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市場調査レポート

マシンラーニング (機械学習) の世界市場 2022年:BFSI・医療&ライフサイエンス・小売・通信・政府&防衛・製造・エネルギー&ユーティリティ

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

発行 MarketsandMarkets 商品コード 556902
出版日 ページ情報 英文 162 Pages
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マシンラーニング (機械学習) の世界市場 2022年:BFSI・医療&ライフサイエンス・小売・通信・政府&防衛・製造・エネルギー&ユーティリティ 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
出版日: 2017年09月14日 ページ情報: 英文 162 Pages
概要

マシンラーニング (機械学習) の市場規模は、2017年の14億1,000万米ドルから、2022年までに88億1,000万米ドルへ、44.1%のCAGR (年間複合成長率) で拡大すると予測されています。大型・多次元データの急増、リアルタイムの問題を解決することに対する注目の高まり、ならびに洗練されたアルゴリズムプラットフォーム・ツールの需要拡大は、世界にわたるマシンラーニングの導入を促進しています。

当レポートでは、世界のマシンラーニング (機械学習) 市場を調査し、市場の概要、市場への各種影響因子および市場機会の分析、垂直産業・展開形態・組織規模・サービス・地域別の動向と市場規模の推移と予測、競合環境、主要企業のプロファイルなど、体系的な情報を提供しています。

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

  • マシンラーニング市場における魅力的な市場機会
  • マシンラーニング市場:3大垂直産業
  • ライフサイクル分析:地域別

第5章 市場概要・産業動向

  • イントロダクション
  • 市場力学
    • 成長推進因子
    • 成長抑制因子
    • 市場機会
    • 課題
  • 産業動向
    • マシンラーニング
  • マシンラーニングプロセス
  • 規制の影響
    • イントロダクション
    • 上場企業会計改革および投資家保護法
    • EU一般データ保護規則 (GDPR)
    • BASEL

第6章 マシンラーニング市場分析:垂直産業別

  • イントロダクション
    • 銀行、金融サービスおよび保険におけるマシンラーニング用途
      • 不正・リスク管理
      • 顧客セグメンテーション
      • 販売・マーケティングキャンペーン管理
      • 投資予測
      • デジタルアシスタンス
      • その他
    • 医療・ライフサイエンスにおけるマシンラーニング用途
      • 疾病特定・診断
      • 画像分析
      • 個別化治療
      • 創薬/製造
      • その他
    • 小売りにおけるマシンラーニング用途
      • 在庫計画
      • レコメンデーションエンジン
      • アップセル・クロスチャンネルマーケティング
      • セグメンテーション・ターゲッティング
      • その他
    • 通信におけるマシンラーニング用途
      • 顧客分析
      • ネットワークセキュリティ
      • ネットワーク最適化
      • その他
    • 政府・防衛におけるマシンラーニング用途
      • 自律型防衛システム
      • スレットインテリジェンス
      • その他
    • 製造業におけるマシンラーニング用途
      • 予知保全
      • 収益推計
      • 需要予測
      • サプライチェーン管理
      • その他
    • エネルギー・ユーティリティにおけるマシンラーニング用途
      • 電力/エネルギー利用分析
      • 地震探査データ処理
      • 炭素排出量
      • スマートグリッド管理
      • その他
    • その他の用途

第7章 マシンラーニング市場分析:展開形態別

  • イントロダクション
  • クラウド
  • オンプレミス

第8章 マシンラーニング市場分析:組織規模別

  • イントロダクション
  • 大企業
  • 中小企業

第9章 マシンラーニング市場分析:サービス別

  • イントロダクション
  • 専門サービス
  • マネージドサービス

第10章 地域分析

  • イントロダクション
  • 北米
  • 欧州
  • アジア太平洋
  • 中東・アフリカ
  • ラテンアメリカ

第11章 競合情勢

  • 市場ランキング

第12章 企業プロファイル

  • INTERNATIONAL BUSINESS MACHINES CORPORATION (IBM)
  • MICROSOFT CORPORATION
  • SAP SE
  • SAS INSTITUTE INC.
  • AMAZON WEB SERVICES, INC.
  • BIGML, INC.
  • GOOGLE INC.
  • FAIR ISAAC CORPORATION
  • BAIDU, INC.
  • HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
  • INTEL CORPORATION
  • H2O.AI

