What's driving the Machine Learning as a Service (MLaaS) Market Growth? IBM, Google, Amazon Web Services (AWS), Microsoft, AT&T and SAS

The global machine learning as a service market is on a significant rise because of the ongoing revolution of internet and its related services. Service category contributed a larger revenue to the global market in 2016 due to increase in the demand for advanced cloud based machine learning services across sectors. MLaaS refers to a range of services which offer machine learning tools as part of advanced cloud computing services.

The tools in the MLaaS include data visualization, application program interface (API), face recognition, natural language processing, and predictive analytics and deep learning. The prime attraction of MLaaS is that consumers can get started easily with machine learning without the need to install software, or provision their own servers, just like any other cloud service.

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The global market is on a significant rise because of the ongoing revolution of internet and its related services. The trend of bridging the world’s applications and resources virtually, has generated huge amounts of data. Since the mainstream deployment of machine learning enhances the overall speed and accuracy of functions performed by a particular operating system, this factor has boosted the overall adoption of machine learning within many organizations. In addition, the introduction of analytics technologies such as predictive analytics by several verticals, including healthcare and life sciences, IT & Telecom, BFSI, and retail & manufacturing, is also contributing highly towards the market growth,globally.

The market is categorized mainly into two components, software and service. The service category wasthe larger contributor to global revenue during 2013-2016. In the service category, professional service accounts for the larger share in the market as compared to managed service.On the other hand, the market for managed services is expected to grow faster during the forecast period. Professional services include support & maintenance, consulting & integration, network security services, and analytics, which are backing the growth and awareness of MLaaS adoption, globally.

The recent rise in demand to understand consumer behaviour and purchasing patterns across verticals is one of the prime factors for the growth of machine learning industry. Recommendation systems, which are now being used across a wide range of industries such as online shopping sites, help organisations to get a deeper insight about their customer behaviour and product buying pattern. This further enables them in discovering new and relevant product specific offers, which ultimately lead to a strong and healthy customer relationship, and further generate higher sales for the business. Also, machine learning as service helps leaders in making important decisions during real time operation with best outcome predictions.

North America has been the largest revenue contributor to the global market. The market in the region is also expected to grow the fastest during the forecast period. The fastest growth is expected to be fuelled by the increase in the need for integration of MLaaS with big data, and rise in IoT and other advanced data oriented technologies. Another reason which is expected to escalate the demand for machine learning solutions is the rapid expansion of all sized enterprises in the region. On the other hand, the market in Asia-Pacific is also expected to witness significant growth in coming years. The high growth in Asia-Pacific is expected to be backed by rise in investment for analytics and predictive software development by regional players, growth in adoption of machine learning tools, and the ongoing e-commerce wave.

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Some of the prominent players operating in the global machine learning industry are IBM Corporation, Google Inc., Amazon Web Services, Microsoft Corporation, AT&T, FICO, Fuzzy.ai, Yottamine Analytics, Ersatz Labs Inc, Predictron Labs Ltd and SAS Institute.

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This release was published on openPR.