MLaaS（Machine Learning as a Service）の世界市場 - 市場規模・セグメント・展望・収益予測（2022年～2028年）：コンポーネント別、用途別、企業別、エンドユーザー別、地域別

世界のMLaaS（Machine Learning as a Service）の市場規模は、2017年の50億米ドルから、2022年には100億米ドルに成長し、2028年までに300億米ドルに達し、予測期間中にCAGRで約20％の成長が予測されています。市場は、クラウドコンピューティングの需要の高まり、分析ソリューションの採用の増加、人工知能とコグニティブコンピューティング市場の成長、アプリケーション分野の拡大、および訓練を受けた専門家不足などの理由により、成長が期待されています。

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、市場スナップショット、セグメント別分析、主要企業のプロファイル、競合情勢などの情報を提供しています。

目次

範囲

第1章 エグゼクティブサマリー

• MLaaS（Machine Learning as a Service）市場の成長実績と予測のハイライト
• 市場動向、課題、競合企業のハイライト
• 市場収益シェアのハイライト：セグメント別

第2章 市場概要と成長に影響を与える主要動向

• MLaaS（Machine Learning as a Service）市場の分類法
• 業界のバリューチェーン
• MLaaS（Machine Learning as a Service）市場における主要企業のエコシステム
• 政府の規制と開発
• 市場に影響を与える主要な促進要因と課題
• MLaaS（Machine Learning as a Service）市場へのCOVID-19の影響
• 世界のMLaaS（Machine Learning as a Service）市場の成長実績：セグメントタイプ別（2017年～2021年）
  • コンポーネント別
  • 用途別
  • 企業別
  • エンドユーザー別
  • 主要国別
• 世界のMLaaS（Machine Learning as a Service）市場の成長実績と予測（2017年～2028年）
• 重要ポイント

第3章 世界市場セグメンテーションの成長実績、展望、予測：コンポーネント別

• 市場定義 - セグメンテーション：コンポーネント別
• 市場収益シェア、成長実績、展望、予測：コンポーネント別（2017年～2028年）
  • サービス
  • ソフトウェアツール
• 市場セグメンテーションの重要ポイント：コンポーネント別

第4章 世界市場セグメンテーションの成長実績、展望、予測：用途別

• 市場定義 - セグメンテーション：用途別
• 市場収益シェア、成長実績、展望、予測：用途別（2017年～2028年）
  • マーケティング・広告
  • 予測分析
  • 自動ネットワーク管理
  • 不正検知・リスク分析
  • ネットワーク分析・自動トラフィック管理
  • その他
• 市場セグメンテーションの重要ポイント：用途別

第5章 世界市場セグメンテーションの成長実績、展望、予測：企業別

• 市場定義 - セグメンテーション：企業別
• 市場収益シェア、成長実績、展望、予測：企業別（2017年～2028年）
  • 中小企業
  • 大企業
• 市場セグメンテーションの重要ポイント：企業別

第6章 世界市場セグメンテーションの成長実績、展望、予測：エンドユーザー別

• 市場定義 - セグメンテーション：エンドユーザー別
• 市場収益シェア、成長実績、展望、予測：エンドユーザー別（2017年～2028年）
  • 銀行、金融、サービス、保険
  • IT・通信
  • 自動車
  • ヘルスケア
  • 航空宇宙・防衛
  • 小売
  • 政府
  • その他
• 市場セグメンテーションの重要ポイント：エンドユーザー別

第7章 業界 / 競合分析 - 競合情勢

• 企業（競合企業）タイプと競合シェア
• 世界のMLaaS（Machine Learning as a Service）市場競合企業のポーターのファイブフォース分析
• 市場成長に影響を与えるMLaaS（Machine Learning as a Service）分野の主な発展
• 世界のMLaaS（Machine Learning as a Service）市場における主要な競合の比較（2021年）
• コンポーネント別
• 用途別
• 企業別
• エンドユーザー別
• 地域別
• 競合情勢の重要ポイント

第8章 主要な競合企業のプロファイル（企業概要、製品タイプ、開発）

• Amazon
• Google LLC
• IBM Corporation
• Microsoft Corporation
• Oracle Corporation
• HPE
• SAS Institute Inc.
• FICO
• Yottamine Analystics, LLC
• Predictron Labs Ltd.
• BigML
• ErsatzLabs, Inc.

