Farmington, March 01, 2023 (GLOBE NEWSWIRE) -- The Global Machine Learning (ML) Market Size Was Valued At USD 15.44 Billion In 2021. The Market Is Expected To Grow From USD 21.17 Billion In 2022 To USD 209.91 Billion By 2030, Exhibiting A CAGR Of 38.8% During The Forecast Period. The COVID-19 virus has had shocking effects all over the world that have never been seen before. For example, the demand for machine learning technology is higher than projected in all regions compared to before the pandemic. Based on our study, the machine learning (ML) market around the world will grow by 36.1% more in 2020 than it did in 2019.
One of the parts of artificial intelligence is machine learning. (AI). It is a way to look at data that teaches computers to learn quickly from algorithms and data, just like people do. The growth of the market is mostly due to the rising use of artificial intelligence (AI) and machine learning (ML) technology in end-use industries like healthcare, automotive, retail, and manufacturing, among others. Also, in 2020, some countries have put in place quarantine and social separation policies to lessen the effects of the pandemic. ML tools will be used by developers and experts to study how these changes work. For instance, in April 2020, experts at the Massachusetts Institute of Technology made a model based on the COVID-19 pandemic. The model uses machine intelligence algorithms to figure out how the virus will spread and how well quarantine steps will work. This kind of progress is going to make it more important to have smarter machines.
Request Sample Copy of Report “Machine Learning (ML) Market Size, Share & Trends Estimation Report By Component (Solution, and Services), By Enterprise Size (SMEs, and Large Enterprises), By Deployment (Cloud and On-premise), By Industry (Healthcare, Retail, IT and Telecommunication, BFSI, Automotive and Transportation, Advertising and Media, Manufacturing, and Others), By Region, And Segment Forecasts, 2023 - 2030”, published by Contrive Datum Insights.
Recent Developments:
- April 2021: Microsoft Corporation launched open databases for transportation, health and genomics, population and safety, labor and economics, and more to improve the accuracy of ML models using publicly available datasets. This enables companies to leverage Azure Open Datasets along with Azure's ML and data analytics solutions to deliver hyperscale insights to increase MLaaS sales.
- February 2020: Oracle Corporation, a leading technology company, launched the Oracle Cloud Data Science Platform. The newly launched platform will help enterprises collaboratively build, train, manage and deploy ML models to improve the performance of data science programs.
Segment Overview
Component Insights
Parts of the world market are based on solutions and services. In 2021, the answer has the biggest share of the market, and it's likely to stay at the top for a long time. IBM's Watson Machine Learning, Oracle's ML, and Microsoft's Azure are some of the solutions that market players have to give. Researchers and data scientists can use AI and machine learning more quickly with the help of these tools. Machine-learning-as-a-service is expected to become a bigger market trend in the coming years.
Enterprise Size Insights
The world market is split into small and medium-sized enterprises and large enterprises based on the size of the business. Large businesses made up the biggest part of the market in 2021. This is because companies are using artificial intelligence and data science technology more and more to get precise insights into how their businesses work. Using deep learning, machine learning, and decision optimization, big companies are trying to make their services better.
Deployment Insights
Based on how they are used, the market has been split into two groups: the cloud and on-premise. Market players can set up machine intelligence options in the cloud or on-premise. Alphabet, Inc. makes Google Cloud, for example. There are many tools for machine learning and artificial intelligence in the Google cloud. (AI). In the same way, businesses can use on-premise deployments with BigML if they want to set up, maintain, and control their installations within the business.
End-user Insights
Industries that deal with a lot of data use ML technology to get real-time information from the data. Real-time insights give companies an edge over their competitors and help them work better.
Before COVID-19, the rise of wearable devices and sensors that can check a patient's health in real time has made machine intelligence applications more important in the health care business. With the help of technology, doctors can find trends and look at data, which makes evaluation and treatment better. But the spread of the new Coronavirus has caused the industry as a whole to use machine learning technology more.
Regional Outlook:
North America had the biggest share of the market in 2020. Big companies like IBM, Amazon.com, and Oracle that spend a lot of money on research and development make the market in the area bigger. Because of high investments and a well-developed IT infrastructure, the market is expected to grow in North America. For example, the U.S. Defense Advanced Research Projects Agency (DARPA) spent $2 billion on creating AI technologies like machine learning.
Europe is likely to grow strongly on the world market. This is because ML technology is being used more and more in new countries with a lot of skilled workers, such as the U.K. and Germany. The regional market is also being affected by how easy it is for people to get services and items that use AI. In June 2018, the European Union suggested a program called "Digital Europe" that would run from 2021 to 2027 and cost 10.4 billion USD. The goal of the program is to make AI better and find more ways for people and businesses to use it. These kinds of active steps are likely to create new market possibilities and help the European market grow.
