Machine Learning as a Service (MLaaS) Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

Machine Learning as a Service (MLaaS) Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028

The global machine learning as a service (MLaaS) market size reached US$ 5.7 Billion in 2022. Looking forward, IMARC Group expects the market to reach US$ 31.0 Billion by 2028, exhibiting a growth rate (CAGR) of 31.2%during 2023-2028.

Machine learning as service (MLaaS) refers to a set of cloud-based platforms that offer machine learning (ML) tools on the go. It offers the benefits of cost-effective data storage, pre-made pipelines for data ingestion, and toolkits for setting up effective data governance. Moreover, it plays a vital role in eradicating infrastructural concerns, such as model training and evaluation and pre-processing. It also enables deep learning, data visualization, accurate regression, speech and face recognition, predictive analytics, and computer vision. Consequently, organizations nowadays use MLaaS to meet the dynamic business needs, such as personalizing search results and predicting product demand.

Machine Learning as a Service (MLaaS) Market Trends:
Several companies presently are transferring their data from on-premise storage to cloud storage systems. This acts as a key factor driving the need for MLaaS to organize the data properly. Apart from this, the widespread adoption of Internet of Things (IoT) devices and systems in enterprise automation is propelling the market growth. Besides this, the escalating demand for personalization and developments in virtual technologies, such as virtual assistants, augmented reality (AR), smart storage management, and logistics, is contributing to the market growth. Furthermore, MLaaS is gaining traction in designing chatbots and virtual assistants, quality control and detection of manufacturing defects, automating business documentation workflow, and natural language processing (NLP) tasks. Additionally, as ML can detect disease and virus infections accurately, it is used to automate the task of predicting coronavirus disease (COVID-19) infection and forecast future infection tallies. In line with this, scientists across the globe are focusing on developing ML-based smart solutions. These solutions assist in diagnosing and treating various diseases at an early stage, which is anticipated to drive the market.

Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global machine learning as a service (MLaaS) market report, along with forecasts at the global and regional level from 2023-2028. Our report has categorized the market based on component, organization size, application and end user.

Breakup by Component:

Software
Services

Breakup by Organization Size:

Small and Medium-sized Enterprises
Large Enterprises

Breakup by Application:

Marketing and Advertising
Fraud Detection and Risk Management
Predictive Analytics
Augmented and Virtual Reality
Natural Language Processing
Computer Vision
Security and Surveillance
Others

Breakup by End User:

IT and Telecom
Automotive
Healthcare
Aerospace and Defense
Retail
Government
BFSI
Other

Breakup by Region:

North America
United States
Canada
Asia-Pacific
China
Japan
India
South Korea
Australia
Indonesia
Others
Europe
Germany
France
United Kingdom
Italy
Spain
Russia
Others
Latin America
Brazil
Mexico
Others
Middle East and Africa

Competitive Landscape:
The competitive landscape of the industry has also been examined along with the profiles of the key players being Amazon.com Inc., Bigml Inc., Fair Isaac Corporation, Google LLC (Alphabet Inc.), H2O.ai Inc., Hewlett Packard Enterprise Development LP, Iflowsoft Solutions Inc., International Business Machines Corporation, Microsoft Corporation, MonkeyLearn, Sas Institute Inc. and Yottamine Analytics Inc.

Key Questions Answered in This Report
1. What was the size of the global machine learning as a service (MLaaS) market in 2022?
2. What is the expected growth rate of the global machine learning as a service (MLaaS) market during 2023-2028?
3. What are the key factors driving the global machine learning as a service (MLaaS) market?
4. What has been the impact of COVID-19 on the global machine learning as a service (MLaaS) market?
5. What is the breakup of the global machine learning as a service (MLaaS) market based on the component?
6. What is the breakup of the global machine learning as a service (MLaaS) market based on organization size?
7. What is the breakup of the global machine learning as a service (MLaaS) market based on the application?
8. What is the breakup of the global machine learning as a service (MLaaS) market based on the end user?
9. What are the key regions in the global machine learning as a service (MLaaS) market?
10. Who are the key players/companies in the global machine learning as a service (MLaaS) market?