第9章 地域分析と主要国市場の成長実績、展望、予測

• 主要国のマクロ経済要因比較
• 世界の市場収益シェア、成長実績、展望、予測：地域別（2017年～2028年）
• 主要地域の市場分析、成長実績、展望、予測
• 北米 - MLaaS（Machine Learning as a Service）市場分析
  • 北米の主要な生産拠点・消費拠点
  • 北米の注目すべきMLaaS（Machine Learning as a Service）新興企業
  • 市場収益シェア、成長実績、展望、予測：コンポーネント別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：用途別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：企業別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：エンドユーザー別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：地域別（2017年～2028年）
  • 米国
  • カナダ
  • メキシコ
• 欧州 - MLaaS（Machine Learning as a Service）市場分析
  • 欧州の主要な生産拠点・消費拠点
  • 欧州の注目すべきMLaaS（Machine Learning as a Service）新興企業
  • 市場収益シェア、成長実績、展望、予測：コンポーネント別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：用途別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：企業別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：エンドユーザー別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：地域別（2017年～2028年）
  • 英国
  • ドイツ
  • フランス
  • イタリア
  • スペイン
  • その他
• アジア太平洋 - MLaaS（Machine Learning as a Service）市場分析
  • アジア太平洋の主要な生産拠点・消費拠点
  • アジア太平洋の注目すべきMLaaS（Machine Learning as a Service）新興企業
  • 市場収益シェア、成長実績、展望、予測：コンポーネント別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：用途別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：企業別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：エンドユーザー別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：地域別（2017年～2028年）
  • 中国
  • インド
  • 日本
  • 韓国
  • インドネシア
  • オーストラリア
  • その他
• ラテンアメリカ、中東、アフリカ - MLaaS（Machine Learning as a Service）市場分析
  • ラテンアメリカ、中東、アフリカの主要な生産拠点・消費拠点
  • ラテンアメリカ、中東、アフリカの注目すべきMLaaS（Machine Learning as a Service）新興企業
  • 市場収益シェア、成長実績、展望、予測：コンポーネント別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：用途別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：企業別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：エンドユーザー別（2017年～2028年）
  • 市場収益シェア、成長実績、展望、予測：主要地域別（2017年～2028年）
  • ラテンアメリカ
  • 中東
  • アフリカ

第10章 業界専門家の意見 / 展望

• 市場の現状と将来展望に関する業界専門家と経営幹部の注目すべき声明/引用文

第11章 アナリストの提言

• 主要な機会と、機会から得られる可能性のある戦略の特定に関するアナリストの提言

第12章 付録

Market Overview

Machine Learning as a Service (MLaaS) is a group of services that provide machine learning (ML) tools as a component of cloud computing solutions. MLaaS enables customers/clients to benefit from ML without the associated expense, risk, or time required to build an internal ML team.

MLaaS is used in processes such as risk analytics, fraud detection, manufacturing, and supply chain optimization among others. It offers the freedom to build in-house infrastructure from scratch and provides management and storage of data. It has a synergistic value in engaging data with the cloud and can revolutionize a paradigm of ML for a specific result. According to Ken Research analysis, the Machine Learning as a Service (MLaaS) Market was valued at US$ 5 bn in 2017. It is estimated to capture a market size of US$ 10 bn by 2022 and is projected to reach US$ 30 Bn by 2028. It is expected to record a CAGR of ~20% during the forecast period, due to an increase in demand for cloud computing, as well as growth connected with artificial intelligence (AI) and cognitive computing.

ML is driven by the demand for cloud-based solutions, artificial intelligence, and the cognitive computing market. Machine learning's primary pattern in IoT data is analyzing massive volumes of data using strong algorithms.

