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Machine Learning Market - Global Industry Analysis

Machine Learning Market - by Service (Professional Services and Managed Services), by Application (BFSI, Healthcare & Life Sciences, Retail, Telecommunication, Government & Defense, Manufacturing, and Energy & Utilities): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2020-2027

Published Date: 11-Jul-2018 Category: Technology & Media Report Format : PDF Pages: 110 Report Code: ZMR-3171 Status : Published

Global Machine Learning market, which was estimated at 4.98 (USD Billion) in 2019 and is predicted to accrue earnings worth 46.94 (USD Billion) by 2027, is set to record a CAGR of nearly 44.06% over 2020-2027.

Description

The global Machine Learning market, which was estimated at 4.98 (USD Billion) in 2019 and is predicted to accrue earnings worth 46.94 (USD Billion) by 2027, is set to record a CAGR of nearly 44.06% over 2020-2027. The report offers valuation and analysis of Machine Learning Market on a global as well as regional level. The study offers a comprehensive assessment of the industry competition, limitations, sales estimates, avenues, current & emerging trends, and industry-validated market data. The report offers historical data from 2018 to 2019 along with a forecast from 2020 to 2027 based on value (USD Billion).

Introduction

Machine learning, which is a part of Artificial Intelligence, is the study of computer programs that improves automatically with experience. Additionally, the learning process helps the organization commence with observations or data for searching the patterns in the data in order to take better business decisions in the future. Precisely, machine learning helps the creation of such computer algorithms that can access the data and helps the computer in learning to use it without requiring any human intervention. Machine learning algorithms are categorized into unsupervised and supervised machine learning algorithms. Apparently, machine learning facilitates the analysis of large data quantities and provides accurate & speedy results for the firm so that it can know the business growth opportunities or the risks.

Global Machine Learning Market

Market Growth Dynamics

Escalating demand for Machine Learning as a Service (MLaaS) tool or machine learning as a vendor platform will create lucrative growth avenues for the market over the forthcoming years. Apart from this, machine learning facilitates activities like chat bots, image recognition, language translation, and predictive analytics. Additionally, it helps in simulating the human intelligence aspects like concept formation and problem solving. Since, a large number of machine learning programs are created and executed on cloud, massive use of the cloud services by various firms globally will facilitate the growth of machine learning market in the coming decade.

Furthermore, machine learning algorithms can be deployed for automating the tasks that are monotonous and codified along with being criteria-driven. For instance, information retrieval and product sorting into myriad categories can be done by machine learning algorithms. Firms can save the expenditure on these tasks by raising the efficacy of the tasks and reducing labor costs along with saving time by using machine learning tools. All these aforementioned aspects will leverage the industry landscape over the forecasting years. Apparently, machine learning is utilized for assisting human resources in business decision-making process and can augment human intelligence abilities through its authentic predictions & data insights.

Humungous use of machine learning programs in healthcare, BFSI, retail, defense, energy & utilities, Lifesciences, and telecommunications will provide lucrative growth opportunities to the market over the forthcoming years. In addition to this, growing requirement for proliferating the generated data will create new growth horizons for the market over the upcoming years.

North America To Contribute Majorly Towards Overall Market Share By 2027

The surge in the industry scope in the region over 2020-2027 is ascribed to presence of key players in the countries like the U.S. In addition to this, massive funding of Machine Learning as a Service (MLaaS) tool in the region along with the lucrative use of machine learning tools in cognitive applications in the countries like the U.S. will push the growth of the market over the ensuing years. Apart from this, firms like USAA – a financial services firm serving U.S. military personnel- makes use of machine learning algorithms.

Key players profiled in the report include Intel Corporation, Microsoft Corporation, SAP SE, Hewlett Packard Enterprise Development Lp, International Business Machines Corporation, Baidu Inc., Sas Institute Inc., Bigml Inc., Amazon Web Services Inc., Google Inc., Fair Isaac Corporation, and H2o.ai.

