HOME Top Market Reports Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022

Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022

By: marketsandmarkets.com
Publishing Date: September 2017
Report Code: TC 5578

 

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Machine learning enabled solutions are being significantly adopted by organizations worldwide to enhance customer experience, ROI, and to gain a competitive edge in business operations. Moreover, in the coming years, applications of machine learning in various industry verticals is expected to rise exponentially. Technological advancement and proliferation in data generation are some of the major driving factors for the market. The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period.

The objective of the study has been carried out to define, describe, and forecast the global machine learning market on the basis of vertical (BFSI, energy and utilities, healthcare and life sciences, retail, telecommunication, manufacturing, government and defense, others (transportation, agriculture, media and entertainment, and education), services (professional services and managed services), deployment modes (cloud and on-premises), organization sizes (SMEs and large enterprises), and regions (North America, Europe, APAC, MEA, and Latin America). The report also aims at providing detailed information about the major factors influencing the growth of the machine learning market (drivers, restraints, opportunities, and challenges).

The research methodology used to estimate and forecast the global machine learning market size began with the capturing of data on the key vendor revenues through secondary research, annual reports, Institute of Electrical and Electronic Engineers (IEEE), Factiva, Bloomberg, and press releases. The vendor offerings were also taken into consideration to determine the market segmentations. The bottom-up procedure was employed to arrive at the overall market size from the revenues of the key market players. After arriving at the overall market size, the total market was split into several segments and subsegments, which were then verified through primary research by conducting extensive interviews with key individuals, such as Chief Executive Officers (CEOs), Vice Presidents (VPs), directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments. The breakdown of the profiles of the primary participants is depicted in the figure given below:

Machine Learning Market

To know about the assumptions considered for the study, download the pdf brochure

The major machine learning vendors are Microsoft Corporation (Washington, US), IBM Corporation (New York, US), SAP SE (Walldorf, Germany), SAS Institute Inc. (North Carolina, US), Google, Inc. (California, US), Amazon Web Services Inc. (Washington, US), Baidu, Inc. (Beijing, China), BigML, Inc. (Oregon, US), Fair Isaac Corporation (FICO) (California, US), Hewlett Packard Enterprise Development LP (HPE) (California, US), Intel Corporation (California, US), KNIME.com AG (Zurich, Switzerland), RapidMiner, Inc. (Massachusetts, US),  Angoss Software Corporation (Toronto, Canada), H2O.ai (California, US), Alpine Data (California, US), Domino Data Lab, Inc. (California, US), Dataiku (Paris, France), Luminoso Technologies, Inc. (Massachusetts, US), TrademarkVision (Pennsylvania, US), Fractal Analytics Inc. (New Jersey, US),  TIBCO Software Inc. (California, US), Teradata (Ohio, US), Dell Inc. (Texas, US), and Oracle Corporation (California, US).

Target Audience

  • Machine learning/Artificial Intelligence (AI) solution and service providers
  • System integrators
  • Enterprise data center professionals
  • End-users/consumers/enterprise users
  • Telecommunication providers
  • Mobile network operators
  • Cloud service providers
  • Data center software vendors
  • IoT device/wearable device manufacturers
  • Cognitive and Artificial Intelligence (AI) technology experts/providers
  • Analytics service providers
  • Managed service providers
  • Consultants
  • Training and education service providers

Scope of the Report

The research report segments the machine learning market into the following segments:

By Vertical:

