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Machine learning as a Service Market by Component (Software, and Services), Organization Size (Large Enterprises, and Small & Medium Enterprises), End-Use Industry (Aerospace & Defense, IT & Telecom, Energy & Utilities, Public sector, Manufacturing, BFSI, Healthcare, Retail, and Others), Application (Marketing & Advertising, Fraud Detection & Risk Management, Predictive analytics, Augmented & Virtual reality, Natural Language processing, Computer vision, Security & surveillance, and Others) - Global Opportunity and Forecasts, 2016-2023

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Pages: 204
Aug 2017 | 1575 Views
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Author's : Pankaj Lanjudkar
Tables: 112
Charts: 50
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Machine learning as a Service Market Overview:

Machine learning as a service Market incorporates a comprehensive range of services and solutions and techniques interrelated closely to artificial intelligence (AI), which performs statistical analysis of input data to understand its current or future relationship and performance. Machine learning makes use of massive amount of input data to deliver improved analytical output while optimizing workflow for varied industry verticals. Machine learning as a service (MLaaS) incorporates range of services that offer machine learning tools through cloud computing services.

Growth in IT expenditure in the emerging nations and technological advancements for workflow optimization fuels the demand for advanced analytical systems, thereby driving the MLaaS market growth. In addition, rise in penetration of cloud-based solutions, growth associated with artificial intelligence and cognitive computing market, and increase in market for prediction solutions also fuel the demand for machine learning as a service market. However, dearth of trained professionals is expected to restrain the MLaaS market growth during the forecast period. Furthermore, increased application areas for MLaaS is expected to create lucrative opportunities for market expansion.

Segment Overview

The global machine learning as a service market is segmented based on component, organization size, end-use industry, application, and geography. The component segment is bifurcated into software and services. Based on organization size, it is divided into large enterprises, and small & medium enterprises. The application segment is categorized into marketing & advertising, fraud detection & risk management, predictive analytics, augmented & virtual reality, natural language processing, computer vision, security & surveillance, and others. On the basis of end-use industry, it is classified into aerospace & defense, IT & telecom, energy & utilities, public sector, manufacturing, BFSI, healthcare, retail, and others. By geography, the machine learning as a service market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.

Key Market Segmentation

MACHINE LEARNING AS A SERVICE MARKET KEY MARKET SEGMENTATION

Top Impacting Factors

The global machine learning as a service market is influenced by several factors that include growth in demand for increased application areas, growth associated with artificial intelligence (AI) & cognitive computing market, dearth of trained professionals, and impact of developing economies. All these factors collectively create opportunities for market growth. However, each factor is expected to have its definite impact on the MLaaS market share.

Top Impacting Factors

MACHINE LEARNING AS A SERVICE MARKET TOP IMPACTING FACTORS

Impact of Developing Economies

The developing countries possess high potential for the machine learning as a service market, owing to a low adoption base and developing infrastructure. Further, the need for cost-effective predictive solutions among end-use industries is expected to fuel the demand for MLaaS.

Increased Application Areas

Increase in automation and advancement in technology are expected to boost the market growth during the forecast period. Machine learning technology has driven the emergence of predictive analytics which experiences rapid grow in consumption and has become an important aspect of all business operations and processes. Predictive analytics is used in several online activities such as Amazon product recommendations and Google search box auto suggestion. For instance, Netflix, an online movie rental service giant, used machine learning to predict the movies which a customer would prefer to view. Recently, Walmart Labs announced the acquisition of Inkiru, a specialized company in machine learning technology. This acquisition helped Walmart provide better site personalization and fraud prevention. Earlier, adoption of MLaaS was largely among developed nations, but in the recent years, most of the emerging economies such as India and China, have started implementing MLaaS.

Dearth of Skilled Workforce

At present, the impact of this factor on the market growth is high, which limits end users to invest into advanced solutions and services. However, by 2023, the impact is projected to decrease due to availability of skilled workforce.

Growth Associated With Artificial Intelligence and Cognitive Computing Market

Improved productivity, diversified application areas, increased customer satisfaction, and big data integration drive the artificial intelligence (AI) market. Cognitive computing, with the help of different technologies such as natural language processing, machine learning and automated reasoning, translates unstructured data to sense, infer, and predict the best solution. Cognitive computing is majorly used in BFSI, healthcare, security, retail, e-commerce, and other sectors. Increase in volume of unstructured data and advancements in technology majorly drive the cognitive computing market. AI has different application areas across media & advertising, finance, retail, healthcare, automotive & transportation, agriculture, law, educational institutions, oil & gas, and other industries. The impact of this factor is expected to be higher in future, since machine-learning algorithms are anticipated to be used for preventing payment frauds and cyberterrorism. Furthermore, AI is estimated to have a strong impact on healthcare advancements and lead to more accurate treatments and prevention of medical conditions.

