MLaaS（Machine Learning as a Service）の世界市場 - 産業規模、シェア、動向、機会、予測：コンポーネント別、組織規模別、用途別、エンドユーザー別、地域別、競合別（2018年～2028年）

世界のMLaaS（Machine Learning as a Service）の市場規模は、2028年にかけて2桁のCAGRで成長すると予測されています。

市場成長の要因としては、クラウドベースのソリューションの採用が進み、ビッグデータの用途が増加していることが挙げられます。さらに、熟練労働者の少なさや、データセキュリティの欠如が、予測期間を通じて世界のMLaaS（Machine Learning as a Service）市場の成長を阻害する可能性があると推定されます。

当レポートでは、世界のMLaaS（Machine Learning as a Service）市場について調査し、市場概要、VOC分析、セグメント別・地域別の見通し、促進要因や課題、COVID-19の影響、市場動向、企業プロファイルなどの情報を提供しています。

目次

第1章 サービス概要

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 世界のMLaaS（Machine Learning as a Service）市場におけるCOVID-19の影響

第5章 VOC

• MLaaS（Machine Learning as a Service）の認知度
• MLaaS（Machine Learning as a Service）の主な用途
• MLaaS（Machine Learning as a Service）の主な利点
• 主要ベンダー選択のパラメーター
• MLaaS（Machine Learning as a Service）採用時の主な選択範囲
• 主要ベンダーの課題

第6章 世界のMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別（ソリューション、サービス）
  • 組織規模別（大企業、中小企業）
  • 用途別（銀行・金融サービス・保険、ヘルスケア・医薬品、eコマース・小売、メディア・エンターテイメント、IT・通信、その他）
  • エンドユーザー別（IT・通信、自動車、ヘルスケア、航空宇宙・防衛、小売、政府、銀行・金融サービス・保険）
  • 地域別
  • 重要ポイント
  • 企業別
• 市場マップ（コンポーネント別、組織規模別、用途別、エンドユーザー別、地域別）

第7章 北米のMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別
  • 組織規模別
  • 用途別
  • エンドユーザー別
  • 国別
  • 重要ポイント
• 北米：国別分析
  • 米国
  • カナダ
  • メキシコ

第8章 欧州のMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別
  • 組織規模別
  • 用途別
  • エンドユーザー別
  • 国別
  • 重要ポイント
• 欧州：国別分析
  • ドイツ
  • 英国
  • フランス
  • イタリア
  • スペイン

第9章 アジア太平洋地域のMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別
  • 組織規模別
  • 用途別
  • エンドユーザー別
  • 国別
  • 重要ポイント
• アジア太平洋地域：国別分析
  • 中国
  • 日本
  • インド
  • 韓国
  • オーストラリア

第10章 中東・アフリカのMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別
  • 組織規模別
  • 用途別
  • エンドユーザー別
  • 国別
  • 重要ポイント
• 中東・アフリカ：国別分析
  • サウジアラビア
  • アラブ首長国連邦
  • 南アフリカ

第11章 南米のMLaaS（Machine Learning as a Service）市場の見通し

• 市場規模と予測
  • 金額別
• 市場シェアと予測
  • コンポーネント別
  • 組織規模別
  • 用途別
  • エンドユーザー別
  • 国別
  • 重要ポイント
• 南米：国別分析
  • ブラジル
  • アルゼンチン
  • コロンビア

第12章 市場力学

• 促進要因
• 課題

第13章 市場動向と発展

• 顧客対応活動の増加
• スマートバックオフィスとオペレーション
• 小売分野での機械学習の使用増加
• 合併と買収
• ビッグデータの急激な成長

第14章 企業プロファイル

• Google Inc
• SAS Institute Inc
• Fair Isaac Corporation
• Hewlett Packard Enterprise Development LP
• Yottamine Analytics Inc.
• Amazon Web Services
• BigML, Inc.
• Microsoft Corporation
• IBM Corporation
• Broadcom Corporation

