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Report Description

Report Description

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.


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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.

Attribute

Details

Base Year

2022

Historic Data

2018 – 2021

Estimated Year

2023

Forecast Period

2024 – 2028

Quantitative Units

Revenue in USD Million, and CAGR for 2018-2022 and 2023-2028

Report coverage

Revenue forecast, company share, growth factors, and trends

Segments covered

·         By Component

·         By Organization Size

·         By Application

·         By End-User

·         By Region

Regional scope

North America, Asia Pacific, Europe, Latin America, MEA

Country scope

United States; Canada; Mexico; China; Indian; Japan; South Korea; Australia; Germany; United Kingdom; France; Italy Spain; Saudi Arabia; South Africa; UAE; Brazil; Colombia; Argentina;

Key companies profiled

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

Customization scope

10% free report customization with purchase. Addition or alteration to country, regional & segment scope.

Pricing and purchase options

Avail customized purchase options to meet your exact research needs. Explore purchase options

Delivery Format

PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request)


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).

Global Machine Learning as a Service Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

Table of content

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 (Public, Private, Consortium and Hybrid)

6.2.2.                           By Organization Size (Large Enterprises, Small and Medium-Sized Enterprises)

6.2.3.                           By Application (Marketing & Advertising, Fraud Detection & Risk Management, Computer vision, Security & Surveillance, Predictive analytics, Natural Language Processing, Augmented & Virtual Reality, 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

Figures and Tables

Frequently asked questions

Frequently asked questions

Machine learning are now used to gather and analyze social, behavioral and historical data which helps gain better understanding of the customers.

The main attraction of these services is that user can start quickly with machine learning without installing any software or provision to own servers.

Machine learning is driving an era of automation benefiting global leaders in increasing productivity and optimizing internal business operations.

Healthcare industry uses machine learning the most because it can be used to analyze and process medical data to provide better insights to medical doctors and researchers.

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