Key Benefits

  • The report provides an overview of the trends, structure, drivers, challenges, and opportunities in the global machine learning as a service market.
  • Porters Five Forces analysis highlights the potential of buyers & suppliers, and provides insights on the competitive structure of the market to determine the investment pockets.
  • Current and future trends adopted by key market players are highlighted to determine overall competitiveness.
  • The quantitative analysis of the market through 20162023 is provided to elaborate the market potential.

Machine learning as a Service Market Key Segments:

By Component

  • Software
  • Services

By Organization Size

  • Large Enterprises
  • Small & Medium Enterprises

By End-Use Industry

  • Aerospace & Defence
  • IT & Telecom
  • Energy & Utilities
  • Public sector
  • Manufacturing
  • BFSI
  • Healthcare
  • Retail
  • Others

By Application

  • Marketing & Advertising
  • Fraud Detection & Risk Management
  • Predictive analytics
  • Augmented & Virtual reality
  • Natural Language processing
  • Computer vision
  • Security & surveillance
  • Others

By Geography

  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • UK
    • France
    • Germany
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • India
    • Rest of Asia-Pacific
  • LAMEA
    • Latin America
    • Middle East
    • Arica

Key Players Profiled in the Report

  • Google Inc.
  • SAS Institute Inc.
  • FICO
  • Hewlett Packard Enterprise
  • Yottamine Analytics
  • Amazon Web Services
  • BigML, Inc.
  • Microsoft Corporation
  • Predictron Labs Ltd.
  • IBM Corporation
 

Chapter: 1 INTRODUCTION

1.1. REPORT DESCRIPTION
1.2. KEY BENEFITS
1.3. KEY MARKET SEGMENTS
1.4. KEY MARKET SEGMENTATION
1.5. RESEARCH METHODOLOGY

1.5.1. Secondary research
1.5.2. Primary research
1.5.3. Analyst tools and models

Chapter: 2 EXECUTIVE SUMMARY

2.1. CXO PERSPECTIVE

Chapter: 3 MARKET OVERVIEW

3.1. MARKET DEFINITION AND SCOPE
3.2. KEY FINDINGS

3.2.1. Top impacting factors
3.2.2. Top investment pockets
3.2.3. Top winning strategies

3.3. PORTER’S FIVE FORCES ANALYSIS

3.3.1. Moderate-to-low bargaining power of suppliers
3.3.2. Moderate-to-low bargaining power of buyers
3.3.3. Moderate-to-high threat of substitutes
3.3.4. High threat of new entrants
3.3.5. Moderate-to-high competitive rivalry

3.4. KEY PLAYER POSITIONING, 2016 (%)
3.5. MARKET DYNAMICS

3.5.1. Drivers

3.5.1.1. Increased market for cloud computing
3.5.1.2. Growth associated with artificial intelligence and cognitive computing