The report segments the global machine learning market as follows:

Global Machine Learning Market: Services segment Analysis

  • Professional Services
  • Managed Services

Global Machine Learning Market: Vertical Segment Analysis

  • BFSI
  • Healthcare and Life Science
  • Retail
  • Telecommunication
  • Government and Defense
  • Manufacturing
  • Energy and Utilities
  • Others

By Region

  • North America
    • The U.S.
    • Canada
  • Europe
    • France
    • The UK
    • Spain
    • Germany
    • Italy
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Southeast Asia
    • Rest of Asia Pacific
  • Latin America
    • Brazil
    • Mexico
    • Rest of Latin America
  • Middle East & Africa
    • GCC
    • South Africa
    • Rest of Middle East & Africa

Table Of Content

  • Chapter 1. Preface
    • 1.1. Report description and scope
    • 1.2. Research scope
    • 1.3. Research methodology
      • 1.3.1. Market research process
      • 1.3.2. Market research methodology
  •  
  • Chapter 2. Executive Summary
    • 2.1. Global Machine Learning Market, 2017 - 2024, (USD Billion)
    • 2.2. Machine Learning Market: Market Snapshot
  •  
  • Chapter 3. Global Machine Learning Market - Industry Analysis
    • 3.1. Machine Learning Market: Market dynamics
    • 3.2. Market Drivers
      • 3.2.1. Technological Advancements
      • 3.2.2. Proliferation in Data Generation
    • 3.3. Restraints
      • 3.3.1. Lack of Skilled Employees
    • 3.4. Opportunity
      • 3.4.1. Increasing Demand for Intelligent Business Processes
      • 3.4.2. Increasing Adoption in Modern Applications
    • 3.5. Challenges
      • 3.5.1. Sensitive Data Security
      • 3.5.2. Ethical Implications of the Algorithms Deployed
    • 3.6. Porter's Five Forces Analysis
    • 3.7. Market Attractiveness Analysis
      • 3.7.1. Market attractiveness analysis by services segment
      • 3.7.2. Market attractiveness analysis by verticals segment
      • 3.7.3. Market attractiveness analysis by regional segment
  •  
  • Chapter 4. Global Machine Learning Market - Competitive Landscape
    • 4.1. Company Market share analysis, 2017 (Subject to data availability)
  •  
  • Chapter 5. Global Machine Learning Market -Services Segment Analysis
    • 5.1. Global Machine Learning Market revenue share, by services, 2017 & 2024
    • 5.2. Global Machine Learning Market by Professional Services, 2015 - 2024 (USD Billion)
    • 5.3. Global Machine Learning Market by Managed Services, 2015 - 2024 (USD Billion)
  •  
  • Chapter 6. Global Machine Learning Market -Vertical Segment Analysis
    • 6.1. Global Machine Learning Market revenue share, by vertical 2017 & 2024
    • 6.2. Global Machine Learning Market by BFSI, 2015 - 2024(USD Billion)
    • 6.3. Global Machine Learning Market by Healthcare and Life Science, 2015 - 2024(USD Billion)
    • 6.4. Global Machine Learning Market by Retail, 2015 - 2024(USD Billion)
    • 6.5. Global Machine Learning Market by Telecommunication, 2015 - 2024(USD Billion)
    • 6.6. Global Machine Learning Market by Government and Defense, 2015 - 2024(USD Billion)
    • 6.7. Global Machine Learning Market by Manufacturing, 2015 - 2024(USD Billion)
    • 6.8. Global Machine Learning Market by Energy and Utilities, 2015 - 2024(USD Billion)
    • 6.9. Global Machine Learning Market by Others, 2015 - 2024(USD Billion)
  •  
  • Chapter 7. Global Machine Learning Market - Regional Analysis
    • 7.1. Global Machine Learning Market: Regional overview
      • 7.1.1. Global Machine Learning Market Revenue Share by region, 2017 and 2024
    • 7.2. North America
      • 7.2.1. North America Machine Learning Market, 2015 - 2024 (USD Billion)
      • 7.2.2. North America Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
      • 7.2.3. North America Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.2.4. U.S.
        • 7.2.4.1. U.S. Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
        • 7.2.4.2. U.S. Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
    • 7.3. Europe
      • 7.3.1. Europe Machine Learning Market, 2015 - 2024(USD Billion)
      • 7.3.2. Europe Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
      • 7.3.3. Europe Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.3.4. U.K.