第15章 戦略的提言

第16章 免責事項

Global machine learning as a service market is anticipated to grow at double digit CAGR through 2028 on account of rising adoption of cloud-based solutions and increasing application of big data. Additionally, it is estimated that the limited availability of skilled labour and a lack of data security can hamper the growth of the machine learning as a service (MLaaS) market globally throughout the forecasted period. The term "Machine Learning as a Service" (MLaaS) refers to a group of services which includes several cloud-based platforms using machine learning techniques to offer dedicated solutions. Furthermore, MLaaS reduces infrastructure-related issues such as data pre-processing, model training, model evaluation, and, ultimately, predictions.

Rising adoption of cloud-based services

, Several industry verticals utilize major cloud-based solutions to manage business operations. With cloud-based technologies being majorly used in various organizations and enterprises; data interchange is facilitated by the simplicity with which these connections are established. This makes it possible to access the information within the organization, increasing the latter's cost-effectiveness. For instance, Infosys Ltd launched industry cloud platform for organizations in 2022 to increase innovation and business value in the cloud across the financial services industry.

Lack of skilled resources

Developers can now design efficient cloud-based business operation solutions with the expanding adoption of cloud technologies and desirable delivery techniques across numerous industry verticals. To speed up the ML integration process, SMEs in the MLaaS industry prefer cloud-based services. Eliminating tedious work improves an organization's efficiency without adding more people. Though, lack of trained consultants, compliance problems, and regulatory limitations are some obstacles preventing this market's expansion. Therefore, in order to improve uniformity in the market environment, market participants should collaborate with governmental and regulatory agencies to improve the uniformity in the market environment.

Growing IoT in business operations

The information technology industry is expanding due to the increasing popularity of social media platforms and cloud computing technologies. Today, cloud computing services are extensively used by various companies that offer enterprise storage solutions. The ability to analyze real time data online using cloud storage is a benefit. Thanks to cloud computing, data analysis is now possible at any time and location. Businesses may also digitally access critical data from linked data warehouses and save money on infrastructure and storage costs by utilizing cloud and ML, which includes trends in customer behaviour and purchasing. The growth of cloud computing has led to the development of MLaaS industry. AI systems employ ML to speed up learning, self-correction, and reasoning. AI applications include expert systems, speech recognition, and machine vision, to name a few. Hence, AI is becoming increasingly popular as a result of modern initiatives like big data infrastructure and cloud computing.

Market Segments

Global Machine Learning as a Service Market is segmented into by component, by organization size, by application, by end-user and by region. Based on component, the market is segmented into Solution and Service. Based on Organization Size, the market is segmented into Small and Medium-Sized Enterprises and Large Enterprises. Based on Application, the market is segmented into Marketing & Advertising, Fraud Detection & Risk Management, Computer vision, Security & Surveillance, Predictive analytics, Natural Language Processing, Augmented & Virtual Reality, Others. Based on End User, the market is further segmented into IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI.

Market Players

Major market players in the Global Machine Learning as a Service Market are Google Inc, SAS Institute Inc, Fair Isaac Corporation, Hewlett Packard Enterprise Development LP, Yottamine Analytics Inc., Amazon Web Services, BigML, Inc., Microsoft Corporation, IBM Corporation, Broadcom Corporation

Recent Developments

• Inflection AI received one of the largest fundraising rounds for artificial machine learning in June 2022, amounting to USD 225 million. It is said to be a startup for AI and machine learning. Venture capitalists have provided it with equity financing worth USD 225 million.
• Vertex AI, a new managed machine learning platform that enables users to maintain and deploy AI models based on client needs, was announced by Google Cloud in May 2021.