The Machine Learning as a Service (MLaaS) Market is expected to grow as demand for a cloud-based solution increases, including growing demand for cloud computing, rise in adoption of analytical solutions, growth of artificial intelligence & cognitive computing market, increased application areas, and lack of trained professionals.

According to research conducted by Microsoft Corporation in 2020, 85% of businesses have at least one IoT use case project. Nearly 94% of the respondents started pursuing IoT initiatives in 2021 leading to the creation of additional growth opportunities for Machine Learning as a Service (MLaaS) vendors in the market.

The low availability of technically skilled personnel is expected to hamper the Global Machine Learning as a Service (MLaaS) Market growth during the forecast period along with the lack of data security faced by the organizations.

Several organizations are unwilling to adopt ML technologies due to concerns regarding data security. For many regulated industry sectors such as banking, insurance, healthcare, and government, data security is crucial and any failure in data security may result in major problems.

OneSpan, in a Global Financial Regulations report observed nearly half of surveyed banks focus on reducing and preventing cyberattacks and frauds, along with protecting sensitive data, as their top challenges. The overall fintech investments have reached US$ 98 billion in the first half of 2021, compared to US$ 121.5 billion in 2020

COVID-19 caused an acceleration in the migration of public cloud solutions and some of the applications of AI to help in tracing patients during the pandemic. Since cloud service elasticity could meet the unexpected rise in demand, the need for AI services had seen growth, and many cloud providers offered Machine Learning as a Service (MLaaS). Several countries used population surveillance methods to track and trace COVID-19 cases.

In South Korea, researchers used surveillance camera footage and geo-location data to track coronavirus patients. Using this data, scientists leveraged ML algorithms to predict the location of the next outbreak and inform the responsible authorities, helping to track diseases in real-time.

Scope of the Report

Machine Learning as a Service (MLaaS) Market is segmented by components, applications, enterprises, and end-user. In addition, the report also covers market size and forecasts for the region's four major regions' North America, Asia Pacific, Europe, and LAMEA Machine Learning as a Service (MLaaS) market. The revenue used to size and forecast the market for each segment is US$ billion.

By Components

Software Tools

Services

By Application

Marketing & Advertising

Predictive Analytics

Automated Network Management

Fraud detection and risk Analytics

Network Analytics and Automated Traffic Management

Others

By Enterprises

SMEs

Large enterprises

By End-User

Banking, Financial, Services, and Insurance

IT and Telecom

Automotive

Healthcare

Aerospace and Defense

Retail

Government

Others

By Geography

North America

USA

Canada

Mexico

Europe

Germany

UK

France

Italy

Spain

Asia Pacific

China

Japan

India

AustraliaSouth Korea

LAMEA

Latin America

Middle East

Africa

Key Players

Amazon.com Inc

Google LLC

IBM Corporation

Microsoft Corporation

Oracle Corporation

HPE

SAS Institute, Inc.

FICO

Yottamine Analytics, LLC

PREDICTRON LABS

BigML

Ersatz Labs, Inc

Key Trends by Market Segment

By Component: The service segment dominated the Machine Learning as a Service (MLaaS) Market in 2021 and is expected to maintain its dominance during the forecast period.

The market for ML services is expected to grow due to increasing cloud applications and the growth of end-use industries in developing economies. To enhance the usage of ML services, industry participants focus on implementing technologically advanced solutions, for instance, the use of ML services in the healthcare sector for cancer detection, as well as checking ECG and MRI. ML services features, such as cost reduction, demand forecasting, real-time data analysis, and increased cloud use, are projected to open considerable prospects for the market.

In December 2021, BigML added Image Processing to the BigML platform, a feature that enhances their components to solve image-driven business problems with ease of use. It labels the image data, trains and evaluates models, makes predictions, and automates end-to-end machine learning workflows.

By Application: Network analytics and automated traffic management segment accounted for the majority share of the Global Machine Learning as a Service (MLaaS) Market in 2021 and is expected to showcase the highest growth rate during the forecast period (2022-2028).

Large amounts of data traverse network infrastructure on an everyday basis. The growth of this segment is attributed to ML's capabilities and characteristics to tackle the exponential growth of datasets and act as a pivotal tool for network analytics and automated traffic management across various verticals.