  • BFSI
    • Applications of machine learning in BFSI
      • Fraud and Risk Management
      • Investment Prediction
      • Sales and Marketing Campaign Management
      • Customer Segmentation
      • Digital Assistance
      • Others (compliance management and credit underwriting)
  • Healthcare and Life Sciences
    • Applications of machine learning in healthcare and life sciences
      • Disease Identification and Diagnosis
      • Image Analytics
      • Drug Discovery/Manufacturing
      • Personalized Treatment
      • Others (clinical trial research and epidemic outbreak prediction)
  • Retail
    • Applications of machine learning in retail
      • Inventory Planning
      • Upsell and Cross Channel Marketing
      • Segmentation and Targeting
      • Recommendation engines
      • Others (customer ROI and lifetime value, and customization management)
  • Telecommunication
    • Applications of machine learning in telecommunication
      • Customer Analytics
      • Network Optimization
      • Network Security
      • Others (digital assistance/contact centers analytics and marketing campaign analytics)
  • Government and Defense
    • Applications of machine learning in government and defense
      • Threat Intelligence
      • Autonomous Defense system
      • Others (sustainability and operational analytics)
  • Manufacturing
    • Applications of machine learning in manufacturing
      • Predictive Maintenance
      • Demand Forecasting
      • Revenue Estimation
      • Supply Chain Management
      • Others (root cause analysis and telematics)
  • Energy and Utilities
    • Applications of machine learning in energy and utilities
      • Power/Energy Usage Analytics
      • Seismic Data Processing
      • Smart Grid Management
      • Carbon Emission
      • Others (customer specific pricing and renewable energy management)
  • Others (Education, Agriculture, Media and Entertainment, and Education)

By Service

  • Professional Services
  • Managed Services

By Deployment Model:

  • Cloud
  • On-premises

By Organization Size:

  • SMEs
  • Large Enterprises

By Region:

  • North America
  • Europe
  • Asia Pacific (APAC)
  • Middle East And Africa (MEA)
  • Latin America

Available Customizations

With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product matrix which gives a detailed comparison of product portfolio of each company

Geographic Analysis

  • Further breakdown of the APAC machine learning market
  • Further breakdown of the North American market
  • Further breakdown of the MEA market
  • Further breakdown of the European market
  • Further breakdown of the Latin American market

Company Information

  • Detailed analysis and profiling of additional market players (Up to 5)

Table of Contents

1 Introduction (Page No. - 16)
    1.1 Objectives of the Study
    1.2 Market Definition
    1.3 Market Scope
    1.4 Years Considered for the Study
    1.5 Currency
    1.6 Stakeholders

2 Research Methodology (Page No. - 20)
    2.1 Research Data
           2.1.1 Secondary Data
           2.1.2 Primary Data
                    2.1.2.1 Breakdown of Primaries
                    2.1.2.2 Key Industry Insights
    2.2 Market Size Estimation
           2.2.1 Bottom-Up Approach
           2.2.2 Top-Down Approach
    2.3 Microquadrant Research Methodology
           2.3.1 Vendor Inclusion Criteria
    2.4 Research Assumptions
    2.5 Limitations

3 Executive Summary (Page No. - 28)

4 Premium Insights (Page No. - 36)
    4.1 Attractive Market Opportunities in the Machine Learning Market
    4.2 Machine Learning Market: Top 3 Verticals
    4.3 Lifecycle Analysis, By Region, 2017–2022

5 Market Overview and Industry Trends (Page No. - 39)
    5.1 Introduction
    5.2 Market Dynamics
           5.2.1 Drivers
                    5.2.1.1 Technological Advancements
                    5.2.1.2 Proliferation in Data Generation
           5.2.2 Restraints
                    5.2.2.1 Lack of Skilled Employees
           5.2.3 Opportunities
                    5.2.3.1 Increasing Demand for Intelligent Business Processes
                    5.2.3.2 Increasing Adoption in Modern Applications
           5.2.4 Challenges
                    5.2.4.1 Sensitive Data Security
                    5.2.4.2 Ethical Implications of the Algorithms Deployed
    5.3 Industry Trends
           5.3.1 Machine Learning: Use Cases
                    5.3.1.1 Introduction
                    5.3.1.2 Use Case #1: Deliver Analytics Solution
                    5.3.1.3 Use Case #2: Improve Cross-Selling Capabilities
                    5.3.1.4 Use Case #3: Increase Revenue and Decrease Customer Incompetence
                    5.3.1.5 Use Case #4: Market Basket Analysis
    5.4 Machine Learning Process
    5.5 Regulatory Implications
           5.5.1 Introduction
           5.5.2 Sarbanes-Oxley Act of 2002
           5.5.3 General Data Protection Regulation
           5.5.4 Basel