Report Scope:

In this report, Global Machine Learning as a Service Market has been segmented into following categories, in addition to the industry trends which have also been detailed below:

• Machine Learning as a Service Market, By Component:

Solution

Service

• Machine Learning as a Service Market, By Organization Size:

Small and Medium-Sized Enterprises

Large Enterprises

• Machine Learning as a Service Market, By Application:

Marketing & Advertising

Fraud Detection & Risk Management

Computer vision

Security & Surveillance

Predictive analytics

Natural Language Processing

Augmented & Virtual Reality

Others

• Machine Learning as a Service Market, By End User:

IT and Telecom

Automotive

Healthcare

Aerospace and Defense

Retail

Government

BFSI

• Machine Learning as a Service Market, By Region:

North America

• United States
• Canada
• Mexico

Asia-Pacific

• China
• Japan
• India
• South Korea
• Australia
• Rest of Asia-Pacific

Europe

• Germany
• UK
• France
• Italy
• Spain
• Rest of Europe

MEA

• Saudi Arabia
• UAE
• South Africa
• Rest of MEA

South America

• Brazil
• Argentina
• Colombia
• Rest of South America

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in Global Machine Learning as a Service Market.

Available Customizations:

Global Machine Learning as a Service Market with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Service Overview

• 1.1. Market Definition
• 1.2. Scope of the Study

2. Research Methodology

• 2.1. Baseline Methodology
• 2.2. Methodology Followed for Calculation of Market Size
• 2.3. Methodology Followed for Calculation of Market Shares
• 2.4. Methodology Followed for Forecasting

3. Executive Summary

4. Impact of COVID-19 on Global Machine Learning as a Service Market

5. Voice of Customer

• 5.1. Awareness of Machine Learning as a Service
• 5.2. Major Applications of Machine Learning as a Service
• 5.3. Key benefits of Machine Learning as a Service
• 5.4. Key vendor selection parameter
• 5.5. Major selection in adopting Machine Learning as a Service
• 5.6. Key vendor challenges

6. Global Machine Learning as a Service Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component (Solution, Service)
  • 6.2.2. By Organization Size (Large Enterprises, Small and Medium-Sized Enterprises)
  • 6.2.3. By Application (BFSI, Healthcare & Pharmaceuticals, E-commerce & Retail, Media & Entertainment, IT & Telecom, and Others)
  • 6.2.4. By End-User (IT and Telecom, Automotive, Healthcare, Aerospace and Defense, Retail, Government, BFSI)
  • 6.2.5. By Region
  • 6.2.6. Key Takeaways
  • 6.2.7. By Company (2022)
• 6.3. Market Map (By Component, By Organization Size, By Application, By End-User, By Region)

7. North America Machine Learning as a Service Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Organization Size
  • 7.2.3. By Application
  • 7.2.4. By End-User
  • 7.2.5. By Country
  • 7.2.6. Key Takeaways
• 7.3. North America: Country Analysis
  • 7.3.1. United States Machine Learning as a Service Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Organization Size
      • 7.3.1.2.3. By Application
      • 7.3.1.2.4. By End-User
  • 7.3.2. Canada Machine Learning as a Service Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Organization Size
      • 7.3.2.2.3. By Application
      • 7.3.2.2.4. By End-User
  • 7.3.3. Mexico Machine Learning as a Service Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Organization Size
      • 7.3.3.2.3. By Application
      • 7.3.3.2.4. By End-User

8. Europe Machine Learning as a Service Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Component
  • 8.2.2. By Organization Size
  • 8.2.3. By Application
  • 8.2.4. By End-User
  • 8.2.5. By Country
  • 8.2.6. Key Takeaways
• 8.3. Europe: Country Analysis
  • 8.3.1. Germany Machine Learning as a Service Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Component
      • 8.3.1.2.2. By Organization Size
      • 8.3.1.2.3. By Application
      • 8.3.1.2.4. By End-User
  • 8.3.2. United Kingdom Machine Learning as a Service Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Component
      • 8.3.2.2.2. By Organization Size
      • 8.3.2.2.3. By Application
      • 8.3.2.2.4. By End-User
  • 8.3.3. France Machine Learning as a Service Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Component
      • 8.3.3.2.2. By Organization Size
      • 8.3.3.2.3. By Application
      • 8.3.3.2.4. By End-User
  • 8.3.4. Italy Machine Learning as a Service Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Organization Size
      • 8.3.4.2.3. By Application
      • 8.3.4.2.4. By End-User
  • 8.3.5. Spain Machine Learning as a Service Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Organization Size
      • 8.3.5.2.3. By Application
      • 8.3.5.2.4. By End-User