In 2021, Amazon released SageMaker Studio, the first ML IDE. This application provides a web-based interface through which clients can run all ML model training tests in a single environment. SageMaker Studio provides access to all development methods and tools, including notebooks, debugging tools, data modeling, and automatic creation.

By Enterprises: SME segment is estimated to capture the largest market share of the Global Machine Learning as a Service (MLaaS) Market in 2021 and is expected to showcase the highest growth rate during the forecast period (2022-2028).

ML lets SMEs optimize their processes on a low budget in comparison with starting things from scratch. For SMEs the 'pay for what you use or 'pay as you grow system offered by most MLaaS providers makes it both budget-friendly and time-effective to integrate ML into their businesses while not requiring a team with specific technical capabilities. With the help of predictive analytics, machine learning algorithms not only provide real-time data but also predict future instances.

SMEs use ML solutions for fine-tuning their supply chain by predicting a product demand and providing suggestions on the timing and quantity of supplies required to meet customers' expectations.

By End Users: The healthcare segment holds the largest market share in Global Machine Learning as a Service (MLaaS) Market in 2021.

Growing adoption of ML solutions by various retail and healthcare service providers is expected to boost the Machine Learning as a Service market during the forecast period. Major market prospects are anticipated to be unlocked by the advantages provided by ML services, such as demand forecasting, cost reduction, real-time data analysis, and a rise in the use of the cloud market.

In April 2021, Microsoft Corporation released an open dataset for health & genomics, transportation, labor & economics, supplementary, population & safety, and common datasets. This dataset aims to increase the accuracy of ML models using publicly accessible datasets. This also enables businesses to use Azure Open Datasets with its ML and data analytics solutions to offer insights at hyper-scale.

By Geography: North Americaaccounted for the largest share among all regions within the total Machine Learning as a Service (MLaaS) Market, accounting for total market revenue.

North America has been the most forward towards adopting ML services. The demand for MLaaS in the region can be attributed to the robust innovation ecosystem, strategic federal investments into advanced technology, and the presence of visionary entrepreneurs from globally renowned research institutions. Furthermore, this region has been extremely responsive to adopting the latest technological advancements such as integration technologies with the cloud, Big Data within ML Services.

In November 2021, SAS added support for open-source users to its flagship SAS Viya platform. SAS Viya is for open-source integration and utility. The software user established an API-first strategy that fueled a data preparation process with ML.

Competitive Landscape

The Global Machine Learning as a Service (MLaaS) Market is highly competitive with ~150 players which include globally diversified players, regional players as well as a large number of country-niche players each with their niche in a cloud-based solution, and technologies. The Machine Learning as a Service (MLaaS) Market's growth is heavily reliant on IoT-based applications. Nowadays, numerous cloud-based companies, including Amazon, Google, HPE, Oracle, and IBM are investing in Machine Learning as a Service (MLaaS), and governments are also making significant investments in Machine Learning.

Country-Niche players comprise about ~45% of the market in terms of the number of competitors, while regional players hold a share of ~35%. Some of the major players in the market include Amazon, Google LLC, HPE, Oracle Corporation, IBM Corporation, Microsoft Corporation, SAS Institution Inc. FICO, Yottamine Analytics, LLC, PREDICTRON LABS, BigML, Ersatz Labs, Inc, and among others.

Recent Developments Related to Major Players

In June 2021, Hewlett Packard completed the acquisition of Determined AI, a San Francisco-based startup offering a software stack to train AI models faster at any scale, utilizing its open-source ML platform. Hewlett Packard integrated Determined AI's unique software solution with its AI and high-performance computing (HPC) products to empower ML engineers to conveniently deploy and train ML models to offer faster and more precise analysis from their data in every industry.

In December 2021, Cognizant, a key player in the MLaaS market acquired Inwisdom, an AI and ML service provider to improve the decision-making ability of businesses using analytics and ML platforms.

In June 2022, Inflection AI secured one of the largest artificial ML funding rounds, totaling US$ 225 million. This ML investment is expected to improve ML, allowing for intuitive human-computer interfaces in the near future.