6 Machine Learning Market Analysis, By Vertical (Page No. - 47)
    6.1 Introduction
           6.1.1 Machine Learning Application in Banking, Financial Services, and Insurance
                    6.1.1.1 Fraud and Risk Management
                    6.1.1.2 Customer Segmentation
                    6.1.1.3 Sales and Marketing Campaign Management
                    6.1.1.4 Investment Prediction
                    6.1.1.5 Digital Assistance
                    6.1.1.6 Others
           6.1.2 Machine Learning Application in Healthcare and Life Sciences
                    6.1.2.1 Disease Identification and Diagnosis
                    6.1.2.2 Image Analytics
                    6.1.2.3 Personalized Treatment
                    6.1.2.4 Drug Discovery/Manufacturing
                    6.1.2.5 Others
           6.1.3 Machine Learning Application in Retail
                    6.1.3.1 Inventory Planning
                    6.1.3.2 Recommendation Engines
                    6.1.3.3 Upsells and Cross Channel Marketing
                    6.1.3.4 Segmentation and Targeting
                    6.1.3.5 Others
           6.1.4 Machine Learning Application in Telecommunication
                    6.1.4.1 Customer Analytics
                    6.1.4.2 Network Security
                    6.1.4.3 Network Optimization
                    6.1.4.4 Others
           6.1.5 Machine Learning Application in Government and Defense
                    6.1.5.1 Autonomous Defense System
                    6.1.5.2 Threat Intelligence
                    6.1.5.3 Others
           6.1.6 Machine Learning Application in Manufacturing
                    6.1.6.1 Predictive Maintenance
                    6.1.6.2 Revenue Estimation
                    6.1.6.3 Demand Forecasting
                    6.1.6.4 Supply Chain Management
                    6.1.6.5 Others
           6.1.7 Machine Learning Application in Energy and Utilities
                    6.1.7.1 Power/Energy Usage Analytics
                    6.1.7.2 Seismic Data Processing
                    6.1.7.3 Carbon Emission
                    6.1.7.4 Smart Grid Management
                    6.1.7.5 Others
           6.1.8 Other Applications

7 Machine Learning Market Analysis, By Deployment Mode (Page No. - 67)
    7.1 Introduction
    7.2 Cloud
    7.3 On-Premises

8 Machine Learning Market Analysis, By Organization Size (Page No. - 70)
    8.1 Introduction
    8.2 Large Enterprises
    8.3 Small and Medium-Sized Enterprises

9 Machine Learning Market Analysis, By Service (Page No. - 73)
    9.1 Introduction
    9.2 Professional Services
    9.3 Managed Services