3.5.2. Restraints

3.5.2.1. Dearth of trained professionals.

3.5.3. Opportunities

3.5.3.1. Increased adoption of analytical solutions
3.5.3.2. Increased application areas

Chapter: 4 GLOBAL MACHINE LEARNING AS A SERVICE MARKET, BY COMPONENT

4.1. OVERVIEW
4.2. SOFTWARE

4.2.1. Key market trends
4.2.2. Key growth factors and opportunities
4.2.3. Market size and forecast

4.3. SERVICES

4.3.1. Key market trends
4.3.2. Key growth factors and opportunities
4.3.3. Market size and forecast

Chapter: 5 GLOBAL MACHINE LEARNING AS A SERVICE MARKET, BY ORGANIZATION SIZE

5.1. OVERVIEW
5.2. LARGE ENTERPRISES

5.2.1. Key market trends
5.2.2. Key growth factors and opportunities
5.2.3. Market size and forecast

5.3. SMALL AND MEDIUM ENTERPRISES

5.3.1. Key market trends
5.3.2. Key growth factors and opportunities
5.3.3. Market size and forecast

Chapter: 6 GLOBAL MACHINE LEARNING AS A SERVICE MARKET, BY END-USE INDUSTRY

6.1. OVERVIEW
6.2. AEROSPACE & DEFENCE

1.2.1. Key market trends
1.2.1 Key Growth Factors and Opportunities
1.2.2. Market size and forecast

6.3. IT & TELECOM

1.2.3. Key market trends
1.3.1 Key Growth Factors and Opportunities
1.2.4. Market size and forecast

6.4. ENERGY & UTILITIES

1.2.5. Key market trends
1.3.2 Key Growth factors and Opportunities
1.2.6. Market size and forecast

6.5. PUBLIC SECTOR

1.2.7. Key market trends
1.4.1 Key Growth Factors and Opportunities
1.2.8. Market size and forecast

6.6. MANUFACTURING

1.2.9. Key market trends
1.3.3 Key Growth factors and Opportunities
1.2.10. Market size and forecast

6.7. BANKING, FINANCIAL SERVICES, & INSURANCE (BFSI)

1.2.11. Key market trends
1.3.4 Key Growth Factors and Opportunities
1.2.12. Market size and forecast

6.8. HEALTHCARE

1.2.13. Key market trends
1.6.1 Key Growth Factors and Opportunities
1.2.14. Market size and forecast

6.9. RETAIL

1.2.15. Key market trends
1.5.1 Key Growth Factors and Opportunities
1.2.16. Market size and forecast

6.10. OTHERS

1.2.17. Key market trends
1.3.5 Key Growth factors and Opportunities
1.2.18. Market size and forecast

Chapter: 7 GLOBAL COMMERCIAL AIRCRAFT HEATH MONITORING SYSTEM MARKET, BY APPLICATION

7.1. OVERVIEW
7.2. MARKETING AND ADVERTISING

7.2.1. Key market trends
7.2.2. Key growth factors and opportunities
7.2.3. Market size and forecast

7.3. FRAUD DETECTION AND RISK MANAGEMENT

7.3.1. Key market trends
7.3.2. Key growth factors and opportunities
7.3.3. Market size and forecast

7.4. PREDICTIVE ANALYTICS

7.4.1. Key market trends
7.4.2. Key growth factors and opportunities
7.4.3. Market size and forecast

7.5. AUGMENTED & VIRTUAL REALITY

7.5.1. Key market trends
7.5.2. Key growth factors and opportunities
7.5.3. Market size and forecast

7.6. NATURAL LANGUAGE PROCESSING

7.6.1. Key market trends
7.6.2. Key growth factors and opportunities
7.6.3. Market size and forecast

7.7. COMPUTER VISION

7.7.1. Key market trends
7.7.2. Key growth factors and opportunities
7.7.3. Market size and forecast

7.8. SECURITY AND SURVEILLANCE

7.8.1. Key market trends
7.8.2. Key growth factors and opportunities
7.8.3. Market size and forecast

7.9. OTHERS

7.9.1. Key market trends
7.9.2. Key growth factors and opportunities
7.9.3. Market size and forecast

Chapter: 8 MACHINE LEARNING AS A SERVICE MARKET, BY REGION

8.1. OVERVIEW
8.2. NORTH AMERICA

8.2.1. Key market trends
8.2.2. Key growth factors and opportunities
8.2.3. Market size and forecast

8.2.3.1. Market size and forecast by country
8.2.3.2. U.S.
8.2.3.3. Market size and forecast
8.2.3.4. Canada
8.2.3.5. Market size and forecast
8.2.3.6. Mexico
8.2.3.7. Market size and forecast

8.3. EUROPE

8.3.1. Key market trends
8.3.2. Key growth factors and opportunities
8.3.3. Market size and forecast

8.3.3.1. Market size and forecast by country
8.3.3.2. UK
8.3.3.3. Market size and forecast
8.3.3.4. Germany
8.3.3.5. Market size and forecast
8.3.3.6. France
8.3.3.7. Market size and forecast
8.3.3.8. Rest of Europe
8.3.3.9. Market size and forecast

8.4. ASIA-PACIFIC

8.4.1. Key market trends
8.4.2. Key growth factors and opportunities
8.4.3. Market size and forecast

8.4.3.1. Market size and forecast by country
8.4.3.2. China
8.4.3.3. Market size and forecast
8.4.3.4. Japan
8.4.3.5. Market size and forecast
8.4.3.6. India
8.4.3.7. Market size and forecast
8.4.3.8. Rest of Asia-Pacific
8.4.3.9. Market size and forecast

8.5. LATIN AMERICA, THE MIDDLE EAST, & AFRICA (LAMEA)

8.5.1. Key market trends
8.5.2. Key growth factors and opportunities
8.5.3. Market size and forecast

8.5.3.1. Market size and forecast by region
8.5.3.2. Latin America
8.5.3.3. Market size and forecast
8.5.3.4. Middle East
8.5.3.5. Market size and forecast
8.5.3.6. Africa
8.5.3.7. Market size and forecast

