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Machine Learning-as-a-Service Market Size, Share & Trends Analysis - Global opportunity analysis and industry forecast 2030

Machine Learning-as-a-Service Market Size, Share & Trends Analysis - Global...

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Machine Learning-as-a-Service Market Size, Share & Trends Analysis - Global opportunity analysis and industry forecast 2030
Machine Learning-as-a-Service Market Size, Share...
Report Code
RO13/107/1829

Publish Date
26/Apr/2022

Pages
210
PRICE
$ 4570 /-
$ 5450 /-
$ 7695 /-

The global machine learning-as-a-service (MLaaS) market size was US$ 2.5 billion in 2021. The global machine learning-as-a-service (MLaaS) market size is forecast to reach US$ 32.3 billion by 2030, growing at a compound annual growth rate (CAGR) of 39.9% during the forecast period from 2022 to 2030. 

Machine learning-as-a-service encompasses a wide range of services, solutions, and methodologies closely related to artificial intelligence (AI), which analyses input data statistically to determine its current or future relationship and performance. Machine learning makes use of a large amount of data to increase analytical output while streamlining workflow in a variety of industries. Machine learning-as-a-service (MLaaS) refers to a collection of cloud-based services that provide machine learning technologies. 

Factors Influencing Market Growth

  • The growing IT expenditures in emerging countries and technological advances for workflow optimization fuel the demand for advanced analytical systems. Thus, this factor drives the global market. 
  • The growing penetration of cloud-based solutions, the increase associated with the artificial intelligence and cognitive computing market, and rising prediction solutions demand in the market fuels global market growth.
  • The lack of trained professionals may slow down the overall market growth during the forecast period.

Impact Analysis of COVID-19

The COVID-19 pandemic had a positive impact on the global market growth. Due to the COVID-19 pandemic, the government worldwide imposed a lockdown in order to curb the spread of the deadly virus. As a result, companies globally had to change their working patterns. In addition, many organizations revved their migrations to public cloud solutions since cloud service elasticity can meet unpredictable spikes in service demand. Migrations to cloud-enabled companies reinvent the way they run their businesses in the time of COVID-19. The need for AI services has increased, and many cloud providers offer AIaaS and MLaaS. 

Regional Insights

North America is forecast to garner a substantial share in the market during the forecast period. The growth of MLaaS aid by a dynamic invention ecosystem fueled by significant federal investments in sophisticated technology and the presence of visionary scientists and entrepreneurs from globally recognized research institutions. In addition, the region is seeing a huge increase in 5G, IoT, and connected devices. As a result, through virtualization, network slicing, new use-cases, and service requirements, communications service providers (CSPs) must effectively handle an ever-increasing complexity. As traditional network and service management methodologies are no longer viable, this is forecast to fuel the market growth in the region. MLaaS alternatives.

Leading Competitors

The leading prominent companies profiled in the global machine learning-as-a-service market are:

  • Microsoft Corporation
  • SAS Institute Incorporated
  • Fair Isaac Corporation (FICO)
  • Google LLC
  • IBM Corporation
  • Hewlett Packard Enterprise Company
  • Yottamine Analytics LLC
  • BigML Incorporated
  • Iflowsoft Solutions Incorporated
  • Amazon Web Services Incorporated
  • Monkeylearn Incorporated
  • Sift Science Incorporated
  • H2O.ai Incorporated
  • Other Prominent Players

Scope of the Report

The global machine learning-as-a-service market segmentation focuses on Application, Organization Size, End-Users, and Region.

Segmentation based on Application

  • Marketing and Advertisement
  • Predictive Maintenance
  • Automated Network Management
  • Fraud Detection and Risk Analytics
  • Natural language processing (NLP) 
  • Sentiment Analysis
  • Computer Vision
  • Other Applications

Segmentation based on Organization Size

  • Small Enterprises
  • Medium Enterprises
  • Large Enterprises

Segmentation based on End-Users

  • IT and Telecom
  • Automotive
  • Healthcare
  • Aerospace and Defense
  • Retail
  • Government
  • BFSI
  • Education
  • Media and Entertainment
  • Agriculture
  • Other End Users

Segmentation based on Region

  • North America
  • The U.S.
  • Canada
  • Mexico
  • Europe
  • Western Europe
  • The UK
  • Germany
  • France
  • Italy
  • Spain
  • Rest of Western Europe
  • Eastern Europe
  • Poland
  • Russia
  • Rest of Eastern Europe
  • Asia Pacific
  • China
  • India
  • Japan
  • Australia & New Zealand
  • ASEAN
  • Rest of Asia Pacific
  • Middle East & Africa (MEA)
  • UAE
  • Saudi Arabia
  • South Africa
  • Rest of MEA
  • South America
  • Brazil
  • Argentina
  • Rest of South America

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