10 Geographic Analysis (Page No. - 76)
     10.1 Introduction
     10.2 North America
             10.2.1 By Vertical
                        10.2.1.1 Machine Learning Application Trends in BFSI
                        10.2.1.2 Machine Learning Application Trends in Healthcare and Life Sciences
                        10.2.1.3 Machine Learning Application Trends in Retail
                        10.2.1.4 Machine Learning Application Trends in Telecommunication
                        10.2.1.5 Machine Learning Application Trends in Government and Defense
                        10.2.1.6 Machine Learning Application Trends in Manufacturing
                        10.2.1.7 Machine Learning Application Trends in Energy and Utilities
             10.2.2 By Organization Size
             10.2.3 By Deployment Mode
             10.2.4 By Service
     10.3 Europe
             10.3.1 By Vertical
                        10.3.1.1 Machine Learning Application Trends in BFSI
                        10.3.1.2 Machine Learning Application Trends in Healthcare and Life Sciences
                        10.3.1.3 Machine Learning Application Trends in Retail
                        10.3.1.4 Machine Learning Application Trends in Telecommunication
                        10.3.1.5 Machine Learning Application Trends in Government and Defense
                        10.3.1.6 Machine Learning Application Trends in Manufacturing
                        10.3.1.7 Machine Learning Application Trends in Energy and Utilities
             10.3.2 By Organization Size
             10.3.3 By Deployment Mode
             10.3.4 By Service
     10.4 Asia Pacific
             10.4.1 By Vertical
                        10.4.1.1 Machine Learning Application Trends in BFSI
                        10.4.1.2 Machine Learning Application Trends in Healthcare and Life Sciences
                        10.4.1.3 Machine Learning Application Trends in Retail
                        10.4.1.4 Machine Learning Application Trends in Telecommunication
                        10.4.1.5 Machine Learning Application Trends in Government and Defense
                        10.4.1.6 Machine Learning Application Trends in Manufacturing
                        10.4.1.7 Machine Learning Application Trends in Energy and Utilities
             10.4.2 By Organization Size
             10.4.3 By Deployment Mode
             10.4.4 By Service
     10.5 Middle East and Africa
             10.5.1 By Vertical
                        10.5.1.1 Machine Learning Application Trends in BFSI
                        10.5.1.2 Machine Learning Application Trends in Healthcare and Life Sciences
                        10.5.1.3 Machine Learning Application Trends in Retail
                        10.5.1.4 Machine Learning Application Trends in Telecommunication
                        10.5.1.5 Machine Learning Application Trends in Government and Defense
                        10.5.1.6 Machine Learning Application Trends in Manufacturing
                        10.5.1.7 Machine Learning Application Trends in Energy and Utilities
             10.5.2 By Organization Size
             10.5.3 By Deployment Mode
             10.5.4 By Service
     10.6 Latin America
             10.6.1 By Vertical
                        10.6.1.1 Machine Learning Application Trends in BFSI
                        10.6.1.2 Machine Learning Application Trends in Healthcare and Life Sciences
                        10.6.1.3 Machine Learning Application Trends in Retail
                        10.6.1.4 Machine Learning Application Trends in Telecommunication
                        10.6.1.5 Machine Learning Application Trends in Government and Defense
                        10.6.1.6 Machine Learning Application Trends in Manufacturing
                        10.6.1.7 Machine Learning Application Trends in Energy and Utilities
             10.6.2 By Organization Size
             10.6.3 By Deployment Mode
             10.6.4 By Service

11 Competitive Landscape (Page No. - 113)
     11.1 Market Ranking for the Machine Learning Market, 2017

12 Company Profiles (Page No. - 114)
(Business Overview, Strength of Product Portfolio, Business Strategy Excellence, Recent Developments)*
     12.1 International Business Machines Corporation
     12.2 Microsoft Corporation
     12.3 SAP SE
     12.4 Sas Institute Inc.
     12.5 Amazon Web Services, Inc.
     12.6 Bigml, Inc.
     12.7 Google Inc.
     12.8 Fair Isaac Corporation
     12.9 Baidu, Inc.
     12.10 Hewlett Packard Enterprise Development Lp
     12.11 Intel Corporation
     12.12 H2o.ai

*Details on Overview, Strength of Product Portfolio, Business Strategy Excellence, Recent Developments Might Not Be Captured in Case of Unlisted Companies.

13 Appendix (Page No. - 151)
     13.1 Discussion Guide
     13.2 Knowledge Store: Marketsandmarkets’ Subscription Portal
     13.3 Introducing RT: Real-Time Market Intelligence
     13.4 Available Customizations
     13.5 Related Reports
     13.6 Author Details


List of Tables (71 Tables)

