Machine Learning Market by Deployment Mode (Cloud, On-premise), Organization Size (SMEs (Small and Medium-Sized Enterprises), Large Enterprises), Service (Professional Services, Managed Services), Industry Vertical (Healthcare & Life Sciences, Manufacturing, Retail, Telecommunications, Government and Defense, BFSI (Banking, financial services, and insurance), Energy and Utilities and Others) - Global Analysis & Forecast 2019-2030

Report ID : 133  |  Published Date : Jan 2020  |  Pages : 190  |  Region : Global  |  Report Code : OTH-20





Machine Learning Market Overview and Introduction

Machine Learning Market was estimated at US$ 2.7 billion in 2019. The market is anticipated to further grow at a CAGR of 43.5% from 2019 to 2030.

Machine Learning is a branch of Artificial Intelligence (AI) that enables machines to perform tasks competently by using advanced software. The backbone of intelligent software constitutes statistical learning methods that are used to develop machine intelligence. It gives computers the ability to learn from data, identify patterns and make decisions with minimal human intervention. As it is evident from the name, it allows computers to learn automatically without assistance and adjust actions from experiences. The computational architectures and algorithms are used to effectively capture, store, index, retrieve, and merge this data. Machine learning is one of the top emerging sciences and has extensive applications in various domains. Some of the applications include traffic alerts (Google Maps), transportation & commuting (Uber), product recommendations (Amazon), self-driving cars, and fraud detection, among others.

In recent times, the machine learning market has gained importance due to the presence of large data sets and the need to process this data and obtain insights from it. The global machine learning market is driven by the availability of robust data sets and the adoption of machine learning techniques in modern applications. Security concerns, implementation challenges, lack of skilled data scientists, and data inaccessibility are some of the factors that may restrain the machine learning market to a certain extent.

The global machine learning market can be segmented into the following categories - By Deployment Mode, By Organization Size, By Service, and By Industry Vertical.

Machine Learning Market By Deployment Mode

The deployment mode segment can be classified into the cloud and on-premise. The cloud deployment segment is expected to account for the largest market share and the highest CAGR over the forecast period. Automated software updates, recovery of data through backup systems and data loss prevention with robust cloud storage facilities, among others are some of the factors that resulted in the adoption of cloud-based delivery models for machine learning solutions & services.

Machine Learning Market By Organization Size

The enterprise segment size can be classified into Small & Medium-sized Enterprises (SMEs) and large enterprises. The large enterprise segment is anticipated to account for the largest market share and the SME segment is expected to grow at the highest CAGR during the forecast period. Large enterprises have been adopting machine learning to extract the required information from a large amount of data and predict the outcome of different problems. Increasing digitization and rising security threats to critical business information and data has led to adoption of machine learning solutions by organizations. Moreover, rapidly evolving and highly active SMEs have increased the adoption of machine learning technologies and services globally.

Machine Learning Market By Service

The service segment can be classified into professional services and managed services. The managed services segment is expected to grow at a higher CAGR whereas the professional services segment is expected to account for the largest market share during the forecast period. Managed services will grow at rapid rates owing to increased efficiency and cost-saving in running machine learning services on demand.

Machine Learning Market By Industry Vertical

The industry vertical segment can be classified into healthcare & life sciences, manufacturing, retail, telecommunications, government & defense, Banking, Financial Services, & Insurance (BFSI), energy & utilities, and others. The BFSI segment is anticipated to account for the largest market share and the healthcare & life sciences segment is expected to grow at the highest CAGR during the forecast period. These industry verticals produce huge amounts of data every second and there is a growing demand for data management techniques, such as machine learning and predictive analytics, to gain critical business insights from the ever-increasing data. Other industry verticals, such as telecommunication, retail, government & defense, energy & utilities, and manufacturing are also contributing significantly to the machine learning market.

Machine Learning Market by Regions

The global machine learning market can be segmented into North America, Europe, Asia Pacific, and the Rest of the World (ROW).  North America has a significant market share due to its dynamic and fast-changing market. This is primarily due to the high concentration of technologies in the developed economies of the U.S. and Canada. The APAC region is expected to witness the highest CAGR during the forecast period. It is a high-potential machine learning market owing to factors such as competently designed machine learning solutions offered by vendors in the region and increased awareness regarding business productivity.          

Machine Learning Market Prominent Players

Some of the key players operating in the global machine learning market include Intel Corporation, H2O.ai, Amazon Web Services, Inc., Hewlett Packard Enterprise Development LP, IBM, Google LLC, Microsoft, SAS Institute Inc., SAP SE, and BigML, Inc., among others.

