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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.
2018 - 2026
Fastest Growing Market:
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.
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.
|Marketing and Advertisement|
|Automated Network Management|
|Fraud Detection and Risk Analytics|
|By Organization Size|
|Small and Medium Enterprises|
|By End User|
|IT and Telecom|
|Aerospace and Defense|
|Other End Users|
|Rest of the World|
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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.
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET DYNAMICS
4.1 Market Overview
4.2 Introduction to Market Drivers and Restraints
4.3 Market Drivers
4.3.1 Increasing Adoption of IoT and Automation
4.3.2 Increasing Adoption of Cloud-based Services
4.3.3 Growing Demand for Digitalization across Multiple End-User Segments
4.4 Market Restraints
4.4.1 Privacy and Data Security Concerns
4.4.2 Need for Skilled Professionals
4.5 Industry Attractiveness - Porter's Five Forces Analysis
4.5.1 Threat of New Entrants
4.5.2 Bargaining Power of Buyers/Consumers
4.5.3 Bargaining Power of Suppliers
4.5.4 Threat of Substitute Products
4.5.5 Intensity of Competitive Rivalry
5. MARKET SEGMENTATION
5.1 By Application
5.1.1 Marketing and Advertisement
5.1.2 Predictive Maintenance
5.1.3 Automated Network Management
5.1.4 Fraud Detection and Risk Analytics
5.1.5 Other Applications
5.2 By Organization Size
5.2.1 Small and Medium Enterprises
5.2.2 Large Enterprises
5.3 By End User
5.3.1 IT and Telecom
5.3.4 Aerospace and Defense
5.3.8 Other End Users
5.4.1 North America
5.4.4 Rest of the World
6. COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 Microsoft Corporation
6.1.2 IBM Corporation
6.1.3 Google LLC
6.1.4 SAS Institute Inc.
6.1.5 Fair Isaac Corporation (FICO)
6.1.6 Hewlett Packard Enterprise Company
6.1.7 Yottamine Analytics LLC
6.1.8 Amazon Web Services Inc.
6.1.9 BigML Inc.
6.1.10 Iflowsoft Solutions Inc.
6.1.11 PurePredictive Inc.
6.1.12 Sift Science Inc.
6.1.13 H2O.ai Inc.
7. INVESTMENT ANALYSIS
8. MARKET OPPORTUNITIES AND FUTURE TRENDS
** Subject to Availability