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Market Research Report

Asia Pacific Machine Learning Market Forecast 2019-2027

Published by Inkwood Research Product code 678054
Published Content info 110 Pages
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Asia Pacific Machine Learning Market Forecast 2019-2027
Published: August 12, 2019 Content info: 110 Pages
Description

KEY FINDINGS

The Asia-Pacific machine learning market is predicted to contribute $XX million by 2027 while registering the CAGR of 32.92% in the global market by the end of the forecast period of 2019-2027. The widening consumer base of machine learning technology accompanied by government policies promoting artificial intelligence in the region is showcasing tremendous opportunities for market growth.

MARKET INSIGHTS

Countries like India, China, Japan, and Australia are expected to showcase considerable growth over the forecast period. The Indian machine learning is primarily driven by the entry of start-ups with advanced machine learning platform and services coupled with government initiatives to promote the technology. Data scientists, programmers, or machine learning codes are made available by managed machine learning service providers for installation, integration, and maintenance of machine learning solutions. Significant applications of managed services are found in automation, predictive analysis, ERP, etc. Though the technological advancements and its adoption are fuelling the market growth, the complexities involved in managing sensitive data of companies along with the technical limitations are hindering market development.

COMPETITIVE INSIGHTS

Fair Isaac Corporation (FICO), Google Inc., Fractal Analytics, IBM Corporation, Dell Inc., and Hewlett Packard Enterprise (HPE), among others, are examples of few firms providing machine learning services in the market. Though the market has the presence of large organizations, less regulatory norms, capital investment, and lucrativeness of the market is attracting new players. Also, the rising adoption of machine learning across industries is leading to the emergence of start-ups in the region.

Table of Contents
Product Code: 20899

Table of contents

1. RESEARCH SCOPE

  • 1.1. STUDY GOALS
  • 1.2. SCOPE OF THE MARKET STUDY
  • 1.3. WHO WILL FIND THIS REPORT USEFUL?
  • 1.4. STUDY AND FORECASTING YEARS

2. RESEARCH METHODOLOGY

  • 2.1. SOURCES OF DATA
    • 2.1.1. SECONDARY DATA
    • 2.1.2. PRIMARY DATA
  • 2.2. TOP-DOWN APPROACH
  • 2.3. BOTTOM-UP APPROACH
  • 2.4. DATA TRIANGULATION

3. EXECUTIVE SUMMARY

  • 3.1. MARKET SUMMARY
  • 3.2. KEY FINDINGS
    • 3.2.1. CHINA & INDIA LED ASIA PACIFIC TO BE THE FASTEST-GROWING MARKET
    • 3.2.2. CLOUD IS THE MOST PREFERRED DEPLOYMENT MODE
    • 3.2.3. SMALL & MEDIUM-SIZED ENTERPRISES (SMEs) IS PROJECTED TO GROW AT FASTEST CAGR
    • 3.2.4. GROWING NUMBER OF START-UPS IN MACHINE LEARNING

4. MARKET DYNAMICS

  • 4.1. TIMELINE OF MACHINE LEARNING
  • 4.2. PARENT MARKET ANALYSIS: ARTIFICIAL INTELLIGENCE
  • 4.3. MARKET SCOPE & DEFINITION
  • 4.4. MARKET DRIVERS
    • 4.4.1. PROLIFERATION IN DATA GENERATION
    • 4.4.2. RISING ROBOTIZATION ACROSS NUMEROUS VERTICALS
    • 4.4.3. CONTINUAL ADVANCEMENTS IN MACHINE LEARNING
    • 4.4.4. GROWING ACCEPTANCE OF CONNECTED DEVICES
    • 4.4.5. UPSURGE IN ADOPTION OF DATA-DRIVEN APPLICATIONS
  • 4.5. MARKET RESTRAINTS
    • 4.5.1. COMPLEXITIES IN MANAGING SENSITIVE DATA
    • 4.5.2. TECHNOLOGICAL LIMITATIONS
  • 4.6. MARKET OPPORTUNITIES
    • 4.6.1. GROWING INTEREST IN INTELLIGENT BUSINESS PROCESSES
    • 4.6.2. INTEGRATION OF BIG DATA WITH ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
    • 4.6.3. HIGH DEMAND FROM NUMEROUS END USER INDUSTRIES
  • 4.7. MARKET CHALLENGES
    • 4.7.1. ETHICAL IMPLICATIONS OF ALGORITHMS DEPLOYED
    • 4.7.2. SUSCEPTIBLE TO HARDWARE & SOFTWARE MALFUNCTIONS