Table 1 United States Dollar Exchange Rate, 2014–2016
Table 2 Evaluation Criteria
Table 3 Global Machine Learning Market Size and Growth Rate, 2015–2022 (USD Million, Y-O-Y %)
Table 4 Machine Learning Market Size, By Vertical, 2015–2022 (USD Million)
Table 5 Banking, Financial Services, and Insurance Market Size, By Application, 2015–2022 (USD Million)
Table 6 Healthcare and Life Sciences Market Size, By Application, 2015–2022 (USD Million)
Table 7 Retail Market Size, By Application, 2015–2022 (USD Million)
Table 8 Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 9 Government and Defense Market Size, By Application, 2015–2022 (USD Million)
Table 10 Manufacturing Market Size, By Application, 2015–2022 (USD Million)
Table 11 Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 12 Market Size By Deployment Mode, 2015–2022 (USD Million)
Table 13 Market Size By Organization Size, 2015–2022 (USD Million)
Table 14 Market Size By Service, 2015–2022 (USD Million)
Table 15 Market Size By Region, 2015–2022 (USD Million)
Table 16 North America: Machine Learning Market Size, By Vertical, 2015–2022 (USD Million)
Table 17 North America: Banking, Financial Services, and Insurance Market Size,  By Application, 2015–2022 (USD Million)
Table 18 North America: Healthcare and Life Sciences Market Size, By Application, 2015–2022 (USD Million)
Table 19 North America: Retail Market Size, By Application, 2015–2022 (USD Million)
Table 20 North America: Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 21 North America: Government and Defense Market Size, By Application, 2015–2022 (USD Million)
Table 22 North America: Manufacturing Market Size, By Application, 2015–2022 (USD Million)
Table 23 North America: Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 24 North America: Market Size, By Organization Size,  2015–2022 (USD Million)
Table 25 North America: Market Size, By Deployment Mode,  2015–2022 (USD Million)
Table 26 North America: Market Size, By Service, 2015–2022 (USD Million)
Table 27 Europe: Machine Learning Market Size, By Vertical, 2015–2022 (USD Million)
Table 28 Europe: Banking, Financial Services, and Insurance Market Size, By Application, 2015–2022 (USD Million)
Table 29 Europe: Healthcare and Life Sciences Market Size, By Application,  2015–2022 (USD Million)
Table 30 Europe: Retail Market Size, By Application, 2015–2022 (USD Million)
Table 31 Europe: Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 32 Europe: Government and Defense Market Size, By Application, 2015–2022 (USD Million)
Table 33 Europe: Manufacturing Market Size, By Application, 2015–2022 (USD Million)
Table 34 Europe: Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 35 Europe: Market Size, By Organization Size, 2015–2022 (USD Million)
Table 36 Europe: Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 37 Europe: Market Size, By Service, 2015–2022 (USD Million)
Table 38 Asia Pacific: Machine Learning Market Size, By Vertical, 2015–2022 (USD Million)
Table 39 Asia Pacific: Banking, Financial Services, and Insurance Market Size, By Application, 2015–2022 (USD Million)
Table 40 Asia Pacific: Healthcare and Life Sciences Market Size, By Application,  2015–2022 (USD Million)
Table 41 Asia Pacific: Machine Learning Market Size in Retail, By Application,  2015–2022 (USD Million)
Table 42 Asia Pacific: Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 43 Asia Pacific: Government and Defense Market Size, By Application,  2015–2022 (USD Million)
Table 44 Asia Pacific: Manufacturing Market Size, By Application, 2015–2022 (USD Million)
Table 45 Asia Pacific: Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 46 Asia Pacific: Machine Learning Market Size, By Organization Size, 2015–2022 (USD Million)
Table 47 Asia Pacific: Machine Learning Market Size, By Deployment Mode, 2015–2022 (USD Million)
Table 48 Asia Pacific: Machine Learning Market Size, By Service, 2015–2022 (USD Million)
Table 49 Middle East and Africa: Machine Learning Market Size, By Vertical,  2015–2022 (USD Million)
Table 50 Middle East and Africa: Banking, Financial Services, and Insurance Market Size, By Application, 2015–2022 (USD Million)
Table 51 Middle East and Africa: Healthcare and Life Sciences Market Size, By Application, 2015–2022 (USD Million)
Table 52 Middle East and Africa: Retail Market Size, By Application, 2015–2022 (USD Million)
Table 53 Middle East and Africa: Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 54 Middle East and Africa: Government and Defense Market Size, By Application, 2015–2022 (USD Million)
Table 55 Middle East and Africa: Manufacturing Market Size, By Application,  2015–2022 (USD Million)
Table 56 Middle East and Africa: Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 57 Middle East and Africa: Market Size By Organization Size, 2015–2022 (USD Million)
Table 58 Middle East and Africa: Market Size By Deployment Mode, 2015–2022 (USD Million)
Table 59 Middle East and Africa: Market Size By Service,  2015–2022 (USD Million)
Table 60 Latin America: Machine Learning Market Size, By Vertical, 2015–2022 (USD Million)
Table 61 Latin America: Banking, Financial Services, and Insurance Market Size,  By Application, 2015–2022 (USD Million)
Table 62 Latin America: Healthcare and Life Sciences Market Size, By Application, 2015–2022 (USD Million)
Table 63 Latin America: Retail Market Size, By Application, 2015–2022 (USD Million)
Table 64 Latin America: Telecommunication Market Size, By Application, 2015–2022 (USD Million)
Table 65 Latin America: Government and Defense Market Size, By Application,  2015–2022 (USD Million)
Table 66 Latin America: Manufacturing Market Size, By Application, 2015–2022 (USD Million)
Table 67 Latin America: Energy and Utilities Market Size, By Application, 2015–2022 (USD Million)
Table 68 Latin America: Market Size By Organization Size,  2015–2022 (USD Million)
Table 69 Latin America: Market Size By Deployment Mode,  2015–2022 (USD Million)
Table 70 Latin America: Market Size By Service, 2015–2022 (USD Million)
Table 71 Market Ranking for the Machine Learning Market, 2017
 
