According to the latest report by IMARC Group, titled, “Machine Learning as a Service (MLaaS) Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027", the global machine learning as a service (MLaaS) market reached a value of US$ 3.90 Billion in 2021. Looking forward, IMARC Group expects the market to reach US$ 25.67 Billion by 2027, exhibiting at a CAGR of 36.80% during 2022-2027.
Machine learning comprises a broad set of algorithms that are used to draw valuable models from raw data. Machine learning as a service (MLaaS) helps identify the benefits of cost-effective data storage and assists in setting up effective data governance. These solutions are widely used across various sectors, such as information technology (IT), telecom, automotive, healthcare, aerospace and defense.
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The global market is majorly driven by the rising digital transformations across multiple industries. Moreover, MLaaS are widely employed in cybersecurity and online fraud detection systems across numerous organizations. Coupled with the increasing adoption of cloud-based services across the globe, this is providing an impetus to the market growth. Furthermore, the rising demand for consumer behavior analysis and continual advancements in network connectivity technology have positively influenced the market growth. Other factors, including significant growth in the IT sector, the growing need for operational excellence and the widespread adoption of cloud-based solutions in the banking, financial services and insurance (BFSI) sector, have also created a positive outlook for the market.
Note: We are regularly tracking the direct effect of COVID-19 on the market, along with the indirect influence of associated industries. These observations will be integrated into the report.
The competitive landscape of the industry has also been examined along with the profiles of the key players.
The report has segmented the market based on component, organization size, application and end user.
Breakup by Component:
Breakup by Organization Size:
Breakup by Application:
Breakup by End User:
Breakup by Region:
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