Chapter: 9 COMPANY PROFILES

9.1. GOOGLE INC.

9.1.1. Company Overview
9.1.2. Financial performance
9.1.3. Key strategies & developments

9.2. SAS INSTITUTE INC.

9.2.1. Company Overview
9.2.2. Financial performance
9.2.3. Key strategies & developments

9.3. FICO

9.3.1. Company Overview
9.3.2. Financial performance
9.3.3. Key strategies & developments

9.4. HEWLETT PACKARD ENTERPRISE

9.4.1. Company Overview
9.4.2. Financial performance
9.4.3. Key strategies & developments

9.5. YOTTAMINE ANALYTICS

9.5.1. Company Overview
9.5.2. Financial performance
9.5.3. Key strategies & developments

9.6. AMAZON WEB SERVICES

9.6.1. Company Overview
9.6.2. Financial performance
9.6.3. Key strategies & developments

9.7. BIGML, INC.

9.7.1. Company Overview
9.7.2. Financial performance
9.7.3. Key strategies & developments

9.8. MICROSOFT CORPORATION

9.8.1. Company Overview
9.8.2. Financial performance
9.8.3. Key strategies & developments

9.9. PREDICTRON LABS LTD.

9.9.1. Company Overview
9.9.2. Financial performance
9.9.3. Key strategies & developments

9.10. IBM CORPORATION

9.10.1. Company Overview
9.10.2. Financial performance
9.10.3. Key strategies & developments

LIST OF TABLES

TABLE 1. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY COMPONENT, 2016-2023 ($MILLION)
TABLE 2. SOFTWARE MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 3. SERVICES MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 4. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY ORGANIZATION SIZE, 2016-2023 ($MILLION)
TABLE 5. LARGE ENTERPRISES MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 6. SMALL AND MEDIUM ENTERPRISES MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 7. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY END-USE INDUSTRY, 2016-2023 ($MILLION)
TABLE 8. AEROSPACE AND DEFENSE MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 9. IT AND TELECOM MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 10. ENERGY AND UTILITIES MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 11. PUBLIC SECTOR MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 12. MANUFACTURING MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 13. BFSI MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 14. HEALTHCARE MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 15. RETAIL MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 16. OTHERS MACHINE LEARNING AS A SERVICE MARKET, BY REGION, 2016-2023 ($MILLION)
TABLE 17. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY APPLICATION, 2016-2023 ($MILLION)
TABLE 18. MARKETING AND ADVERTISING MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 19. FRAUD DETECTION AND RISK MANAGEMENT MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 20. PREDICTIVE ANALYTICS MARKET BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 21. AUGMENTED & VIRTUAL REALITY MARKET, BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 22. NATURAL LANGUAGE PROCESSING MARKET, BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 23. COMPUTER VISION MARKET, BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 24. SECURITY AND SURVEILLANCE MARKET, BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 25. OTHERS MARKET, BY GEOGRAPHY, 2016-2023 ($MILLION)
TABLE 26. MACHINE LEARNING AS A SERVICE MARKET BY REGION, 2016-2023 ($MILLION)
TABLE 27. NORTH AMERICA: MACHINE LEARNING AS A SERVICE MARKET BY COUNTRY, 2016-2023 ($MILLION)
TABLE 28. EUROPE: MACHINE LEARNING AS A SERVICE MARKET BY COUNTRY, 2016-2023 ($MILLION)
TABLE 29. ASIA-PACIFIC: MACHINE LEARNING AS A SERVICE MARKET BY COUNTRY, 2016-2023 ($MILLION)
TABLE 30. LAMEA: MACHINE LEARNING AS A SERVICE MARKET BY REGION, 2016-2023 ($MILLION)
TABLE 31. COMPANY SNAPSHOT: GOOGLE INC.
TABLE 32. COMPANY SNAPSHOT: SAS INSTITUTE INC.
TABLE 33. COMPANY SNAPSHOT: FICO
TABLE 34. COMPANY SNAPSHOT: HEWLETT PACKARD ENTERPRISE
TABLE 35. COMPANY SNAPSHOT: YOTTAMINE ANALYTICS
TABLE 36. COMPANY SNAPSHOT: AMAZON WEB SERVICES
TABLE 37. COMPANY SNAPSHOT: BIGML, INC.
TABLE 38. COMPANY SNAPSHOT: MICROSOFT CORPORATION
TABLE 39. COMPANY SNAPSHOT: PREDICTRON LABS LTD.
TABLE 40. COMPANY SNAPSHOT: IBM CORPORATION