5. MARKET BY DEPLOYMENT

  • 5.1. CLOUD
  • 5.2. ON-PREMISE

6. MARKET BY SERVICES

  • 6.1. PROFESSIONAL SERVICES
  • 6.2. MANAGED SERVICES

7. MARKET BY ORGANIZATION SIZE

  • 7.1. LARGE ENTERPRISES
  • 7.2. SMALL & MEDIUM-SIZED ENTERPRISES (SMEs)

8. MARKET BY INDUSTRY VERTICALS

  • 8.1. BANKING, FINANCIAL SERVICES & INSURANCE (BFSI)
  • 8.2. HEALTHCARE & LIFE SCIENCES
  • 8.3. RETAIL
  • 8.4. TELECOMMUNICATION
  • 8.5. GOVERNMENT & DEFENSE
  • 8.6. MANUFACTURING
  • 8.7. ENERGY & UTILITIES
  • 8.8. MEDIA & ADVERTISING
  • 8.9. OTHER VERTICALS

9. KEY ANALYTICS

  • 9.1. PORTER'S FIVE FORCE MODEL
    • 9.1.1. THREAT OF NEW ENTRANTS
    • 9.1.2. THREAT OF SUBSTITUTE
    • 9.1.3. BARGAINING POWER OF SUPPLIERS
    • 9.1.4. BARGAINING POWER OF BUYERS
    • 9.1.5. THREAT OF COMPETITIVE RIVALRY
  • 9.2. KEY BUYING CRITERIA
    • 9.2.1. PRICE
    • 9.2.2. SCALABILITY
    • 9.2.3. TRAINING TIME
    • 9.2.4. APPLICATION
  • 9.3. VALUE CHAIN ANALYSIS
    • 9.3.1. SOFTWARE DEVELOPMENT
    • 9.3.2. CLOUD
    • 9.3.3. USERS
  • 9.4. PATENT ANALYSIS
  • 9.5. OPPORTUNITY MATRIX
  • 9.6. VENDOR LANDSCAPE

10. GEOGRAPHICAL ANALYSIS

  • 10.1. ASIA PACIFIC
    • 10.1.1. CHINA
    • 10.1.2. JAPAN
    • 10.1.3. INDIA
    • 10.1.4. SOUTH KOREA
    • 10.1.5. AUSTRALIA
    • 10.1.6. REST OF ASIA PACIFIC

11. COMPETITIVE LANDSCAPE

  • 11.1. MARKET SHARE ANALYSIS
  • 11.2. CORPORATE STRATEGIES
    • 11.2.1. MERGER & ACQUISITIONS
    • 11.2.2. PRODUCT DEVELOPMENT
    • 11.2.3. COLLABORATION & PARTNERSHIP
    • 11.2.4. OTHER KEY STRATEGIES
  • 11.3. COMPANY PROFILES
    • 11.3.1. AMAZON WEB SERVICES INC.
    • 11.3.2. BAIDU, INC.
    • 11.3.3. DELL, INC.
    • 11.3.4. FAIR ISAAC CORPORATION (FICO)
    • 11.3.5. FRACTAL ANALYTICS
    • 11.3.6. GOOGLE, INC.
    • 11.3.7. HEWLETT PACKARD ENTERPRISE (HPE)
    • 11.3.8. IBM CORPORATION (INTERNATIONAL BUSINESS MACHINES)
    • 11.3.9. INTEL CORPORATION
    • 11.3.10. MICROSOFT CORPORATION
    • 11.3.11. ORACLE CORPORATION
    • 11.3.12. SAP SE
    • 11.3.13. TERADATA CORPORATION
    • 11.3.14. TIBCO SOFTWARE INC.
    • 11.3.15. TRADEMARKVISION

LIST OF TABLES

  • TABLE 1: ASIA PACIFIC MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)
  • TABLE 2: LIST OF PROMINENT START-UPS IN MACHINE LEARNING
  • TABLE 3: TIMELINE OF MACHINE LEARNING
  • TABLE 4: ASIA PACIFIC MACHINE LEARNING MARKET, BY DEPLOYMENT, 2019-2027 (IN $ MILLION)
  • TABLE 5: ASIA PACIFIC MACHINE LEARNING MARKET, BY SERVICES, 2019-2027 (IN $ MILLION)
  • TABLE 6: ASIA PACIFIC MACHINE LEARNING MARKET, BY ORGANIZATION SIZE, 2019-2027 (IN $ MILLION)
  • TABLE 7: ASIA PACIFIC MACHINE LEARNING MARKET, BY INDUSTRY VERTICALS, 2019-2027 (IN $ MILLION)
  • TABLE 8: OPPORTUNITY MATRIX
  • TABLE 9: VENDOR LANDSCAPE
  • TABLE 10: PATENTS FILLED IN MACHINE LEARNING BY KEY TECHNOLOGY COMPANIES, 2017
  • TABLE 11: ASIA PACIFIC MACHINE LEARNING MARKET, BY COUNTRY, 2019-2027 (IN $ MILLION)
  • TABLE 12: LIST OF MERGER & ACQUISITIONS
  • TABLE 13: LIST OF PRODUCT DEVELOPMENT
  • TABLE 14: LIST OF COLLABORATION & PARTNERSHIP
  • TABLE 15: LIST OF OTHER KEY STRATEGIES

