Machine Learning Market size is anticipated to surpass USD 750 billion by the end of 2035, growing at a CAGR of 37% during the forecast period i.e. 2023-2035. In the year 2022, the industry size of machine learning was USD 24 billion. The growth of this sector can be attributed to the increasing demand for machine learning in the healthcare sector. In the healthcare domain, this technology analyses all possible data and then anticipates outcomes along with this it also offers risk scores and correct resource allocations. Another significant application of this technology in this sector is that it helps to identify diseases which is at times difficult to identify. Such as an algorithm developed by Google's DeepMind division can identify retinal images of eye disorders including diabetic retinopathy.
In addition to this, machine learning technology is highly being used in the banking and finance sector for improvement of fraud detection, risk management, and reduce cyber threats in banks. Banks and other financial institutions utilize machine learning algorithms to analyze enormous amounts of data in actual time and more accurately identify fraud and other risks. The growth of the financial services sector is anticipated to fuel the demand for machine learning technologies in the approaching years. In all, 72% of the companies that answered the study stated that they were utilizing or creating ML applications. These apps are being used in more and more different business sectors.
Growth Drivers
Challenges
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Base Year |
2022 |
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Forecast Year |
2023 – 2035 |
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CAGR |
~37% |
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Base Year Market Size (2022) |
~USD 24 billion |
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Forecast Year Market Size (2035) |
~USD 750 billion |
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Regional Scope |
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Deployment (Cloud, On-premises)
The cloud segment is predicted to hold 55% share of the global machine learning market by the end of 2035. One of the major benefits that have resulted from adopting cloud delivery models for learning software solutions and services is flexibility, automated software updates, disaster recovery using cloud backup systems, enhanced collaboration, document version controls, and data loss prevention with robust cloud storage facilities.
Enterprise Type (SMEs, Large Enterprise)
Machine learning market from the large enterprise segment is set to grow substantially with a share of 54% in the time period between 2023 – 2035. It is becoming more and more common to use AI as a service and data science for the quantitative analysis of enterprises that are expected to drive segment revenue growth. For the provision of efficient market services, large firms are using machine learning approaches. Large enterprises can use machine learning without major infrastructure investments with services like Google Cloud AI Platform, Amazon Web Services (AWS), and Microsoft Azure Machine Learning providing pre-built models, distributed training capabilities, and infrastructure management.
Our in-depth analysis of the global market includes the following segments:
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Enterprise Type |
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Deployment |
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End User |
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North American Market Forecast
The machine learning market in the North America region is expected to account for a share of 35% in the time period between 2023 – 2035. North America is expected to be the leading market in machine learning, owing to its increasing application of advanced technologies such as artificial intelligence and big data analytics. The North American big data analytics sector is set to reach USD 169.91 billion by 2028. The US is home to a number of the biggest technology firms, such as Google, Microsoft, and IBM, which are making significant investments in machine learning. In addition, it is expected that market expansion will be further accelerated by the presence of many new companies in this area.
APAC Market Statistics
In the Asia Pacific machine learning market is expected to grow substantially during the projection period. In particular, due to growing demand in emerging countries like China and India for machine learning solutions, the region's market continues to grow. In these countries, there is substantial growth in the use of technology and digitalization that will lead to increased demand for machine learning solutions.
Author Credits: Abhishek Verma, Hetal Singh
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