        • 7.3.4.1. U.K. Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
        • 7.3.4.2. U.K. Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.3.5. France
        • 7.3.5.1. France Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
        • 7.3.5.2. France Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.3.6. Germany
        • 7.3.6.1. Germany Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
        • 7.3.6.2. Germany Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
    • 7.4. Asia Pacific
      • 7.4.1. Asia-Pacific Machine Learning Market, 2015 - 2024 (USD Billion)
      • 7.4.2. Asia-Pacific Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
      • 7.4.3. Asia-Pacific Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.4.4. China
        • 7.4.4.1. China Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
        • 7.4.4.2. China Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.4.5. Japan
        • 7.4.5.1. Japan Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
        • 7.4.5.2. Japan Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.4.6. India
        • 7.4.6.1. India Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
        • 7.4.6.2. India Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
    • 7.5. Latin America
      • 7.5.1. Latin America Machine Learning Market, 2015 - 2024(USD Billion)
      • 7.5.2. Latin America Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
      • 7.5.3. Latin America Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
      • 7.5.4. Brazil
        • 7.5.4.1. Brazil Machine Learning Market revenue, by services , 2015 - 2024 (USD Billion)
        • 7.5.4.2. Brazil Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
    •  
    • 7.6. Middle East & Africa
      • 7.6.1. The Middle East & Africa Machine Learning Market, 2015 - 2024 (USD Billion)
      • 7.6.2. The Middle East & Africa Machine Learning Market revenue, by services, 2015 - 2024 (USD Billion)
      • 7.6.3. The Middle East & Africa Machine Learning Market revenue, by verticals, 2015 - 2024 (USD Billion)
  •  
  • Chapter 8. Company Profiles
    • 8.1. International Business Machines Corporation
      • 8.1.1. Overview
      • 8.1.2. Financials
      • 8.1.3. Product portfolio
      • 8.1.4. Business strategy
      • 8.1.5. Recent developments
    • 8.2. Microsoft Corporation
      • 8.2.1. Overview
      • 8.2.2. Financials
      • 8.2.3. Product portfolio
      • 8.2.4. Business strategy
      • 8.2.5. Recent developments
    • 8.3. SAP SE
      • 8.3.1. Overview
      • 8.3.2. Financials
      • 8.3.3. Product portfolio
      • 8.3.4. Business strategy
      • 8.3.5. Recent developments
    • 8.4. Sas Institute Inc.
      • 8.4.1. Overview
      • 8.4.2. Financials
      • 8.4.3. Product portfolio
      • 8.4.4. Business strategy
      • 8.4.5. Recent developments
    • 8.5. Amazon Web Services, Inc.
      • 8.5.1. Overview
      • 8.5.2. Financials
      • 8.5.3. Product portfolio
      • 8.5.4. Business strategy
      • 8.5.5. Recent development
    • 8.6. Bigml, Inc.
      • 8.6.1. Overview
      • 8.6.2. Financials
      • 8.6.3. Product portfolio
      • 8.6.4. Business strategy
      • 8.6.5. Recent developments
    • 8.7. Google Inc.
      • 8.7.1. Overview
      • 8.7.2. Financials
      • 8.7.3. Product portfolio
      • 8.7.4. Business strategy
      • 8.7.5. Recent developments
    • 8.8. Fair Isaac Corporation
      • 8.8.1. Overview
      • 8.8.2. Financials
      • 8.8.3. Product portfolio
      • 8.8.4. Business strategy
      • 8.8.5. Recent developments
    • 8.9. Baidu, Inc.
      • 8.9.1. Overview
      • 8.9.2. Financials
      • 8.9.3. Product portfolio
      • 8.9.4. Business strategy
      • 8.9.5. Recent developments
    • 8.10. Hewlett Packard Enterprise Development Lp
      • 8.10.1. Overview
      • 8.10.2. Financials
      • 8.10.3. Product portfolio
      • 8.10.4. Business strategy
      • 8.10.5. Recent developments
    • 8.11. Intel Corporation
      • 8.11.1. Overview
      • 8.11.2. Financials
      • 8.11.3. Product portfolio
      • 8.11.4. Business strategy
      • 8.11.5. Recent developments
    • 8.12. H2o.ai
      • 8.12.1. Overview
      • 8.12.2. Financials
      • 8.12.3. Product portfolio
      • 8.12.4. Business strategy
      • 8.12.5. Recent developments