 
List of Figures (56 Figures)
 
Figure 1 Global Machine Learning Market Segmentation
Figure 2 Global Machine Learning Market: Research Design
Figure 3 Breakdown of Primary Interviews: By Company Size, Designation, and Region
Figure 4 Data Triangulation
Figure 5 Market Size Estimation Methodology: Bottom-Up Approach
Figure 6 Market Size Estimation Methodology: Top-Down Approach
Figure 7 Machine Learning Market Snapshot (2017), By Vertical
Figure 8 Machine Learning Market Snapshot (2017), By Banking, Financial Services, and Insurance Application
Figure 9 Market Snapshot (2017) By Healthcare and Life Sciences Application
Figure 10 Market Snapshot (2017) By Retail Application
Figure 11 Market Snapshot (2017) By Telecommunication Application
Figure 12 Market Snapshot (2017) By Government  and Defense Application
Figure 13 Market Snapshot (2017) By Manufacturing Application
Figure 14 Market Snapshot (2017) By Energy and Utilities Application
Figure 15 Market Snapshot (2017) By Service
Figure 16 Market Snapshot (2017) By Organization Size
Figure 17 Machine Learning Market Snapshot (2017), By Deployment Mode
Figure 18 Machine Learning Market Snapshot, By Region
Figure 19 Proliferation in Data Generation is One of the Major Factors Driving the Overall Growth of the Machine Learning Market During the Forecast Period
Figure 20 Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 21 Asia Pacific is Expected to Exhibit the Highest Growth Potential During the Forecast Period
Figure 22 Market Investment Scenario: Asia Pacific is Expected to Be the Best Market for Investment in the Next 5 Years
Figure 23 Machine Learning Market: Drivers, Restraints, Opportunities, and Challenges
Figure 24 Machine Learning Process
Figure 25 Healthcare and Life Sciences Vertical is Expected to Exhibit the Highest CAGR During the Forecast Period
Figure 26 Fraud and Risk Management Application is Expected to Hold  the Largest Market Size During the Forecast Period
Figure 27 Disease Identification and Diagnosis Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 28 Inventory Planning Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 29 Customer Analytics Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 30 Threat Intelligence Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 31 Predictive Maintenance Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 32 Power/Energy Usage Analytics Application is Expected to Hold the Largest Market Size During the Forecast Period
Figure 33 Cloud Deployment Mode is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 34 Small and Medium-Sized Enterprises Segment is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 35 Managed Services Segment is Expected to Exhibit A Higher CAGR During the Forecast Period
Figure 36 North America is Expected to Hold the Largest Market Size During the Forecast Period
Figure 37 Asia Pacific is Expected to Have the Highest Growth Rate in the Machine Learning Market During the Forecast Period
Figure 38 North America: Market Snapshot
Figure 39 North America: Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 40 Major Fintech Companies in North America Using Machine Learning
Figure 41 Europe: Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 42 Asia Pacific: Market Snapshot
Figure 43 Asia Pacific: Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 44 Middle East and Africa: Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 45 Latin America: Healthcare and Life Sciences Vertical is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 46 International Business Machines Corporation: Company Snapshot
Figure 47 Microsoft Corporation: Company Snapshot
Figure 48 SAP SE: Company Snapshot
Figure 49 Amazon Web Services, Inc.: Company Snapshot
Figure 50 Google Inc.: Company Snapshot
Figure 51 Fair Isaac Corporation: Company Snapshot
Figure 52 Baidu, Inc.: Company Snapshot
Figure 53 Hewlett Packard Enterprise Development LP: Company Snapshot
Figure 54 Intel Corporation: Company Snapshot
Figure 55 Markets and Markets Knowledge Store: Snapshot 1
Figure 56 Markets and Markets Knowledge Store: Snapshot 2 

The global machine learning market is expected to grow from USD 1.41 Billion in 2017 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1%. The main driving factors for the market are proliferation in data generation and technological advancement.

