GLOBAL MACHINE LEARNING MARKET 2019-2027

ICT | AI and IoT

GLOBAL MACHINE LEARNING MARKET 2019-2027

Market By Deployment Mode, Organization Size, Service And End-user | Forecast 2019-2027

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Triton Market Research predicts that the global machine learning market, which accounted for $1807.77 million in 2018, would witness a CAGR of 34.19% over the forecast period of 2019-2027 to reach $24753.05 million.

Big Data, artificial intelligence, and machine learning are becoming an integral part of businesses to accelerate the delivery of business value and increase efficiency. The availability of large volumes & sources of data is the empowering capabilities of AI and ML. Businesses can now process gigantic volumes of data that was not thinkable before. The availability of gigantic datasets has corresponded with significant breakthroughs in machine learning, mainly owing to the emergence of better and more sophisticated AI algorithms. 

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Triton Market Research’s report on the machine learning market provides an in-depth insight into the market. The detailed analysis of the market includes: the evolution & transition of ML, vendor scorecard, key market insights, patent analysis, industry player positioning, industry components, Porter’s five forces analysis, key impact analysis and the market attractiveness index. 

The market has witnessed healthy growth over the years, owing to the expanding data volume across the world, widening application of machine learning in different end-use industries, significant developments in the field of AI & ML, rise in the implementation of data-driven applications and the augmented demand for intelligent business processes. Proliferation in data generation is a major factor driving the growth of the machine learning market. According to the World Economic Forum, 2.5 quintillion bytes of data is created each day. Further, according to the Institute of Electrical and Electronics Engineers, IEEE, machine learning is highly used in planning for data management. Thus, the rise in data generation is expected to increase the demand for machine learning for data management is contributing to the growth of the market.

Furthermore, the incorporation of artificial intelligence & machine learning with Big Data, the development of smart robots, increasing adoption of IoT-connected devices and the growing number of start-ups are expected to act as some growth opportunities for the market. There are around 8,705 start-ups and companies at present which are involved in development of ML applications, products and services. Further, these start-ups are exploring the potentials of machine learning in autonomous driving, healthcare, Big Data analytics and others. For instance, in October 2019, a London-based company, Rahko, raised €1.5 million in a seed round led by Balderton Capital and is working on ‘quantum discovery’ competencies for chemical simulation.

However, a notable limitation of machine learning is the sensitivity of errors that leads to computational limitations. According to Brynjolfsson and McAfee, the real problem is that when they make errors, it can be difficult to diagnose and correct them because it is necessary to go through the underlying complications of algorithms and related processes. Further, machine learning is a time-consuming process as it is not possible to make immediate and accurate predictions with machine learning. Thus, computational and technological barriers can limit real-time testing and deployment of machine learning solutions, which can hinder the market growth over the forecast period.

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Key geographies covered in the global machine learning market are:

•    North America: United States and Canada

•    Europe: United Kingdom, France, Germany, Spain, Italy, Russia and Rest of Europe

•    Asia-Pacific: China, Japan, India, Australia, South Korea, ASEAN Countries and Rest of Asia-Pacific 

•    Latin America: Brazil, Mexico and Rest of Latin America

•    Middle East and Africa: Saudi Arabia, Turkey, United Arab Emirates, South Africa and Rest of Middle East & Africa

Segmentation analysis of the machine learning market:.

•    Delivery Model is sub-segmented into:

O    Cloud

O    On-Premises

•    Organization Size is sub-segmented into:

O    Large Enterprises

O    Small & Medium-Sized Enterprises (SMEs)

•    Service Type is sub-segmented into:

O    Professional Services

O    Managed Services

•    End-Users are sub-segmented into:

O    Banking, Financial Services & Insurance (BFSI) 

O    Healthcare & Life Sciences

O    Retail

O    Telecommunication

O    Government & Defense

O    Manufacturing

O    Media & Advertising 

O    Energy & Utilities

O    Other End Users

The top companies that have been studied in the global machine learning market include Teradata Corporation, Amazon Web Services, Inc., Clarivate Analytics LLC (TrademarkVision), Baidu, Inc., Oracle Corporation, IBM Corporation (International Business Machines), SAP SE, Intel Corporation, Microsoft Corporation, TIBCO Software, Inc., Fractal Analytics, Fair Isaac Corporation (FICO), Hewlett Packard Enterprise Company (HPE), Google, Inc. and Dell Technologies, Inc.

The strategic analysis for each of these companies in the global machine learning market has been covered in detail.


