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The Global Machine Learning as a Service (MLaaS) Market, By Deployment (Public Cloud, Private Cloud/Virtual Private Cloud) By End-use Application (Manufacturing, Retail, Healthcare & Life Sciences, Telecom, Banking, Financial services and Insurance (BFSI), Others (Energy & Utilities, Government, Education etc.) and by Region (North America, Europe, Asia Pacific, Latin America, Middle East and Africa) - Global Forecast to 2027”, is expected to be valued at US$ 38,063.0million by 2027, exhibiting a CAGR of 38.6% during the forecast period (2019-2027), as highlighted in a report published by Coherent Market Insights.

Overview

Machine learning as-a-service a plethora of services that offer machine learning capabilities as a part of cloud computing services. MLaaS providers offer various machine learning tools including API, predictive analytics, deep learning, data visualization, natural language processing, etc. A number of cloud computing service providers offer machine learning as a service including Amazon, IBM Corporation, and Microsoft Corporation. Moreover, MLaaS is offered on a limited trial basis for a developer to evaluate before committing to a particular platform. The major advantage that MLaaS offers to businesses is that it enables them to get started quickly with machine learning without undergoing tedious software installation processes.

The global machine learning as a service (MLaaS) market was valued US$ 2,802.8Mn in 2019 and expected to grow at a CAGR of 36.8% over the forecasted period 2019-27.

Market Driver

Rising need for smart machines is expected to drive growth of the global machine learning as a service (MLaaS) market during the forecast period

Majority of companies are preferring the use of smart machines, which are capable of learning on their own and improving their performance over time. Furthermore, these companies are constantly seeking novel technology that helps machines identify real-time incidence and offer predictions to reduce human errors and also save time. Growing demand to enhance the capability of machines to make decisions on their own is expected to propel the global machine learning as a service (MLaaS) market growth over the forecast period.

Market Opportunity

Growing internet penetration and enhanced data generation on a different platform is expected to present lucrative growth opportunities

Rising internet penetration across the globe, especially in emerging economies, has increased the connectivity. Furthermore, growing adoption of IoT-enabled devices and platforms has led to increase in data generation. Processing and analyzing such a vast amount of data requires enhanced capabilities, which can be fulfilled with machine learning solutions. Major MLaaS providers in the market can offer novel solutions and gain a competitive edge in the market.

Market Restraint

Stringent government norms and compliant issues are expected to restrain growth of the global machine learning as a service (MLaaS) market during the forecast period

Since machine leering solutions process and analyze a lot of confidential data and information, they are subjected to strict regulatory framework. MLaaS providers are expected to comply with these strict regulatory norms enforced by local governments. Moreover, these rules and regulations vary with each country, thus solutions providers need to make suitable adjustments to their services, in order to comply with regulatory framework. Such factors are expected to restrict growth of the global machine learning as a service (MLaaS) market during the forecast period.

Key Takeaways

Market Trends

  1. Retail and e-commerce verticals are expected to hold dominant position

Retail and e-commerce are two major sectors where machine learning is being increasingly adopted. Retail owners and e-commerce business owners are focused on implementing machine learning tools to understand their customers, their preferences, and their spending habits. These insights would help e-commerce business owners and retailers to strategically change their marketing strategy and gain a competitive edge in the market. Moreover, machine learning can be used to facilitate smooth functioning in supply chain and warehouse facilities and enhance overall productivity of the business.

  1. Rising adoption of MLaaS in automated traffic management

In many countries, governments are increasingly adopting machine learning tools, in order to manage traffic in a better manner. Machine learning tools can help transport authorities to understand traffic patterns, traffic density, enhance road safety, and other factors affecting mobility of traffic. As a result of this, traffic management capabilities can be enhanced, especially during peak hours.

Competitive Section

Key players involved in the global machine learning as a service (MLaaS) market are H2O.ai, Google Inc., Predictron Labs Ltd, IBM Corporation, Ersatz Labs Inc., Microsoft Corporation, Yottamine Analytics, Amazon Web Services Inc., FICO, and BigML Inc.

Key Developments

  1. Major market players are focused on partnerships and collaborations, in order to gain a competitive advantage in the market. For instance, in February 2017, Microsoft Corporation partnered with Flipkart, under which Flipkart will adopt the Microsoft Azure cloud platform with artificial intelligence, machine learning, and analytics capabilities.
  2. Key companies in the market are focused on product and service launches, in order to enhance the market presence. For instance, in November 2018, Amazon Web Services Inc. launched 13 new machine learning services and capabilities, which includes custom chip for machine learning interface.

Segmentation

Market Taxonomy:

  1. By Deployment

Public Cloud

Private Cloud/Virtual Private Cloud

  1. By End-use Application
  • Manufacturing
  • Retail
  • Healthcare & Life Sciences
  • Telecom
  • Banking, Financial services and Insurance (BFSI)
  • Others (Energy & Utilities, Government, Education etc.)
  1. By Region
  • North America
  • Europe
  • Middle East and Africa
  • Latin America
  • Asia Pacific
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