Over the next few years, the economies of Asia and the Pacific should grow faster. China, India, and the Philippines, which are all developing economies in the region, have a strong startup environment that is helped by a growing number of skilled workers. This is good for the growth of the markets in the area as a whole. Also, the Japanese government does a lot to get people all over the country interested in artificial intelligence. This is happening at the same time that machine learning services are getting more popular, which is a big part of what drives
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Scope of Report:
| Report Attributes | Details |
| Growth Rate | CAGR of 38.8% from 2023 to 2030. |
| Revenue Forecast by 2030 | USD 209.91 Billion |
| By Component | Solution, Services, Others |
| By Enterprise Size | SMEs, Large Enterprises, Others |
| By Deployment | Cloud, On-premise, Others |
| By End-user | Healthcare, Retail, IT and Telecommunication, Banking, Financial Services and Insurance (BFSI), Automotive & Transportation, Advertising & Media, Manufacturing, Others |
| By Companies | IBM Corporation (New York, U.S.), SAP SE (Walldorf, Germany), Oracle Corporation (Texas, U.S.), Hewlett Packard Enterprise Company (Texas, U.S.), Microsoft Corporation (Washington, U.S.), Amazon, Inc. (Washington, U.S.), Intel Corporation (California, U.S.), Fair Isaac Corporation (California, U.S.), SAS Institute Inc. (North Carolina, U.S.), BigML, Inc. (Oregon, U.S.) |
| Regions and Countries Covered |
|
| Base Year | 2022 |
| Historical Year | 2017 to 2022 |
| Forecast Year | 2023 to 2030 |
Latest Trends:
Integration of machine intelligence with solutions that are driven by data is a market trend that will grow.
Retail data has grown by leaps and bounds in the past few years. Many e-commerce companies, like Amazon, Alibaba, and eBay, use advanced data analytics technologies to boost sales and make customers happier. As study into speech and voice recognition technologies has progressed, ML-based cognitive speech coding methods have been created.
Driving Factors:
Because there are more and more uses in healthcare, the market is expected to grow.
ML technology is already helping in the healthcare area in a number of ways. This technology can be used to look at millions of different data points and guess what will happen in the health care field. It can also be used to quickly give risk scores and figure out how to use resources in the best way.
One of the most important ways this technology is used in healthcare is to find and identify diseases and conditions that can be hard to see. This can be anything from cancers that are hard to find early to other diseases that run in families. IBM Watson Genomics is a well-known example of how cognitive computing and genome-based analysis of tumors can be used together to help find cancer. Berg is a well-known name in the field of biopharmaceuticals. He uses AI to make medicines to help diseases like cancer.
Restraining Factors:
Technical troubles and a lack of accuracy will slow the growth of the market.
There are many good things about the ML tool that help the market grow. But the platform is missing some factors that could slow the market's growth. One of the main things slowing down the market is that these programs aren't always right and aren't always well-made. Businesses that make things and use big data and machine learning need to be very precise. If the formula isn't quite right, the wrong things could be made. So, a person must work with the system until all of the settings are set and the margin of error is close to or equal to zero. So, this may make the market grow less quickly.
Key Segments Covered:
Top Market Players:
IBM Corporation (New York, U.S.), SAP SE (Walldorf, Germany), Oracle Corporation (Texas, U.S.), Hewlett Packard Enterprise Company (Texas, U.S.), Microsoft Corporation (Washington, U.S.), Amazon, Inc. (Washington, U.S.), Intel Corporation (California, U.S.), Fair Isaac Corporation (California, U.S.), SAS Institute Inc. (North Carolina, U.S.), BigML, Inc. (Oregon, U.S.), and others.
By Component
- Solution
- Services
- Others
By Enterprise Size
- SMEs
- Large Enterprises
- Others
By Deployment
- Cloud
- On-premise
- Others
By End-user
- Healthcare
- Retail
- IT and Telecommunication
- Banking, Financial Services and Insurance (BFSI)
- Automotive & Transportation
- Advertising & Media
- Manufacturing
- Others
Regions and Countries Covered
- North America: (US, Canada, Mexico, Rest of North America)
- Europe: (Germany, France, Italy, Spain, UK, Nordic Countries, Benelux Union, Rest of Europe)
- Asia-Pacific: (Japan, China, India, Australia, South Korea, Southeast Asia, Rest of Asia-Pacific)
- The Middle East & Africa: (Saudi Arabia, UAE, Egypt, South Africa, Rest of the Middle East & Africa)
- Latin America: (Brazil, Argentina, Rest of Latin America)
- Rest Of the World
Check out more related studies published by Contrive Datum Insights:
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