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Machine Learning Market Segmentation: by Solution Type (Software, Hardware and Services); By Application (Advertising & Media, BFSI, Government, Healthcare, Retail, Telecom, Utilities, and Manufacturing); and Region -Analysis of Market Size, Share & Trends for 2016 - 2020 and Forecasts to 2030
Machine Learning market to surpass USD 121.23 Billion by 2030; this is valued at 9.25 billion in 2020 at a compound annual growth rate of 37.5%.
Machine learning is a subset of Artificial intelligence (AI) that enables computers to learn without being carefully programmed. It primarily focuses on promoting computer programs that can be changed when new data is released. It assists the computer analyses and gets meaningful information without being programmed acutely for them. In the modern safety and security technology environment, it has numerous functions such as face detection, face recognition, picture classification, voice recognition, antivirus, Google, and spam filtering, genetic engineering, signal diagnostics, and weather prediction.
Machine Learning market to surpass USD 121.23 Billion by 2030; this is valued at 9.25 billion in 2020 at a compound annual growth rate of 37.5%. Organizations around the world implement machine learning services that deliver better client experience, ROI and create a competitive advantage in the fields of business. In addition, machine learning applications are anticipated to rise progressively in various end user industries in the near term. Progresses in technology and data generation are some of the main drivers in the market.
Source: Fatpos Global
Global Machine Learning market has been segmented based on technology, product offering, and application. It has been further segmented based on region into North America, Europe, Asia-Pacific, Mid East, and Africa.
Healthcare segment is expected to dominate the market with a growing CAGR
Global Managed Security Services market is segmented by application into: Advertising & media, BFSI, Government, Healthcare, Retail, Telecom, Utilities, and Manufacturing. This is because this technology has been increasingly adopted in new areas of healthcare. This technology is used for example to estimate the probability of a person's death. The use of machine learning to improve diagnostic knowledge and use it for disease prevention moves the medical field from reactive to proactive, thus augmenting the segment’s growth.
Source: Fatpos Global
In 2019 the Hardware, solution accounted for XX% of the total Machine Learning market
Global Machine Learning market is segmented by solution type: Software, hardware, and services. During the projected timeframe, the hardware industry is anticipated to record the highest CAGR. This can be driven by the increasing use of machine learning hardware. The development of AI and ML custom silicon chips drives hardware implementation. Departments such as Samba Nova Systems are expected to develop more powerful processing systems to further fuel the market.
Collaborative Policies adopted by many companies
The competitive landscape in the market for Machine learning shows a tendency towards companies that adopt strategies such as partnerships, cooperation, and joint ventures as well as launching and developing of their products. With the growing global market growth, companies in this sector are being forced to develop collaborative policies to sustain themselves in the highly competitive market.
Technological advancement and implementation by end user
Organizations around the world implement machine learning services that deliver better client experience, ROI and create a competitive advantage in the fields of business. In addition, machine learning applications are anticipated to rise progressively in various end-user industries in the near term. Progresses in technology and data generation are some of the main drivers in the market.
Insufficient Knowledge
One reason for the slow adoption of machine learning in the sector is a lack of necessary knowledge about ML technology among decision-makers. Many companies simply don’t have sufficient technical background to understand how their business can benefit from AI adoption. Conservative stakeholders prefer to stick with time-proven methods and tools rather than risk trying something new.
Fewer number of trained professionals
Machine learning is still a new technology, and skilled professionals are few. There are many experts with a thorough theoretical insight into the topic. Yet it is incredibly difficult to find professionals who are able to develop reliable, functional ML applications.
The largest share of the market in 2019 was held by America which accounting for over XX% share in the world.
The expansion of the marketing industries has led to the development of increasing e-commerce, online streaming and spread of internet. Marketers now seek more advanced and cutting-edge marketing solutions for a wide range and ever-growing customer bases. This led to the implementation of Machine learning-compatible marketing solutions. In security, organizations and governments focus on comprehensive defense infrastructure with rising occurrences of cyber-attacks and widespread cyberwar in the region. APAC is considered the largest market for industrial robots, particularly China, Japan and South Korea.
Asia Pacific: China, Japan, India, and Rest of Asia Pacific
Europe: Germany, the UK, France, and Rest of Europe
North America: The US, Mexico, and Canada
Latin America: Brazil and Rest of Latin America
Middle East & Africa: GCC Countries and Rest of Middle East & Africa
Source: Fatpos Global
Global Machine Learning market is further segmented by region into:
In response to a disease outbreak of COVID-19 and to continue expanding problems, artificial intelligence (AI), Machine Learning (ML) virtual reality (VR) and augmented reality (AR) technologies are expected to contribute significantly. The present situation due to the epidemic will motivate pharmaceutical providers and health centers, as the key technologies for different initiatives, to strengthen their R&D investments in ML. The cost-efficiency pressures are anticipated in the insurance sector. In the course of the renewal process, the use of AI can drastically reduce operating cost and, at the same time, can improve customer satisfaction. ML, VR / AR can support Digital-learning, which will be increasingly demanded by the shutdown of many schools and institutions. VR / AR can also provide offline assistance as they help minimize potential journeys and can prove to be a worthwhile solution.
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