9. Asia Pacific Machine Learning as a Service Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Component
  • 9.2.2. By Organization Size
  • 9.2.3. By Application
  • 9.2.4. By End-User
  • 9.2.5. By Country
  • 9.2.6. Key Takeaways
• 9.3. Asia Pacific: Country Analysis
  • 9.3.1. China Machine Learning as a Service Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Component
      • 9.3.1.2.2. By Organization Size
      • 9.3.1.2.3. By Application
      • 9.3.1.2.4. By End-User
  • 9.3.2. Japan Machine Learning as a Service Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Component
      • 9.3.2.2.2. By Organization Size
      • 9.3.2.2.3. By Application
      • 9.3.2.2.4. By End-User
  • 9.3.3. India Machine Learning as a Service Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Component
      • 9.3.3.2.2. By Organization Size
      • 9.3.3.2.3. By Application
      • 9.3.3.2.4. By End-User
  • 9.3.4. South Korea Machine Learning as a Service Market Outlook
    • 9.3.4.1. Market Size & Forecast
      • 9.3.4.1.1. By Value
    • 9.3.4.2. Market Share & Forecast
      • 9.3.4.2.1. By Component
      • 9.3.4.2.2. By Organization Size
      • 9.3.4.2.3. By Application
      • 9.3.4.2.4. By End-User
  • 9.3.5. Australia Machine Learning as a Service Market Outlook
    • 9.3.5.1. Market Size & Forecast
      • 9.3.5.1.1. By Value
    • 9.3.5.2. Market Share & Forecast
      • 9.3.5.2.1. By Component
      • 9.3.5.2.2. By Organization Size
      • 9.3.5.2.3. By Application
      • 9.3.5.2.4. By End-User

10. Middle East & Africa Machine Learning as a Service Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Organization Size
  • 10.2.3. By Application
  • 10.2.4. By End-User
  • 10.2.5. By Country
  • 10.2.6. Key Takeaways
• 10.3. Middle East & Africa: Country Analysis
  • 10.3.1. Saudi Arabia Machine Learning as a Service Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Organization Size
      • 10.3.1.2.3. By Application
      • 10.3.1.2.4. By End-User
  • 10.3.2. UAE Machine Learning as a Service Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Organization Size
      • 10.3.2.2.3. By Application
      • 10.3.2.2.4. By End-User
  • 10.3.3. South Africa Machine Learning as a Service Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Organization Size
      • 10.3.3.2.3. By Application
      • 10.3.3.2.4. By End-User

11. South America Machine Learning as a Service Market Outlook

• 11.1. Market Size & Forecast
  • 11.1.1. By Value
• 11.2. Market Share & Forecast
  • 11.2.1. By Component
  • 11.2.2. By Organization Size
  • 11.2.3. By Application
  • 11.2.4. By End-User
  • 11.2.5. By Country
  • 11.2.6. Key Takeaways
• 11.3. South America: Country Analysis
  • 11.3.1. Brazil Machine Learning as a Service Market Outlook
    • 11.3.1.1. Market Size & Forecast
      • 11.3.1.1.1. By Value
    • 11.3.1.2. Market Share & Forecast
      • 11.3.1.2.1. By Component
      • 11.3.1.2.2. By Organization Size
      • 11.3.1.2.3. By Application
      • 11.3.1.2.4. By End-User
  • 11.3.2. Argentina Machine Learning as a Service Market Outlook
    • 11.3.2.1. Market Size & Forecast
      • 11.3.2.1.1. By Value
    • 11.3.2.2. Market Share & Forecast
      • 11.3.2.2.1. By Component
      • 11.3.2.2.2. By Organization Size
      • 11.3.2.2.3. By Application
      • 11.3.2.2.4. By End-User
  • 11.3.3. Colombia Machine Learning as a Service Market Outlook
    • 11.3.3.1. Market Size & Forecast
      • 11.3.3.1.1. By Value
    • 11.3.3.2. Market Share & Forecast
      • 11.3.3.2.1. By Component
      • 11.3.3.2.2. By Organization Size
      • 11.3.3.2.3. By Application
      • 11.3.3.2.4. By End-User