Methodology

Free Analysis

Machine Learning aids in the continuous advancement of computing with exposure to new adaptation, testing, and scenario. It is an application of artificial intelligence that equips the system with the ability of self-learning and improving from experience without being explicitly programmed. Some common machine learning methods are supervised machine learning algorithms, unsupervised machine learning algorithms, semi-supervised machine learning algorithms, and reinforcement machine learning algorithms. Many of the artificial intelligence experts have projected their idea that by 2050 all the intellectual tasks performed by the humans can be accomplished by the artificial intelligence technology. There are several applications of machine learning among which some are agriculture, brain-machine interface, telecommunication, detecting credit card fraud, internet frauds, medical diagnosis, insurance, robot locomotion, sequence mining, and more. Some of the open-source and proprietary software for machine learning are Amazon Machine Learning, IBM SPSS Modeler, KXEN Modeler, IBM Data Science Experience, Google Prediction API, MATLAB, Neural Designer, and more. The introduction of machine learning has transformed many industries which holds the benefits such as smart manufacturing, predictive maintenance, autonomous vehicles and interactive machines in production, optimized energy management for climate and energy change, quality control or test automation, and more. Some of the technical giants that use machine learning in their business improvement are IBM, Salesforce, Google, Netflix, Baidu, Microsoft, Twitter, and Amazon. Machine learning helps finance industry in customer and client satisfaction, reacting to market trends, and calculating risk; for the healthcare industry in personalized health monitoring; for the retail industry in online recommendations, and tracking price change. Siri and Cortana are the voice recognition systems that use deep neural networks and machine learning for emulating human interaction. With progress, these apps learn to understand the semantics and nuances of our language. Google Map suggests the fastest route by analyzing the traffic speed through anonymous data location from smartphones by using machine learning. There are several more real-time examples used by the Facebook, PayPal, Netflix, Uber, Lyst, and many more to provide advanced featured apps.

Global Machine Learning Market

Technological advancements and proliferation in data generation are some of the major factors which are catering to the market growth. Lack of skilled employees is one of the major restraining factors. Additionally, from a future aspect, some factors which uplift the market demand are increasing demand for intelligent business processes and increasing adoption in modern applications. However, sensitive data security and ethical implications of the algorithms deployed are hindering the market growth.

Machine learning market is segmented based on service, verticals, and region. On the basis of the services, the market is bifurcated as professional services and managed services. Furthermore on basis of verticals market is categorized into BFSI, healthcare and life science, retail, telecommunication, government and defense, manufacturing, energy and utilities, and others. In respect of geographic region, North America is expected to dominate the market in forecast period due to the developed countries and their major focus on innovative technologies obtained from R&D sector. Asia-Pacific region is predicted to grow at the highest CAGR during the forecast period because of increasing awareness regarding business productivity. In Asia, region vendors are offering competent machine learning proficiency due to which it is the highest potential region for the market.

Many technical giants are showing interest in machine learning technology for growing their businesses at a rapid pace. Some of the leading players in the global machine learning market are Microsoft Corporation, International Business Machines Corporation, Sas Institute Inc., SAP SE, Bigml Inc., Google Inc., Intel Corporation, Fair Isaac Corporation, Baidu Inc., Amazon Web Services Inc., Hewlett Packard Enterprise Development Lp, H2o.ai, and others.


Frequently Asked Questions

Escalating demand for Machine Learning as a Service (MLaaS) tool or machine learning as a vendor platform will create lucrative growth avenues for the market over the forthcoming years. Apart from this, machine learning facilitates activities like chat bots, image recognition, language translation, and predictive analytics. Additionally, it helps in simulating the human intelligence aspects like concept formation and problem solving. Since, a large number of machine learning programs are created and executed on cloud, massive use of the cloud services by various firms globally will facilitate the growth of machine learning market in the coming decade. Humungous use of machine learning programs in healthcare, BFSI, retail, defense, energy & utilities, Lifesciences, and telecommunications will provide lucrative growth opportunities to the market over the forthcoming years.

According to Zion market research report, the global Machine Learning market, which was estimated at 4.98 (USD Billion) in 2019 and is predicted to accrue earnings worth 46.94 (USD Billion) by 2027, is set to record a CAGR of nearly 44.06% over 2020-2027.

North America is likely to make noteworthy contributions towards overall market revenue. The regional market growth over 2020-2027 can be credited to presence of key players in the countries like the U.S. In addition to this, massive funding of Machine Learning as a Service (MLaaS) tool in the region along with the lucrative use of machine learning tools in cognitive applications in the countries like the U.S. will push the growth of the market over the ensuing years. Apart from this, firms like USAA – a financial services firm serving U.S. military personnel- makes use of machine learning algorithms.

The key players profiled in the report include Intel Corporation, Microsoft Corporation, SAP SE, Hewlett Packard Enterprise Development Lp, International Business Machines Corporation, Baidu Inc., Sas Institute Inc., Bigml Inc., Amazon Web Services Inc., Google Inc., Fair Isaac Corporation, and H2o.ai.

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