML, Inc., Microsoft Corporation, Predictron Labs Ltd., and IBM Corporation.
The global machine learning as a service market report covers various parameters of the machine learning industry. The market is segmented based on component, organization size, end-use industry, application, and geography. The component segment is bifurcated into software and services. Based on organization size, it is divided into large enterprises and small & medium enterprises. The application segment is categorized into marketing & advertising, fraud detection & risk management, predictive analytics, augmented & virtual reality, natural language processing, computer vision, security & surveillance, and others. Based on end-use industry, it is classified into aerospace & defense, IT & telecom, energy & utilities, public sector, manufacturing, BFSI, healthcare, retail, and others.
This report features information on machine learning services offered by key vendors. Based on region, the global machine learning as a service market is segmented across North America, Europe, Asia-Pacific, and LAMEA. Further, the report also highlights the altered strategies of key market players to improve the market share and sustain competition.
Key players operating in the market include Google Inc., SAS Institute Inc., FICO, Hewlett Packard Enterprise, Yottamine Analytics, Amazon Web Services, BigML, Inc., Microsoft Corporation, Predictron Labs Ltd., and IBM Corporation.
Key Benefits For Stakeholders
- The study provides an in-depth analysis of the machine learning as a service market along with current trends and future estimations to elucidate imminent investment pockets.
- Information about key drivers, restrains, and opportunities and their impact analysis on the market size is provided in the report.
- Porter’s five forces analysis illustrates the potency of buyers and suppliers operating in the industry.
- The quantitative analysis of machine learning as a service market for the period 2021-2030 is provided to determine the market potential.
Key Market Segments
BY APPLICATION
- 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
- BANKING, FINANCIAL SERVICES, and INSURANCE
- Healthcare
- Retail
- Others
By Region
- North America
- U.S.
- Canada
- Europe
- United Kingdom
- Germany
- France
- Italy
- Spain
- Netherlands
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- Australia
- South Korea
- Rest of Asia-Pacific
- LAMEA
- Latin America
- Middle East
- Africa
Key Market Players
- GOOGLE INC
- SAS INSTITUTE INC
- FICO
- HEWLETT PACKARD ENTERPRISE
- YOTTAMINE ANALYTICS
- AMAZON WEB SERVICES
- BIGML, INC
- MICROSOFT CORPORATION
- PREDICTRON LABS LTD
- IBM CORPORATION
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Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: MACHINE LEARNING AS A SERVICE MARKET, BY APPLICATION
CHAPTER 5: MACHINE LEARNING AS A SERVICE MARKET, BY ORGANIZATION SIZE
CHAPTER 6: MACHINE LEARNING AS A SERVICE MARKET, BY COMPONENT
CHAPTER 7: MACHINE LEARNING AS A SERVICE MARKET, BY END-USE INDUSTRY
CHAPTER 8: MACHINE LEARNING AS A SERVICE MARKET, BY REGION
CHAPTER 9: COMPANY LANDSCAPE
CHAPTER 10: COMPANY PROFILES
LIST OF TABLES
LIST OF FIGURES
Executive Summary
According to this report titled, 'Machine learning as a Service Market,' the machine learning as a service market was valued at $13.95 billion in 2020, and is estimated to reach $302.66 billion by 2030, growing at a CAGR of 36.2% from 2021 to 2030.The global machine learning as a service market is influenced by a number of factors, including growth in demand for cloud computing, increase in adoption of analytical solutions, growth of artificial intelligence & cognitive computing market, increased application areas. However, the restraints include dearth of trained professionals.
In 2021, on the basis of component, the service segment dominated the machine learning as a service market, and is expected to maintain its dominance in the upcoming years. This is attributed to factors such as increase in application areas and growth associated with end-use industries among developing economies, which is expected to drive the market growth for machine learning services. Industry players are focused toward implementation of technologically advanced solutions to increase adoption of machine learning services. The use of machine learning services in the healthcare industry for detection of cancer as well as to check ECG, MRI will increase the market in the healthcare sector. Benefits offered by machine learning services such as cost reduction, demand forecasting, real-time data analysis, and growth in adoption of cloud market are expected to unlock major opportunities in the market. For instance, in April 2021, Microsoft Corporation announced an open Dataset for transportation, health & genomics, labor & economics, population & safety, and supplemental & common datasets to improve accuracy of machine learning models with publicly available datasets. This also allows companies to deliver insights at hyperscale using Azure Open Datasets with Azure’s machine learning and data analytics solutions that boosts sales MLaaS of companies.