12. Market Dynamics

• 12.1. Drivers
  • 12.1.1. Increase demand for cloud computing
  • 12.1.2. Growth associate with cognitive computing & AI
  • 12.1.3. Rise in adoption of analytics solutions
• 12.2. Challenges
  • 12.2.1. Lack of skilled resources
  • 12.2.2. Lacking infrastructure

13. Market Trends and Developments

• 13.1. Increasing customer facing activities
• 13.2. Smarter back office & operations
• 13.3. Growing use of machine learning in retail sector
• 13.4. Mergers & Acquisitions
• 13.5. Exponential growth of big data

14. Company Profiles

• 14.1. Google Inc
  • 14.1.1. Company Overview
  • 14.1.2. Product Portfolio
  • 14.1.3. SWOT Analysis
  • 14.1.4. Key Personals
  • 14.1.5. Recent Developments/Updates
• 14.2. SAS Institute Inc
  • 14.2.1. Company Overview
  • 14.2.2. Product Portfolio
  • 14.2.3. SWOT Analysis
  • 14.2.4. Key Personals
  • 14.2.5. Recent Developments/Updates
• 14.3. Fair Isaac Corporation
  • 14.3.1. Company Overview
  • 14.3.2. Product Portfolio
  • 14.3.3. SWOT Analysis
  • 14.3.4. Key Personals
  • 14.3.5. Recent Developments/Updates
• 14.4. Hewlett Packard Enterprise Development LP
  • 14.4.1. Company Overview
  • 14.4.2. Product Portfolio
  • 14.4.3. SWOT Analysis
  • 14.4.4. Key Personals
  • 14.4.5. Recent Developments/Updates
• 14.5. Yottamine Analytics Inc.
  • 14.5.1. Company Overview
  • 14.5.2. Product Portfolio
  • 14.5.3. SWOT Analysis
  • 14.5.4. Key Personals
  • 14.5.5. Recent Developments/Updates
• 14.6. Amazon Web Services
  • 14.6.1. Company Overview
  • 14.6.2. Product Portfolio
  • 14.6.3. SWOT Analysis
  • 14.6.4. Key Personals
  • 14.6.5. Recent Developments/Updates
• 14.7. BigML, Inc.
  • 14.7.1. Company Overview
  • 14.7.2. Product Portfolio
  • 14.7.3. SWOT Analysis
  • 14.7.4. Key Personals
  • 14.7.5. Recent Developments/Updates
• 14.8. Microsoft Corporation
  • 14.8.1. Company Overview
  • 14.8.2. Product Portfolio
  • 14.8.3. SWOT Analysis
  • 14.8.4. Key Personals
  • 14.8.5. Recent Developments/Updates
• 14.9. IBM Corporation
  • 14.9.1. Company Overview
  • 14.9.2. Product Portfolio
  • 14.9.3. SWOT Analysis
  • 14.9.4. Key Personals
  • 14.9.5. Recent Developments/Updates
• 14.10. Broadcom Corporation
  • 14.10.1. Company Overview
  • 14.10.2. Product Portfolio
  • 14.10.3. SWOT Analysis
  • 14.10.4. Key Personals
  • 14.10.5. Recent Developments/Updates

15. Strategic Recommendations

• 15.1. Use sophisticated algorithms for data utilizing
• 15.2. Use customer churn modelling

16. About Us & Disclaimer