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Table of Content

1.    GLOBAL MACHINE LEARNING MARKET - SUMMARY

2.    INDUSTRY OUTLOOK

2.1. MARKET DEFINITION

2.2. EVOLUTION & TRANSITION OF MACHINE LEARNING

2.3. KEY INSIGHTS

2.3.1. RISE IN IMPLEMENTATION OF DATA-DRIVEN APPLICATIONS

2.3.2. AUGMENTED DEMAND FOR INTELLIGENT BUSINESS PROCESSES

2.3.3. MACHINE LEARNING START-UPS TRANSFORMING THE INDUSTRY

2.4. PORTER’S FIVE FORCES ANALYSIS

2.4.1. BARGAINING POWER OF BUYERS

2.4.2. BARGAINING POWER OF SUPPLIERS

2.4.3. THREAT OF NEW ENTRANTS

2.4.4. THREAT OF SUBSTITUTE

2.4.5. THREAT OF COMPETITIVE RIVALRY

2.5. KEY IMPACT ANALYSIS

2.5.1. COST

2.5.2. APPLICATION

2.5.3. SCALABILITY

2.5.4. TRAINING TIME

2.6. MARKET ATTRACTIVENESS INDEX

2.7. VENDOR SCORECARD

2.8. INDUSTRY COMPONENTS

2.8.1. SOFTWARE DEVELOPMENT

2.8.2. CLOUD

2.8.3. USERS

2.9. PATENT ANALYSIS

2.10.            INDUSTRY PLAYER POSITIONING

2.11.            MARKET DRIVERS

2.11.1. EXPANDING DATA VOLUME ACROSS THE WORLD

2.11.2. WIDENING APPLICATION OF ML IN DIFFERENT END-USE INDUSTRIES

2.11.3. SIGNIFICANT DEVELOPMENTS IN THE FIELD OF MACHINE LEARNING

2.12.            MARKET RESTRAINTS

2.12.1. DIFFICULTIES IN PROTECTING SENSITIVE & PRIVATE DATA

2.12.2. COMPONENTS’ FAILURE MAY DISRUPT ML SERVICE

2.13.            MARKET OPPORTUNITIES

2.13.1. INCORPORATION OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING WITH BIG DATA

2.13.2. DEVELOPMENT OF SMART ROBOTS

2.13.3. INCREASING ADOPTION OF IoT-CONNECTED DEVICES

2.14.            MARKET CHALLENGES

2.14.1. TECHNOLOGICAL & COMPUTATIONAL BARRIERS

3.    GLOBAL MACHINE LEARNING MARKET OUTLOOK - BY DEPLOYMENT MODE

3.1. CLOUD

3.2. ON-PREMISES

4.    GLOBAL MACHINE LEARNING MARKET OUTLOOK - BY ORGANIZATION SIZE

4.1. LARGE ENTERPRISES

4.2. SMALL & MEDIUM-SIZED ENTERPRISES (SMEs)

5.    GLOBAL MACHINE LEARNING MARKET OUTLOOK - BY SERVICE

5.1. PROFESSIONAL SERVICES

5.2. MANAGED SERVICES

6.    GLOBAL MACHINE LEARNING MARKET OUTLOOK - BY END-USER

6.1. BANKING, FINANCIAL SERVICES & INSURANCE (BFSI)

6.2. HEALTHCARE & LIFE SCIENCES

6.3. RETAIL

6.4. TELECOMMUNICATION

6.5. GOVERNMENT & DEFENSE

6.6. MANUFACTURING

6.7. MEDIA & ADVERTISING

6.8. ENERGY & UTILITIES

6.9. OTHER END-USERS

7.    GLOBAL MACHINE LEARNING MARKET - REGIONAL OUTLOOK

7.1. NORTH AMERICA

7.1.1. MARKET BY DEPLOYMENT MODE

7.1.2. MARKET BY ORGANIZATION SIZE

7.1.3. MARKET BY SERVICE

7.1.4. MARKET BY END-USER

7.1.5. COUNTRY ANALYSIS

7.1.5.1.      UNITED STATES

7.1.5.2.      CANADA

7.2. EUROPE

7.2.1. MARKET BY DEPLOYMENT MODE

7.2.2. MARKET BY ORGANIZATION SIZE

7.2.3. MARKET BY SERVICE

7.2.4. MARKET BY END-USER

7.2.5. COUNTRY ANALYSIS

7.2.5.1.      UNITED KINGDOM

7.2.5.2.      GERMANY

7.2.5.3.      FRANCE

7.2.5.4.      SPAIN

7.2.5.5.      ITALY

7.2.5.6.      RUSSIA

7.2.5.7.      REST OF EUROPE

7.3. ASIA-PACIFIC

7.3.1. MARKET BY DEPLOYMENT MODE

7.3.2. MARKET BY ORGANIZATION SIZE

7.3.3. MARKET BY SERVICE

7.3.4. MARKET BY END-USER

7.3.5. COUNTRY ANALYSIS

7.3.5.1.      CHINA

7.3.5.2.      JAPAN

7.3.5.3.      INDIA

7.3.5.4.      SOUTH KOREA

7.3.5.5.      ASEAN COUNTRIES

7.3.5.6.      AUSTRALIA & NEW ZEALAND

7.3.5.7.      REST OF ASIA-PACIFIC

7.4. LATIN AMERICA

7.4.1. MARKET BY DEPLOYMENT MODE

7.4.2. MARKET BY ORGANIZATION SIZE

7.4.3. MARKET BY SERVICE