On the basis of end user industry, the IT & telecom segment is the fastest growing segment of ML as a Service, and is projected to keep its hold on the market in the next years. Moreover, a number of IT & telecom organizations use machine learning as a service to predict the effects of forthcoming promotional strategies and sift through and utilize this refined data to find the most profitable customers. Machine learning used in analytics provides business intelligence to various telecommunication organizations, which helps in increasing their sales, predicting churn rates, improving fraud management, and decreasing operational costs. Rise in adoption of analytics in the telecom industry is to improve its core operations and internal processes to establish trends and to enable future forecasts. The IT and telecom industry has a wide array of growth opportunities, owing to data generated from phone calls, phone applications, social media, and data network. Applications of machine learning, such as real-time data analytics, also provide marketing and sales opportunities, while offering customized customer services. Companies are focused on implementation of machine learning capabilities to gain a competitive edge in the market.
Asia-Pacific is expected to be the fastest-growing regional segment during the forecast period, with the highest CAGR. Industry participants are realizing the importance of providing multi-modal platforms to ensure superior customer service. Growth in penetration of AI applications is expected to be the key trend influencing the market growth in this region. In addition, government organizations have adopted key initiatives to further spur penetration of machine learning and adjacent technologies in this region. North America is the leading region, in terms of technological advancements and adoption. It possesses well-equipped infrastructure and the ability to afford machine learning as a service solutions. Furthermore, rise in investments in the defense sector, along with technological advancements in the telecommunication industry, is expected to drive the market growth during the Machine learning as a Service Market Forecast period. Government regulations regarding data security are expected to continue to be a strong driver for the machine learning services market. Services such as security information and cloud application are expected to drive the market. In addition, strong presence of industry leaders such as Google, IBM, Microsoft, and Amazon Web Services and diversified product offerings have further led to rise in demand for machine learning solutions in this region. Furthermore, growth associated with artificial intelligence and cognitive computing is expected to create lucrative opportunities for market players to leverage varied industry applications such as predictive analytics, natural language processing, computer vision, fraud detection & management, and others.
The current estimation of 2030 is projected to be higher than pre-COVID-19 estimates. The COVID-19 pandemic has had a significant effect on countries' health, financial, and social systems. Individuals can profit from understanding and coping with their mental, psychological, and social well-being if knowledge of individual-level susceptibility factors is accessible. The application of artificial intelligence technology is likely to help combat the COVID-19 pandemic. Several countries are using population surveillance methods to track and trace COVID-19 cases. For example, in South Korea, researchers use surveillance camera footage, geo-location data to track coronavirus patients. Using this data, the data scientists leverage machine intelligence algorithms to predict the location of the next outbreak and inform the responsible authorities, helping to track the disease in real-time. Such active initiatives are likely to surge the demand for machine intelligence solutions in the upcoming period.
Key findings of the Study
- On the basis of component, in 2020, the services segment dominated the machine learning as a service market size. However, the software segment is expected to exhibit significant growth during the forecast period.
- Depending on end-user industry, the IT & telecom segment generated highest revenue in 2020.
- On the basis of organization size, the large enterprises segment generated the highest revenue in 2020. However, the small & medium enterprises segment is expected to exhibit significant growth during the forecast period
- On the basis of region, North America dominated the MLaaS market in 2020. However, Asia-Pacific is expected to witness significant growth in the upcoming years.
Companies Mentioned
- GOOGLE INC
- SAS INSTITUTE INC
- FICO
- HEWLETT PACKARD ENTERPRISE
- YOTTAMINE ANALYTICS
- AMAZON WEB SERVICES
- BIGML, INC
- MICROSOFT CORPORATION
- PREDICTRON LABS LTD
- IBM CORPORATION
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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