Table of Contents

  1. INTRODUCTION
    1. Market Definition
    2. Market Classification
    3. Geographic Scope
    4. Years Considered for the Study: Historical Years – 2016 & 2017; Base Year – 2018; Forecast Years – 2019 to 2030
    5. Currency Used
  2. RESEARCH METHODOLOGY
    1. Research Framework
    2. Data Collection Technique
    3. Data Sources
      1. Secondary Sources
      2. Primary Sources
    4. Market Estimation Methodology
      1.  Bottom Up Approach
      2.  Top Down Approach
    5. Data Validation and Triangulation
      1.  Market Forecast Model
      2.  Limitations/Assumptions of the Study
  3. ABSTRACT OF THE STUDY
  4. MARKET DYNAMICS ASSESSMENT
    1. Overview
    2. Drivers
    3. Barriers/Challenges
    4. Opportunities
  5. UNIQUE SELLING PROPOSITIONS (USPs)
    1. Technological Advancements
    2. Competitive Landscape Assessment
  6. GLOBAL MACHINE LEARNING MARKET - ANALYSIS & FORECAST, BY DEPLOYMENT MODE
    1. Cloud
    2. On-premise
  7. GLOBAL MACHINE LEARNING MARKET - ANALYSIS & FORECAST, BY ORGANIZATION SIZE
    1. SMEs (Small and Medium-Sized Enterprises)
    2. Large Enterprises
  8. GLOBAL MACHINE LEARNING MARKET - ANALYSIS & FORECAST, BY SERVICE
    1. Professional Services
    2. Managed Services
  9. GLOBAL MACHINE LEARNING MARKET - ANALYSIS & FORECAST, BY INDUSTRY VERTICAL
    1. Healthcare & Life Sciences
    2. Manufacturing
    3. Retail
    4. Telecommunications
    5. Government and Defense
    6. BFSI (Banking, Financial Services, & Insurance)
    7. Energy and Utilities
    8. Others
  10. GLOBAL MACHINE LEARNING- ANALYSIS & FORECAST, BY REGION
    1.   North America Machine Learning Market
      1.  North America Machine Learning Market, By Country
        1.  US
        2.  Canada
      2. North America Machine Learning Market Analysis & Forecast, By Deployment Mode
      3. North America Machine Learning Market Analysis & Forecast, By Organization Size
      4. North America Machine Learning Market Analysis & Forecast, By Service
      5. North America Machine Learning Market Analysis & Forecast, By Industry Vertical
    2. Europe Machine Learning Market
      1. Europe Machine Learning Market, By Country/Region
        1. Germany
        2. UK
        3. France
        4. Rest of Europe (ROE)
      2. Europe Machine Learning Market Analysis & Forecast, By Deployment Mode
      3. Europe Machine Learning Market Analysis & Forecast, By Organization Size
      4. Europe Machine Learning Market Analysis & Forecast, By Service
      5. Europe Machine Learning Market Analysis & Forecast, By Industry Vertical
    3. Asia Pacific Machine Learning Market
      1. Asia Pacific Machine Learning Market, By Country/Region
        1. China
        2. Japan
        3. India
        4. Rest of Asia Pacific (RoAPAC)
      2. Asia Pacific Machine Learning  Market Analysis & Forecast, By Deployment Mode
      3. Asia Pacific Machine Learning Market Analysis & Forecast, By Organization Size
      4. Asia Pacific Machine Learning Market Analysis & Forecast, By Service
      5. Asia Pacific Machine Learning Market Analysis & Forecast, By Industry Vertical
    4.   Rest of the World (ROW) Machine Learning Market
      1. Rest of the World Machine Learning Market, By Country/ Region
        1.  Latin America
        2.  Middle East & Africa
      2. Rest of the World Machine Learning Market Analysis & Forecast, By Deployment Mode
      3. Rest of the World Machine Learning Market Analysis & Forecast, By Organization Size
      4. Rest of the World Machine Learning Market Analysis & Forecast, By Service
      5. Rest of the World Machine Learning Market Analysis & Forecast, By Industry Vertical
  11. COMPANY PROFILES (Business Overview, Products Offered, Financial Performance*, Recent Developments)
    1.  Intel Corporation
    2.  H2O.ai
    3.  Amazon Web Services, Inc.
    4.  Hewlett Packard Enterprise Development LP
    5.  IBM
    6.  Google LLC
    7.  Microsoft
    8.  SAS Institute Inc.
    9.  SAP SE
    10. BigML, Inc.

*Financial details might not be captured in case of privately-held companies or for companies that do not report this information in public domain