Conclusion

The Global Machine Learning as a Service (MLaaS) Market is forecasted to continue exponential growth during the forecast period, primarily driven by an increase in the adoption of IoT-based applications to ensure the accuracy of operational management using IoT platforms. Though the market is highly competitive with over 150 participants, few global players control the dominant share, and regional players also hold a significant share.

Note: This is an upcoming/planned report, so the figures quoted here for a market size estimate, forecast, growth, segment share, and competitive landscape are based on initial findings and might vary slightly in the actual report. Also, any required customizations can be covered to the best feasible extent for pre-booking clients, and the report delivered within a maximum of two working weeks.

Key Topics Covered in the Report

Snapshot of the Global Machine Learning as a Service (MLaaS) Market

Industry Value Chain and Ecosystem Analysis

Market size and Segmentation of the Global Machine Learning as a Service (MLaaS) Market

Historic Growth of the Overall Global Machine Learning as a Service (MLaaS) Market and Segments

Competition Scenario of the Market and Key Developments of Competitors

Porter's 5 Forces Analysis of Global Machine Learning as a Service (MLaaS) Industry

Overview, Product Offerings, and SWOT Analysis of Key Competitors

COVID-19 Impact on the Overall Global Machine Learning as a Service (MLaaS) Market

Future Market Forecast and Growth Rates of the Total Global Machine Learning as a Service (MLaaS) Market and by Segments

Market Size of Application/End User Segments with Historical CAGR and Future Forecasts

Analysis of the Machine Learning as a Service (MLaaS) Market

Major Production / Consumption Hubs in the Major within Each Region

Major Production/Supply and Consumption/Demand Hubs within Each Major Country

Major Country-wise Historic and Future Market Growth Rates of the Total Market and Segments

Overview of Notable Emerging Competitor Companies within Each Region

Notable Emerging Companies Mentioned in the Report

AI.Reverie

Anodot

Arturo

Comet.ml

Eightfold AI's

Key Target Audience - Organizations and Entities Who Can Benefit by Subscribing This Report

Machine Learning as a Service (MLaaS) Solution Companies

Potential Investors in Machine Learning as a Service (MLaaS) Companies

IoT Solutions Providers

Government Investors

AI Solution Providers

Networking Companies

Cloud Developers

Research & Development Institutes

Venture Capitalists

Healthcare IoT Companies

Telecommunication Service Providers

Software Developers

Electronic/Smart Device Manufacturers

Finance and Banking Institutes

Marketing Companies

Time Period Captured in the Report

Historical Period: 2017-2021

Forecast Period: 2022E-2028F

Frequently Asked Questions

What is the Study Period of this Market Report?

The Global Machine Learning as a Service (MLaaS) Market is covered from 2017-2028 in this report, which includes a forecast for the period 2022-2028.

What is the Future Growth Rate of the Global Machine Learning as a Service (MLaaS) Market?

The Global Machine Learning as a Service (MLaaS) Market is expected to witness a CAGR of about 20% over the next six years.

What are the Key Factors Driving the Global Machine Learning as a Service (MLaaS) Market?

An increase in the adoption of IoT-based applications generates huge demand to ensure the accuracy of operational management using IoT platforms, which is expected to be the primary driver of this market.

Which is the Largest Type Segment within the Global Machine Learning as a Service (MLaaS) Market?

SMEs hold the largest share of the Global Machine Learning as a Service (MLaaS) Market.

Who are the Key Players in Global Machine Learning as a Service (MLaaS) Market?

Amazon, Google LLC, IBM Corporation, Microsoft Corporation, Oracle Corporation, HPE, SAS Institution, FICO, Yottamine Analytics, LLC, PREDICTION LABS LTD, BigML, and ersatz Labs, Inc among others are the major companies operating in Global Machine Learning as a Service (MLaaS) Market.