In the services segment, the managed service segment is expected to grow at a higher CAGR, whereas professional service segment is expected to be a larger contributor during the forecast period. The managed service is said to be growing faster, as it helps organizations to increase efficiency and save costs for managing on-demand machine learning services. The growth of the professional services segment is mainly governed by the complexity of operations and increasing deployment of machine learning solutions.

In the deployment mode segment, the cloud deployment mode is expected to hold the largest market share and grow at the highest CAGR during the forecast period. Flexibility, automated software updates, disaster recovery through cloud-based backup systems, increased collaboration, monitoring document version control, and data loss prevention with robust cloud storage facilities are some of the crucial benefits that have resulted in the adoption of cloud-based delivery models for machine learning software solutions and services.

In the organization size segment, the large enterprises segment is expected to have the largest market share, whereas the SMEs segment is expected to grow at the highest CAGR during the forecast period. The rapidly emerging and highly active SMEs have increased the adoption of machine learning solutions and services globally, as a result of the growing digitization and increased cyber risks to critical business information and data. Large enterprises have been heavily adopting machine learning to extract the required information from a large amount of data and forecast the outcome of various problems.

In the verticals segment, the Banking, Financial Services, and Insurance (BFSI) vertical is expected to be the highest contributor, whereas the healthcare and life sciences vertical is projected to grow at highest CAGR during the forecast period. Both the verticals generate data in a huge amount every second, and there is accelerated demand for data management technologies such as machine learning and predictive analytics in order to extract business critical insights from this ever-increasing data. The other industry verticals, such as manufacturing, telecommunication, energy and utilities, retail, and government and defense are contributing significantly to the machine learning market. These verticals are also expected to witness significant growth rates during the forecast period due to the increased concerns for managing the complex business processes with improved efficiency and lowering the overall costs.

The global machine learning market has been segmented on the basis of regions into North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. North America is estimated to be the largest revenue-generating region. This is mainly because, in the developed economies of the US and Canada, there is a high focus on innovations obtained from R&D. These regions have the most competitive and rapidly changing machine learning market in the world. The APAC region is expected to be the fastest-growing region in the machine learning market. The increased awareness for business productivity, supplemented with competently designed machine learning solutions offered by vendors present in the APAC region, has led APAC to become a highly potential market.

Machine Learning Market

The major issue faced by most of the organizations while incorporating machine learning in their business process is the lack of skilled employees including analytical talent, and the demand for those who can monitor analytical content is even greater.

The major vendors that offer machine learning solutions across the globe are Microsoft Corporation (Washington, US), IBM Corporation (New York, US), SAP SE (Walldorf, Germany), SAS Institute Inc. (North Carolina, US), Google, Inc. (California, US), Amazon Web Services Inc. (Washington, US), Baidu, Inc. (Beijing, China), BigML, Inc. (Oregon, US), Fair Isaac Corporation (FICO) (California, US), Hewlett Packard Enterprise Development LP (HPE) (California, US), Intel Corporation (California, US), KNIME.com AG (Zurich, Switzerland), RapidMiner, Inc. (Massachusetts, US),  Angoss Software Corporation (Toronto, Canada), H2O.ai (California, US), Alpine Data (California, US), Domino Data Lab, Inc. (California, US), Dataiku (Paris, France), Luminoso Technologies, Inc. (Massachusetts, US), TrademarkVision (Pennsylvania, US), Fractal Analytics Inc. (New Jersey, US),  TIBCO Software Inc. (California, US), Teradata (Ohio, US), Dell Inc. (Texas, US), and Oracle Corporation (California, US).

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