LIST OF FIGURES

  • FIGURE 1: ASIA PACIFIC MACHINE LEARNING MARKET, BY INDUSTRY VERTICALS, 2018 & 2027 (IN %)
  • FIGURE 2: ASIA PACIFIC MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 3: NUMBER OF CONNECTED DEVICES WORLDWIDE, 2015-2025
  • FIGURE 4: ASIA PACIFIC MACHINE LEARNING MARKET, BY CLOUD, 2019-2027 (IN $ MILLION)
  • FIGURE 5: ASIA PACIFIC MACHINE LEARNING MARKET, BY ON-PREMISE, 2019-2027 (IN $ MILLION)
  • FIGURE 6: ASIA PACIFIC MACHINE LEARNING MARKET, BY PROFESSIONAL SERVICES, 2019-2027 (IN $ MILLION)
  • FIGURE 7: ASIA PACIFIC MACHINE LEARNING MARKET, BY MANAGED SERVICES, 2019-2027 (IN $ MILLION)
  • FIGURE 8: ASIA PACIFIC MACHINE LEARNING MARKET, BY LARGE ENTERPRISES, 2019-2027 (IN $ MILLION)
  • FIGURE 9: ASIA PACIFIC MACHINE LEARNING MARKET, BY SMALL & MEDIUM-SIZED ENTERPRISES (SMEs), 2019-2027 (IN $ MILLION)
  • FIGURE 10: ASIA PACIFIC MACHINE LEARNING MARKET, BY BANKING, FINANCIAL SERVICES & INSURANCE (BFSI), 2019-2027 (IN $ MILLION)
  • FIGURE 11: ASIA PACIFIC MACHINE LEARNING MARKET, BY HEALTHCARE & LIFE SCIENCES, 2019-2027 (IN $ MILLION)
  • FIGURE 12: ASIA PACIFIC MACHINE LEARNING MARKET, BY RETAIL, 2019-2027 (IN $ MILLION)
  • FIGURE 13: ASIA PACIFIC MACHINE LEARNING MARKET, BY TELECOMMUNICATION, 2019-2027 (IN $ MILLION)
  • FIGURE 14: ASIA PACIFIC MACHINE LEARNING MARKET, BY GOVERNMENT & DEFENSE, 2019-2027 (IN $ MILLION)
  • FIGURE 15: ASIA PACIFIC MACHINE LEARNING MARKET, BY MANUFACTURING, 2019-2027 (IN $ MILLION)
  • FIGURE 16: ASIA PACIFIC MACHINE LEARNING MARKET, BY MEDIA & ADVERTISING, 2019-2027 (IN $ MILLION)
  • FIGURE 17: ASIA PACIFIC MACHINE LEARNING MARKET, BY ENERGY & UTILITIES, 2019-2027 (IN $ MILLION)
  • FIGURE 18: ASIA PACIFIC MACHINE LEARNING MARKET, BY OTHER VERTICALS, 2019-2027 (IN $ MILLION)
  • FIGURE 19: PORTER'S FIVE FORCE ANALYSIS
  • FIGURE 20: KEY BUYING IMPACT ANALYSIS
  • FIGURE 21: VALUE CHAIN ANALYSIS
  • FIGURE 22: PATENTS FILLED IN ARTIFICIAL INTELLIGENCE BY KEY TECHNOLOGY COMPANIES, 2009-2017
  • FIGURE 23: ASIA PACIFIC MACHINE LEARNING MARKET, REGIONAL OUTLOOK, 2018 & 2027 (IN %)
  • FIGURE 24: CHINA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 25: JAPAN MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 26: INDIA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 27: SOUTH KOREA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 28: AUSTRALIA MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 29: REST OF ASIA PACIFIC MACHINE LEARNING MARKET, 2019-2027 (IN $ MILLION)
  • FIGURE 30: MARKET SHARE ANALYSIS OF KEY PLAYERS IN 2017 (IN %)
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