LIST OF FIGURES

FIGURE 1. KEY MARKET SEGMENTATION
FIGURE 2. ASIA-PACIFIC: A LUCRATIVE MARKET FOR MACHINE LEARNING AS A SERVICE MARKET
FIGURE 3. TOP IMPACTING FACTORS
FIGURE 4. TOP INVESTMENT POCKETS IN THE GLOBAL MACHINE LEARNING AS A SERVICE MARKET
FIGURE 5. TOP WINNING STRATEGIES
FIGURE 6. TOP WINNING STRATEGY
FIGURE 7. BARGAINING POWER OF SUPPLIERS
FIGURE 8. BARGAINING POWER OF BUYERS
FIGURE 9. THREAT OF SUBSTITUTES
FIGURE 10. THREAT OF NEW ENTRANTS
FIGURE 11. COMPETITIVE RIVALRY
FIGURE 12. KEY PLAYER POSITIONING OF GLOBAL MACHINE LEARNING AS A SERVICE MARKET, 2016 (%)
FIGURE 13. MARKET DYNAMICS
FIGURE 14. MACHINE LEARNING AS A SERVICE MARKET BY COMPONENT
FIGURE 15. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY COMPONENT, 2016-2023 ($MILLION)
FIGURE 16. MACHINE LEARNING AS A SERVICE MARKET BY ORGANIZATION SIZE
FIGURE 17. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY ORGANIZATION SIZE, 2016-2023 ($MILLION)
FIGURE 18. MACHINE LEARNING AS A SERVICE MARKET, BY END-USE INDUSTRY
FIGURE 19. GLOBAL MACHINE LEARNING AS A SERVICE MARKET REVENUE, BY END-USE INDUSTRY, 2016-2023 ($MILLION)
FIGURE 22. MACHINE LEARNING AS A SERVICE MARKET, BY REGION
FIGURE 23. NORTH AMERICA: MACHINE LEARNING AS A SERVICE MARKET
FIGURE 24. U.S. MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 25. CANADA MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 26. MEXICO MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 27. EUROPE: MACHINE LEARNING AS A SERVICE MARKET
FIGURE 28. U.K. MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 29. GERMANY MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 30. FRANCE MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 31. REST OF EUROPE MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 32. ASIA-PACIFIC: MACHINE LEARNING AS A SERVICE MARKET
FIGURE 33. CHINA MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 34. JAPAN MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 35. INDIA MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 36. REST OF ASIA-PACIFIC MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 37. LAMEA: MACHINE LEARNING AS A SERVICE MARKET
FIGURE 38. LAMEA MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 39. MIDDLE EAST MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 40. AFRICA MACHINE LEARNING AS A SERVICE MARKET, 2016-2023 ($MILLION)
FIGURE 41. FINANCIAL PERFORMANCE: GOOGLE INC.
FIGURE 42. FINANCIAL PERFORMANCE: SAS INSTITUTE INC.
FIGURE 43. FINANCIAL PERFORMANCE: FICO
FIGURE 44. FINANCIAL PERFORMANCE: HEWLETT PACKARD ENTERPRISE
FIGURE 45. FINANCIAL PERFORMANCE: YOTTAMINE ANALYTICS
FIGURE 46. FINANCIAL PERFORMANCE: AMAZON WEB SERVICES
FIGURE 47. FINANCIAL PERFORMANCE: BIGML, INC.
FIGURE 48. FINANCIAL PERFORMANCE: MICROSOFT CORPORATION
FIGURE 49. FINANCIAL PERFORMANCE: PREDICTRON LABS LTD.
FIGURE 50. FINANCIAL PERFORMANCE: IBM CORPORATION

 

The global machine learning as a service market is estimated to witness significant growth in Asia-Pacific and LAMEA, on account of high investment towards IT expenditure, increased need to improve business process performance and operational efficiency, growth of artificial intelligence (AI) & IoT market, and rise in demand for analytical solutions. The machine learning as a service market share is projected to grow at a CAGR of 39.0% from 2017 to 2023, owing to increase in demand for application-specific solutions in the developed and the developing regions.

Machine learning as a service is increasingly deployed in North America, followed by Europe, Asia-Pacific, and LAMEA. The highest market share in North America is attributed to the increase in adoption of this technology in the BFSI & other industries and increase in number of inorganic strategies followed by market leaders for business expansion. The machine learning as a service market is impacted by the need to improve the overall efficiency of the business processes. However, challenges associated with scarcity of trained professionals limit the market growth.

Key players in machine learning as a service market are involved in the introduction of new features and capabilities to enhance their existing product portfolio. This is anticipated to increase the product penetration and enable key providers to establish themselves in the emerging markets. In this regard, Yottamine Analytics introduced a new product, YottamineAI, in July 2017 which combines the functionalities of AI to deliver advanced services for financial institutions.

 

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