7.4.4. MARKET BY END-USER

7.4.5. COUNTRY ANALYSIS

7.4.5.1.      BRAZIL

7.4.5.2.      MEXICO

7.4.5.3.      REST OF LATIN AMERICA

7.5. MIDDLE EAST AND AFRICA

7.5.1. MARKET BY DEPLOYMENT MODE

7.5.2. MARKET BY ORGANIZATION SIZE

7.5.3. MARKET BY SERVICE

7.5.4. MARKET BY END-USER

7.5.5. COUNTRY ANALYSIS

7.5.5.1.      UNITED ARAB EMIRATES

7.5.5.2.      TURKEY

7.5.5.3.      SAUDI ARABIA

7.5.5.4.      SOUTH AFRICA

7.5.5.5.      REST OF MIDDLE EAST & AFRICA

8.    COMPETITIVE LANDSCAPE

8.1. TIBCO SOFTWARE, INC.

8.2. SAP SE

8.3. ORACLE CORPORATION

8.4. TERADATA CORPORATION

8.5. AMAZON WEB SERVICES, INC.

8.6. MICROSOFT CORPORATION

8.7. INTEL CORPORATION

8.8. FRACTAL ANALYTICS

8.9. GOOGLE, INC.

8.10.            BAIDU, INC.

8.11.            FAIR ISAAC CORPORATION (FICO)

8.12.            IBM CORPORATION (INTERNATIONAL BUSINESS MACHINES)

8.13.            HEWLETT PACKARD ENTERPRISE COMPANY (HPE)

8.14.            DELL TECHNOLOGIES, INC.

8.15.            CLARIVATE ANALYTICS LLC (TRADEMARKVISION)

9.    RESEARCH METHODOLOGY & SCOPE

9.1. RESEARCH SCOPE & DELIVERABLES

9.2. SOURCES OF DATA

9.3. RESEARCH METHODOLOGY

List of Tables

TABLE 1: GLOBAL MACHINE LEARNING MARKET, BY GEOGRAPHY, 2019-2027 (IN $ MILLION)

TABLE 2: EVOLUTION & TRANSITION OF MACHINE LEARNING

TABLE 3: LIST OF PROMINENT START-UPS IN MACHINE LEARNING

TABLE 4: VENDOR SCORECARD

TABLE 5: PATENTS FILLED IN MACHINE LEARNING BY KEY TECHNOLOGY COMPANIES, 2018

TABLE 6: TOP 20 FIRST PATENT FILERS IN MACHINE LEARNING IN 2016

TABLE 7: GLOBAL MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 8: GLOBAL MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 9: GLOBAL MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 10: GLOBAL MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

TABLE 11: GLOBAL MACHINE LEARNING MARKET, BY GEOGRAPHY, 2019-2027 (IN $ MILLION)

TABLE 12: NORTH AMERICA MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)

TABLE 13: NORTH AMERICA MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 14: NORTH AMERICA MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 15: NORTH AMERICA MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 16: NORTH AMERICA MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

TABLE 17: EUROPE MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)

TABLE 18: EUROPE MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 19: EUROPE MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 20: EUROPE MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 21: EUROPE MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

TABLE 22: ASIA-PACIFIC MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)

TABLE 23: ASIA-PACIFIC MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 24: ASIA-PACIFIC MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 25: ASIA-PACIFIC MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 26: ASIA-PACIFIC MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

TABLE 27: LATIN AMERICA MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)

TABLE 28: LATIN AMERICA MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 29: LATIN AMERICA MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 30: LATIN AMERICA MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 31: LATIN AMERICA MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