第13章 付録

目次
Product Code: TC 5578

The machine learning market is projected to grow at a CAGR of 44.1% during the forecast period

The 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 proliferation of large and multidimensional data sets, rising focus towards solving real-time problems from data along with rising demand for sophisticated algorithm platform and tool is driving the adoption of machine learning across the globe.

The major issue in front of 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.

Professional service segment is expected to have a larger market share during the forecast period

The service segment in the machine learning market includes professional and managed services. Majority of the companies do not have the expertise to successfully manage infrastructure, and hence, they outsource these services to third-party partners to maintain the level of security and safety. The growth of the professional services segment is mainly governed by the complexity of operations and increasing deployment of machine learning solutions.

Large enterprises segment is expected to have a larger market size during the forecast period

The organization size segment in the machine learning market includes Small and Medium-Sized Enterprises (SMEs) and large enterprises. Emergence in the demand for cloud computing, cloud storage, IoT connected devices, and excessive use of smartphones are some of the prime reasons why large enterprises have turned toward machine learning for processing data. In large enterprises, machine learning has a huge potential for the big data technology in allowing precise decision-making for superior performance.

Asia Pacific (APAC) is expected to witness the highest growth rate during the forecast period

APAC is estimated to grow at the highest CAGR during the forecast period. Factors, such as continual growth in the mobile network, increasing the complexity of business, rise in demand for intelligent business processes, and exponential growth in data generation throughout the industry verticals are driving the machine learning market in the APAC region. The North American region is expected to have the largest market share during the forecast period. The major growth drivers for this region are the large-scale investments in implementing machine learning services due to the growth in demand for processed data. Moreover, recently the region also witnessed the widespread adoption of cloud-based machine learning platform among large enterprises and SMEs across multiple verticals.

In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews were conducted with the key people.

  • By Company Type - Tier 1 - 18%, Tier 2 - 48%, and Tier 3 - 34%
  • By Designation - C-level - 22%, Director-level - 43%, and Others - 35%
  • By Region -North America - 42%, EMEA (Europe, Middle East and Africa) - 32%, and APAC (Asia Pacific) - 26%

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).

Research Coverage:

The machine learning market has been segmented on the basis of verticals, deployment modes, organization sizes, services, and region. The machine learning is segmented on the basis of verticals into Banking, Financial Services, and Insurance (BFSI), energy and utilities, healthcare and life sciences, retail, telecommunication, manufacturing, government and defense, and others (transportation, agriculture, media and entertainment, and education). The verticals are further segmented on the basis of application areas, applications of machine learning in BFSI includes fraud and risk management, investment prediction, sales and marketing campaign management, customer segmentation, digital assistance, and others (compliance management and credit underwriting). Applications of machine learning in healthcare and life sciences includes disease identification and diagnosis, image analytics, drug discovery/manufacturing, personalized treatment, and others (clinical trial research and epidemic outbreak prediction). Applications of machine learning in retail includes inventory planning, upsell and cross channel marketing, segmentation and targeting, recommendation engines, and others (customer ROI and lifetime value and customization management). Applications of machine learning in telecommunication includes customer analytics, network optimization, network security, and others (digital assistance/contact centers analytics and marketing campaign analytics). Applications of machine learning in government and defense includes threat intelligence, autonomous defense system, and others (sustainability and operational analytics). Applications of machine learning in manufacturing includes predictive maintenance, demand forecasting, revenue estimation, supply chain management, and others (root cause analysis and telematics). Applications of machine learning in energy and utilities includes power/energy usage analytics, seismic data processing, smart grid management, carbon emission, and others (customer specific pricing and renewable energy management).