Table Of Contents

Scope:

1. Executive Summary

• 1.1 Highlights of Global Machine Learning as a Service (MLaaS) Market Historic Growth & Forecast
• 1.2 Highlights of Market Trends, Challenges, and Competition
• 1.3 Highlights of Market Revenue Share by Segments

2. Market Overview and Key Trends Impacting Growth

• 2.1 Global Machine Learning as a Service (MLaaS) Market Taxonomy
• 2.2 Industry Value Chain
• 2.3 The Ecosystem of Major Entities in the Global Machine Learning as a Service (MLaaS) Market
• 2.4 Government Regulations & Developments
• 2.5 Key Growth Drivers & Challenges Impacting the Market
• 2.6 COVID-19 Impact on Global Machine Learning as a Service (MLaaS) Market
• 2.7 Total Global Machine Learning as a Service (MLaaS) Market Historic Growth by Segment Type, 2017-2021

2.7.1 By Components

2.7.2 By Application

2.7.3 By Enterprises

2.7.4 By End-User

2.7.5 By Major Countries

• 2.8 Total Global Machine Learning as a Service (MLaaS) Market Historic Growth and Forecast, 2017-2028
• 2.9 Key Takeaways

3. Global - Market Segmentation by Component, Historic Growth, Outlook & Forecasts

• 3.1 Market Definition - Segmentation by Component
• 3.2 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Components, 2017-2028

3.2.1 Service

3.2.2 Software Tools

• 3.3 Key Takeaways from Market Segmentation by Component

4. Global- Market Segmentation by Application, Historic Growth, Outlook & Forecasts

• 4.1 Market Definition - Segmentation by Application
• 4.2 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Application, 2017-2028

4.2.1 Marketing & Advertising

4.2.2 Predictive Analytics

4.2.3 Automated Network Management

4.2.4 Fraud detection and risk Analytics

4.2.5 Network Analytics and Automated Traffic Management

4.2.6 Others

• 4.3 Key Takeaways from Market Segmentation by Application

5. Global- Market Segmentation by Enterprises, Historic Growth, Outlook & Forecasts

• 5.1 Market Definition - Segmentation by Enterprises
• 5.2 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Enterprises, 2017-2028

5.2.1 Small and Medium Enterprises

5.2.2 Large Enterprises

• 5.3 Key Takeaways from Market Segmentation by Enterprises

6. Global- Market Segmentation by End-User, Historic Growth, Outlook & Forecasts

• 6.1 Market Definition - Segmentation by End-Users
• 6.2 Market Revenue Share, Historic Growth, Outlook, and Forecasts by End-Users, 2017-2028

6.2.1 Banking, Financial, Services, and Insurance

6.2.2 IT and Telecom

6.2.3 Automotive

6.2.4 Healthcare

6.2.5 Aerospace and Defence

6.2.6 Retail

6.2.7 Government

6.2.8 Others

• 6.3 Key Takeaways from Market Segmentation by End-Users

7. Industry / Competition Analysis - Competitive Landscape

• 7.1 Types of Players (Competitors) & Share of Competition
• 7.2 Porter's 5 Forces Analysis of Global Machine Learning as a Service (MLaaS) Market Competitors
• 7.3 Key Developments in the Global Machine Learning as a Service (MLaaS) Sector Impacting Market Growth
• 7.4 Comparison of Leading Competitors within Global Machine Learning as a Service (MLaaS) Market, 2021
• 7.5 Comparison of Leading Competitors within the Global Machine Learning as a Service (MLaaS) Market by Coverage of Component, 2021
• 7.6 Comparison of Leading Competitors within Global Machine Learning as a Service (MLaaS) Market by Coverage of Application, 2021
• 7.7 Comparison of Leading Competitors within Global Machine Learning as a Service (MLaaS) Market by Coverage of Enterprises, 2021
• 7.8 Comparison of Leading Competitors within Global Machine Learning as a Service (MLaaS) Market by Coverage of End-user, 2021
• 7.9 Comparison of Leading Competitors within the Global Machine Learning as a Service (MLaaS) Market by Coverage of Region, 2021
• 7.10 Key Takeaways from Competitive Landscape

8. Key Competitor Profiles (Company Overview, Product Offerings, Developments)

• 8.1 Amazon
• 8.2 Google LLC
• 8.3 IBM Corporation
• 8.4 Microsoft Corporation
• 8.5 Oracle Corporation
• 8.6 HPE
• 8.7 SAS Institute Inc.
• 8.8 FICO
• 8.9 Yottamine Analystics, LLC
• 8.10 Predictron Labs Ltd.
• 8.11 BigML
• 8.12 ErsatzLabs, Inc.