TABLE 32: MIDDLE EAST AND AFRICA MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)

TABLE 33: MIDDLE EAST AND AFRICA MACHINE LEARNING MARKET, BY DEPLOYMENT MODE, 2019-2027 (IN $ MILLION)

TABLE 34: MIDDLE EAST AND AFRICA MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)

TABLE 35: MIDDLE EAST AND AFRICA MACHINE LEARNING MARKET, BY SERVICE, 2019-2027 (IN $ MILLION)

TABLE 36: MIDDLE EAST AND AFRICA MACHINE LEARNING MARKET, BY END-USER, 2019-2027 (IN $ MILLION)

List of Figures

FIGURE 1: KEY BUYING IMPACT ANALYSIS

FIGURE 2: MARKET ATTRACTIVENESS INDEX

FIGURE 3: INDUSTRY COMPONENTS

FIGURE 4: INDUSTRY PLAYER POSITIONING IN 2018 (IN %)

FIGURE 5: VOLUME OF DATA CREATED WORLDWIDE, 2010-2025 (IN ZETTABYTES)

FIGURE 6: NUMBER OF CONNECTED DEVICES WORLDWIDE, 2015-2025

FIGURE 7: GLOBAL MACHINE LEARNING MARKET, BY CLOUD, 2019-2027 (IN $ MILLION)

FIGURE 8: GLOBAL MACHINE LEARNING MARKET, BY ON-PREMISES, 2019-2027 (IN $ MILLION)

FIGURE 9: GLOBAL MACHINE LEARNING MARKET, BY LARGE ENTERPRISES, 2019-2027 (IN $ MILLION)

FIGURE 10: GLOBAL MACHINE LEARNING MARKET, BY SMALL & MEDIUM-SIZED ENTERPRISES (SMEs), 2019-2027 (IN $ MILLION)

FIGURE 11: GLOBAL MACHINE LEARNING MARKET, BY PROFESSIONAL SERVICES, 2019-2027 (IN $ MILLION)

FIGURE 12: GLOBAL MACHINE LEARNING MARKET, BY MANAGED SERVICES, 2019-2027 (IN $ MILLION)

FIGURE 13: GLOBAL MACHINE LEARNING MARKET, BY BANKING, FINANCIAL SERVICES & INSURANCE (BFSI), 2019-2027 (IN $ MILLION)

FIGURE 14: GLOBAL MACHINE LEARNING MARKET, BY HEALTHCARE & LIFE SCIENCES, 2019-2027 (IN $ MILLION)

FIGURE 15: GLOBAL MACHINE LEARNING MARKET, BY RETAIL, 2019-2027 (IN $ MILLION)

FIGURE 16: GLOBAL MACHINE LEARNING MARKET, BY TELECOMMUNICATION, 2019-2027 (IN $ MILLION)

FIGURE 17: GLOBAL MACHINE LEARNING MARKET, BY GOVERNMENT & DEFENSE, 2019-2027 (IN $ MILLION)

FIGURE 18: GLOBAL MACHINE LEARNING MARKET, BY MANUFACTURING, 2019-2027 (IN $ MILLION)

FIGURE 19: GLOBAL MACHINE LEARNING MARKET, BY MEDIA & ADVERTISING, 2019-2027 (IN $ MILLION)

FIGURE 20: GLOBAL MACHINE LEARNING MARKET, BY ENERGY & UTILITIES, 2019-2027 (IN $ MILLION)

FIGURE 21: GLOBAL MACHINE LEARNING MARKET, BY OTHER END-USERS, 2019-2027 (IN $ MILLION)

FIGURE 22: GLOBAL MACHINE LEARNING MARKET, REGIONAL OUTLOOK, 2018 & 2027 (IN %)

FIGURE 23: UNITED STATES MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 24: CANADA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 25: UNITED KINGDOM MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 26: GERMANY MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 27: FRANCE MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 28: SPAIN MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 29: ITALY MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 30: RUSSIA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 31: REST OF EUROPE MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 32: CHINA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 33: JAPAN MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 34: INDIA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 35: SOUTH KOREA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 36: ASEAN COUNTRIES MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 37: AUSTRALIA & NEW ZEALAND MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 38: REST OF ASIA-PACIFIC MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 39: BRAZIL MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 40: MEXICO MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 41: REST OF LATIN AMERICA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 42: UNITED ARAB EMIRATES MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 43: TURKEY MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 44: SAUDI ARABIA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 45: SOUTH AFRICA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

FIGURE 46: REST OF MIDDLE EAST & AFRICA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)

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