The services offered in the machine learning market include professional and managed services. The deployment modes in the machine learning market include the cloud and on-premises. The organization sizes are segmented into Small and Medium-Sized Enterprises (SMEs) and large enterprises. Finally, on the basis of regions, the machine learning market is segmented into North America, Europe, APAC, Middle East and Africa (MEA), and Latin America.

The report will help the market leaders and new entrants in the machine learning market in the following ways:

  • 1. The report segments the market into various subsegments, hence it covers the market comprehensively. The report provides the closest approximations of the revenue numbers for the overall market and the subsegments. The market numbers are further split across different verticals and regions.
  • 2. The report helps in understanding the overall growth of the market. It provides information on the key market drivers, restraints, challenges, and opportunities.
  • 3. The report helps in understanding the competitors better and gaining more insights to strengthen the organization's position in the market. The study also presents the positioning of the key players based on their product offerings and business strategies.

TABLE OF CONTENTS

1. INTRODUCTION

  • 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

  • 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

4. PREMIUM INSIGHTS

  • 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

  • 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

  • 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

  • 7.1. INTRODUCTION
  • 7.2. CLOUD
  • 7.3. ON-PREMISES

8. MACHINE LEARNING MARKET ANALYSIS, BY ORGANIZATION SIZE

  • 8.1. INTRODUCTION
  • 8.2. LARGE ENTERPRISES
  • 8.3. SMALL AND MEDIUM-SIZED ENTERPRISES

9. MACHINE LEARNING MARKET ANALYSIS, BY SERVICE

  • 9.1. INTRODUCTION
  • 9.2. PROFESSIONAL SERVICES
  • 9.3. MANAGED SERVICES

10. GEOGRAPHIC ANALYSIS

  • 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

  • 11.1. MARKET RANKING FOR THE MACHINE LEARNING MARKET, 2017

12. COMPANY PROFILES (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

  • 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

  • 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: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015-2022 (USD MILLION)
  • TABLE 13: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION)
  • TABLE 14: MACHINE LEARNING MARKET SIZE, BY SERVICE, 2015-2022 (USD MILLION)
  • TABLE 15: MACHINE LEARNING 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: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION)
  • TABLE 25: NORTH AMERICA: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015-2022 (USD MILLION)
  • TABLE 26: NORTH AMERICA: MACHINE LEARNING 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: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION)
  • TABLE 36: EUROPE: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015-2022 (USD MILLION)
  • TABLE 37: EUROPE: MACHINE LEARNING 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: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION)
  • TABLE 58: MIDDLE EAST AND AFRICA: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015-2022 (USD MILLION)
  • TABLE 59: MIDDLE EAST AND AFRICA: MACHINE LEARNING 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: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015-2022 (USD MILLION)
  • TABLE 69: LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015-2022 (USD MILLION)
  • TABLE 70: LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY SERVICE, 2015-2022 (USD MILLION)
  • TABLE 71: MARKET RANKING FOR THE MACHINE LEARNING MARKET, 2017

LIST OF FIGURES

  • FIGURE 1: GLOBAL MACHINE LEARNING MARKET: 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: MACHINE LEARNING MARKET SNAPSHOT (2017), BY HEALTHCARE AND LIFE SCIENCES APPLICATION
  • FIGURE 10: MACHINE LEARNING MARKET SNAPSHOT (2017), BY RETAIL APPLICATION
  • FIGURE 11: MACHINE LEARNING MARKET SNAPSHOT (2017), BY TELECOMMUNICATION APPLICATION
  • FIGURE 12: MACHINE LEARNING MARKET SNAPSHOT (2017), BY GOVERNMENT AND DEFENSE APPLICATION
  • FIGURE 13: MACHINE LEARNING MARKET SNAPSHOT (2017), BY MANUFACTURING APPLICATION
  • FIGURE 14: MACHINE LEARNING MARKET SNAPSHOT (2017), BY ENERGY AND UTILITIES APPLICATION
  • FIGURE 15: MACHINE LEARNING MARKET SNAPSHOT (2017), BY SERVICE
  • FIGURE 16: MACHINE LEARNING 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
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