Machine Learning as a Service Market to Reach USD 304.82 Billion by 2032 at 36.20% CAGR: Market Research Future

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According to a report by Market Research Future (MRFR), the Machine Learning as a Service (MLaaS) market is expected to grow at a compound annual growth rate (CAGR) of 36.20% between 2023 and 2032, with a projected market size of USD 304.82 billion by 2032. The expanding use of the Internet of Things (IoT) is driving the growth of MLaaS add-ons, and as more businesses adopt IoT-based technologies and solutions, machine learning technology is becoming increasingly popular for data analytics. MLaaS would encourage IoT innovation by assisting in automation.

The market segmentation for MLaaS is based on component, organisation size, application, and end-user. Cloud APIs currently dominate the market with 35% of sales. The segment of small and medium-sized businesses has generated the highest revenue (66%). The market is segmented by industry, including manufacturing, healthcare, BFSI, transportation, government, and retail, among others. Retail is projected to account for about 38% of the market revenue by 2022, as the growth of e-commerce necessitates greater customer interaction.

North America is anticipated to dominate the MLaaS market, primarily due to its strong infrastructure and the financial ability to acquire an MLaaS solution. Increased defense spending and advancements in telecommunications technology are projected to further increase the market in North America.

The use of big data and machine learning has enabled Airbnb to deliver world-class service to over 80 million visitors worldwide. By analyzing historical data, Airbnb gains a better understanding of customer needs, allowing for tailored service to each visitor. With the use of IoT and automation, companies can ensure proper and safe operation of connected devices as well as the collection of accurate data.

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The report highlights the importance of machine learning in data analytics and its significant role in narrowing the gap between what is beneficial and profitable for businesses and their customers. MLaaS’s scalability and affordability were two major factors driving growth in the market.

Frequently Asked Questions (FAQs) Related to the Above News

What is the projected growth rate for the Machine Learning as a Service market between 2023 and 2032?

The market is expected to grow at a compound annual growth rate (CAGR) of 36.20% between 2023 and 2032.

What is the projected market size for Machine Learning as a Service by 2032?

The projected market size for Machine Learning as a Service by 2032 is USD 304.82 billion.

What is driving the growth of MLaaS?

The expanding use of the Internet of Things (IoT) is driving the growth of MLaaS add-ons, and as more businesses adopt IoT-based technologies and solutions, machine learning technology is becoming increasingly popular for data analytics.

Who currently dominates the MLaaS market in terms of sales?

Cloud APIs currently dominate the MLaaS market with 35% of sales.

Which industry is projected to account for about 38% of the MLaaS market revenue by 2022?

The retail industry is projected to account for about 38% of the MLaaS market revenue by 2022, as the growth of e-commerce necessitates greater customer interaction.

Which region is anticipated to dominate the MLaaS market?

North America is anticipated to dominate the MLaaS market, primarily due to its strong infrastructure and the financial ability to acquire an MLaaS solution.

What is the importance of machine learning in data analytics?

Machine learning plays a significant role in narrowing the gap between what is beneficial and profitable for businesses and their customers in data analytics.

What are the two major factors driving growth in the MLaaS market?

The scalability and affordability of MLaaS are two major factors driving growth in the market.

Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.

Kunal Joshi
Kunal Joshi
Meet Kunal, our insightful writer and manager for the Machine Learning category. Kunal's expertise in machine learning algorithms and applications allows him to provide a deep understanding of this dynamic field. Through his articles, he explores the latest trends, algorithms, and real-world applications of machine learning, making it accessible to all.

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