Machine Learning as a Service (MLaaS) Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)

The Machine Learning as a Service (MLaaS) Market is Segmented by Application (Advertising and Marketing, Predictive Maintenance, Automated Network Management), Organization Size (SMB and Large Enterprises), End User (BFSI, IT and Telecom, Healthcare), and Geography.

  • ABOUT THIS REPORT
    • Market Snapshot
    • Market Overview
    • Scope of the Report
    • Key Market Trends
    • Competitive Landscape
    • Major Players
  • TABLE OF CONTENTS

Market Snapshot

Study Period:

2018 - 2026

Base Year:

2020

Fastest Growing Market:

Asia Pacific

Largest Market:

North America

CAGR:

43 %

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Market Overview

The Machine Learning as a Service (MLaaS) Market was valued at USD 1.0 billion in 2020 and is expected to reach USD 8.48 billion by 2026, at a CAGR of 43% over the forecast period (2021-2026). With advancements in data science and artificial intelligence, the performance of machine learning has accelerated at a rapid pace. Companies are now identifying the potential this technology has, and therefore, the adoption rate of the same is expected to increase over the forecast period.

  • Artificial intelligence has emerged as an enabler for such solutions, and ML consequently plays a critical role.
  • MLaaS model is expected to dominate the market, with users having an option to choose from a wide variety of solutions that are focused on different business needs.
  • The increasing rate of adoption for IoT and automation systems in industries is expected to drive the growth of the adoption rate for MLaaS. Industrial automation already has over a billion connected devices deployed. Owing to IoT, smart and connected technologies have increased the pace of creating vast amounts of data, which can be analyzed to gain profitable insights.

Scope of the Report

Machine learning (ML), a subfield of artificial intelligence (AI) in its simplest description, spans a broad set of algorithms used to extract useful models from raw data. It was developed from traditional statistics and analysis. Since it revolves around algorithms, model complexity, and computational complexity, the market for machine learning as a service (MLaaS) is in demand. The market requires the use of skilled professionals to develop these solutions.

By Application
Marketing and Advertisement
Predictive Maintenance
Automated Network Management
Fraud Detection and Risk Analytics
Other Applications
By Organization Size
Small and Medium Enterprises
Large Enterprises
By End User
IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other End Users
Geography
North America
Europe
Asia-Pacific
Rest of the World

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Key Market Trends

Retail Sector is Expected to hold Major Market Share

  • The retail industry is booming in the digital space. The digital revolution was started by prominent companies, like Amazon and eBay. The popularity of digital business models has created challenges for the traditional retail business model. However, it also has massive potential for retailers and consumers alike.
  • Retail and consumer goods companies are witnessing the applicability of machine learning (ML) in driving improvements in customer service and operational efficiency. For instance, the Azure cloud is helping retail and consumer brands to improve the customer's shopping experience by ensuring that shelves are stocked and the products are always available when, where, and how the consumer wants to shop.

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North America is Expected to Hold Largest Market Share

  • North America is driven by swift market penetration and the presence of large companies working on technology that influences the growth of the market in the region.
  • North America commands machine learning services over other key regions, on account of rapid integration of machine learning as a service with big data, Internet of Things (IoT), and other advanced technologies. The region has the headquarters of some of the top companies for machine learning as a service, which is an advantage. 
  • Companies based in North America, for instance, news organizations, such as the Associated Press, are increasingly publishing new articles and stories written by software, instead of journalists. At the same time, Google is training its AI software, DeepMind, to detect two common types of eye diseases. Microsoft has been using AI for about a decade to improve its online search engine.

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Competitive Landscape

The machine learning as a service market is highly competitive and consists of several major players. In terms of market share, few major players, currently dominate the market. However, with the advancement of Artificial Intelligence, many companies are increasing their market presence by securing new contracts, by tapping new markets.

  • April 2019 - Microsoft developed a platform that uses machine teaching to help deep reinforcement learning algorithms tackle real-world problems. Microsoft scientists and product developers have pioneered a complementary approach called machine teaching. This relies on people’s expertise to break a problem into easier tasks and give machine learning models important clues about how to find a solution faster.
  • November 2018 - Amazon announced the expansion of its machine learning services to healthcare organizations. Amazon Translate, Amazon Comprehend, and Amazon Transcribe are now HIPAA compliant.

Major Players

  1. Microsoft Corporation
  2. IBM Corporation
  3. Google LLC
  4. SAS Institute Inc.
  5. Hewlett Packard Enterprise

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Table Of Contents

  1. 1. INTRODUCTION

    1. 1.1 Study Deliverables

    2. 1.2 Study Assumptions

    3. 1.3 Scope of the Study

  2. 2. RESEARCH METHODOLOGY

  3. 3. EXECUTIVE SUMMARY

  4. 4. MARKET DYNAMICS

    1. 4.1 Market Overview

    2. 4.2 Introduction to Market Drivers and Restraints

    3. 4.3 Market Drivers

      1. 4.3.1 Increasing Adoption of IoT and Automation

      2. 4.3.2 Increasing Adoption of Cloud-based Services

      3. 4.3.3 Growing Demand for Digitalization across Multiple End-User Segments

    4. 4.4 Market Restraints

      1. 4.4.1 Privacy and Data Security Concerns

      2. 4.4.2 Need for Skilled Professionals

    5. 4.5 Industry Attractiveness - Porter's Five Forces Analysis

      1. 4.5.1 Threat of New Entrants

      2. 4.5.2 Bargaining Power of Buyers/Consumers

      3. 4.5.3 Bargaining Power of Suppliers

      4. 4.5.4 Threat of Substitute Products

      5. 4.5.5 Intensity of Competitive Rivalry

  5. 5. MARKET SEGMENTATION

    1. 5.1 By Application

      1. 5.1.1 Marketing and Advertisement

      2. 5.1.2 Predictive Maintenance

      3. 5.1.3 Automated Network Management

      4. 5.1.4 Fraud Detection and Risk Analytics

      5. 5.1.5 Other Applications

    2. 5.2 By Organization Size

      1. 5.2.1 Small and Medium Enterprises

      2. 5.2.2 Large Enterprises

    3. 5.3 By End User

      1. 5.3.1 IT and Telecom

      2. 5.3.2 Automotive

      3. 5.3.3 Healthcare

      4. 5.3.4 Aerospace and Defense

      5. 5.3.5 Retail

      6. 5.3.6 Government

      7. 5.3.7 BFSI

      8. 5.3.8 Other End Users

    4. 5.4 Geography

      1. 5.4.1 North America

      2. 5.4.2 Europe

      3. 5.4.3 Asia-Pacific

      4. 5.4.4 Rest of the World

  6. 6. COMPETITIVE LANDSCAPE

    1. 6.1 Company Profiles

      1. 6.1.1 Microsoft Corporation

      2. 6.1.2 IBM Corporation

      3. 6.1.3 Google LLC

      4. 6.1.4 SAS Institute Inc.

      5. 6.1.5 Fair Isaac Corporation (FICO)

      6. 6.1.6 Hewlett Packard Enterprise Company

      7. 6.1.7 Yottamine Analytics LLC

      8. 6.1.8 Amazon Web Services Inc.

      9. 6.1.9 BigML Inc.

      10. 6.1.10 Iflowsoft Solutions Inc.

      11. 6.1.11 PurePredictive Inc.

      12. 6.1.12 Sift Science Inc.

      13. 6.1.13 H2O.ai Inc.

    7. *List Not Exhaustive

  7. 7. INVESTMENT ANALYSIS

  8. 8. MARKET OPPORTUNITIES AND FUTURE TRENDS

** Subject to Availability

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