by The global Machine Learning as a Service (MLaaS) Market is estimated to be valued at US$5,228.3 Mn in 2021 and is expected to exhibit a CAGR of 38.8% over the forecast period from 2022 to 2030, as highlighted in a new report published by Coherent Market Insights.
Market Overview:
Machine Learning as a Service (MLaaS) refers to the provision of machine learning capabilities and algorithms as a cloud-based service. It enables organizations, especially small and medium enterprises (SMEs), to gain access to advanced machine learning solutions without the need for extensive in-house resources or expertise. MLaaS offers numerous advantages, such as cost-effectiveness, scalability, and flexibility, making it an ideal choice for businesses looking to leverage the power of machine learning for their operations. The growing need to analyze and make sense of large volumes of data generated by businesses and the increasing demand for predictive analytics are driving the adoption of MLaaS solutions across various industries.
Market Key Trends:
One of the key trends in the MLaaS market is the rising adoption of MLaaS by small and medium enterprises (SMEs). Traditionally, SMEs have faced barriers such as limited resources and expertise to deploy machine learning models. With the availability of MLaaS solutions, SMEs can now easily access pre-built machine learning models and algorithms, eliminating the need for heavy investments in infrastructure and technical expertise. MLaaS enables SMEs to quickly and efficiently deploy machine learning capabilities, leading to improved decision-making, enhanced customer experience, and increased operational efficiency. The increasing recognition of the potential benefits of MLaaS among SMEs is expected to drive the growth of the MLaaS market in the coming years.
Porter’s Analysis
Threat of New Entrants: The machine learning as a service market is expected to face a low threat of new entrants. The market is highly competitive and dominated by key players, which makes it difficult for new entrants to gain market share. Furthermore, the high initial investment required to develop machine learning platforms and the need for specialized technical expertise act as barriers to entry for new players.
Bargaining Power of Buyers: The bargaining power of buyers in the machine learning as a service market is moderate. While buyers have the option to choose from multiple service providers, the high switching costs associated with transferring data and projects from one provider to another limits their bargaining power. Additionally, the increasing demand for machine learning services and limited availability of skilled professionals give service providers an advantage in negotiations with buyers.
Bargaining Power of Suppliers: The bargaining power of suppliers in the machine learning as a service market is low. The suppliers in this market are mainly software and cloud service providers. As the demand for machine learning services grows, suppliers are competing to offer advanced solutions and better pricing, giving buyers more options and reducing the bargaining power of suppliers.
Threat of New Substitutes: The threat of new substitutes in the machine learning as a service market is low. Machine learning has become an integral part of various industries and is widely used for data analysis, prediction, and automation. While there may be alternative methods for data analysis and prediction, machine learning offers unique capabilities and accuracy that are difficult to replicate with traditional methods.
Competitive Rivalry: The competitive rivalry in the machine learning as a service market is high. There are several key players operating in the market, including H2O.ai, Google Inc., IBM Corporation, Microsoft Corporation, and Amazon Web Services Inc. These players are constantly innovating and expanding their product portfolios to gain a competitive edge. Additionally, the market is witnessing the entry of new players, further intensifying the competition.
Key Takeaways
The global Machine Learning as a Service (MLaaS) Market is expected to witness high growth, exhibiting a CAGR of 38.8% over the forecast period. This growth is driven by the increasing demand for machine learning services across various industries, such as healthcare, finance, and retail. Machine learning helps organizations automate processes, make data-driven decisions, and gain valuable insights. For example, in the healthcare sector, machine learning algorithms can be used to analyze patient data and predict disease outcomes, leading to improved diagnosis and treatment.
In terms of regional analysis, North America is expected to be the fastest-growing and dominating region in the machine learning as a service market. The region has a strong presence of key players, technological advancements, and a high adoption rate of machine learning services. Moreover, the increasing focus on data-driven decision making and the presence of a large customer base are driving the growth of the market in this region.
The key players operating in the machine learning as a service market include H2O.ai, Google Inc., IBM Corporation, Microsoft Corporation, Amazon Web Services Inc., and others. These players offer a wide range of machine learning platforms and solutions to cater to the diverse needs of organizations. They are focusing on product development, strategic partnerships, and acquisitions to expand their market share and stay ahead of the competition.
*Note:
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it