9. Geographic Analysis & Major Region Market Historic Growth, Outlook, and Forecasts

• 9.1 Major Region Comparison of Macroeconomic Factors
• 9.2 Global- Market Revenue Share, Historic Growth, Outlook, and Forecasts by Region, 2017-2028
• 9.3 Major Region Market Analysis, Historic Growth, Outlook & Forecasts
• 9.4 North America - Machine Learning as a Service (MLaaS) Market Analysis

9.4.1 Major Production and Consumption Hubs in North America

9.4.2 Notable Emerging Machine Learning as a Service (MLaaS) Companies in North America

9.4.3 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Component, 2017-2028

9.4.4 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Applications, 2017-2028

9.4.5 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Enterprises 2017-2028

9.4.6 Market Revenue Share, Historic Growth, Outlook, and Forecasts by End-user, 2017-2028

9.4.7 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Geography Coverage, 2017-2028

9.4.7.1 USA

9.4.7.2 Canada

9.4.7.3 Mexico

• 9.5 Europe - Machine Learning as a Service (MLaaS) Market Analysis

9.5.1 Major Production and Consumption Hubs in Europe

9.5.2 Notable Emerging Machine Learning as a Service (MLaaS) Companies in Europe

9.5.3 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Component, 2017-2028

9.5.4 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Application, 2017-2028

9.5.5 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Enterprises 2017-2028

9.5.6 Market Revenue Share, Historic Growth, Outlook, and Forecasts by End-user, 2017-2028

9.5.7 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Geography Coverage, 2017-2028

9.5.7.1 UK

9.5.7.2 Germany

9.5.7.3 France

9.5.7.4 Italy

9.5.7.5 Spain

9.5.7.6 Rest of Europe

• 9.6 Asia Pacific - Machine Learning as a Service (MLaaS) Market Analysis

9.6.1 Major Production and Consumption Hubs in the Asia Pacific

9.6.2 Notable Emerging Machine Learning as a Service (MLaaS) Companies in the Asia Pacific

9.6.3 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Component, 2017-2028

9.6.4 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Application, 2017-2028

9.6.5 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Enterprises 2017-2028

9.6.6 Market Revenue Share, Historic Growth, Outlook, and Forecasts by End-user, 2017-2028

9.6.7 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Geography coverage, 2017-2028

9.6.7.1 China

9.6.7.2 India

9.6.7.3 Japan

9.6.7.4 South Korea

9.6.7.5 Indonesia

9.6.7.6 Australia

9.6.7.7 Rest of Asia Pacific

• 9.7 LAMEA - Machine Learning as a Service (MLaaS) Market Analysis

9.7.1 Major Production and Consumption Hubs in LAMEA

9.7.2 Notable Emerging Machine Learning as a Service (MLaaS) Companies in LAMEA

9.7.3 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Component, 2017-2028

9.7.4 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Application, 2017-2028

9.7.5 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Enterprises 2017-2028

9.7.6 Market Revenue Share, Historic Growth, Outlook, and Forecasts by End-user, 2017-2028

9.7.7 Market Revenue Share, Historic Growth, Outlook, and Forecasts by Major Region, 2017-2028

Latin America

Middle East

Africa

10. Industry Expert's Opinions/Perspectives

• 10.1 Notable Statements/Quotes from Industry Experts and C-Level Executives on Current Status and Future Outlook of the Market

11. Analyst Recommendation

• 11.1 Analyst Recommendations on Identified Major Opportunities and Potential Strategies to Gain from Opportunities

12. Appendix

• 12.1 Research Methodology - Market Size Estimation, Forecast, and Sanity Check Approach
• 12.2 Sample Discussion Guide

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