Market Overview:
The global machine learning chip market size reached US$ 9.7 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 62.1 Billion by 2032, exhibiting a growth rate (CAGR) of 22.4% during 2024-2032. The rapid emergence of quantum computing, increasing demand for efficient systems to solve computational problems, and rising development of smart cities and smart homes represent some of the key factors driving the market.
Report Attribute
|
Key Statistics
|
Base Year
|
2023
|
Forecast Years
|
2024-2032
|
Historical Years
|
2018-2023
|
Market Size in 2023
|
US$ 9.7 Billion |
Market Forecast in 2032
|
US$ 62.1 Billion |
Market Growth Rate 2024-2032 |
22.4% |
Machine learning (ML) chip comprises artificial intelligence (AI) technology that that is designed to support deep learning-based applications. It involves various technologies, such as system-on-chip (SoC), multi-chip module, and system-in-package, and its hardware infrastructure includes computing, storing, and networking. It is installed in a system to enhance intellectual property cores and improve design and tool flows. It is cost-effective and assists in preventing errors in a workflow, and efficiently saves a huge amount of data. It offers high speed, increases efficiency, and consumes less energy as compared to larger transistors. Besides this, it aids in improving performance, power, optimization, and analytics. As a result, the ML chip is widely employed in the automotive, healthcare, retail, media and advertising, information technology (IT) and telecommunication, and banking, financial services, and insurance (BFSI) industries across the globe.
Machine Learning Chip Market Trends:
At present, the rising trend of digitalization and expansion of the IT and telecommunication industry around the world represent one of the key factors supporting the growth of the market. In addition, the increasing number of cyber-attacks encourages businesses to utilize database management and fraud detection systems, which is propelling the growth of the market. Apart from this, the rising demand for ML chips due to the development of smart cities and smart homes across the globe is offering lucrative growth opportunities to industry investors. Moreover, the increasing emergence of quantum computing, along with the implementation of ML chips in robotics to reduce human intervention and errors around the world, is positively influencing the market. Besides this, the growing adoption of ML chips on account of the escalating demand for efficient systems to solve mathematical and computational problems is offering a positive market outlook. Additionally, the rising integration of big data analytics and cloud computing to provide enhanced services among numerous industries across the globe is contributing to the growth of the market. This, coupled with the increasing utilization of ML chips for real-time consumer behavior insights, is impelling the growth of the market. Furthermore, the rising preference toward GPUs from CPUs to perform several complex tasks in the gaming industry is strengthening the market growth.
Key Market Segmentation:
IMARC Group provides an analysis of the key trends in each sub-segment of the global machine learning chip market report, along with forecasts at the global, regional and country level from 2024-2032. Our report has categorized the market based on technology, chip type and industry vertical.
Technology Insights:
- System-on-Chip (SoC)
- System-in-Package
- Multi-chip Module
- Others
The report has provided a detailed breakup and analysis of the machine learning chip market based on the technology. This includes system-on-chip (SoC), system-in-package, multi-chip module, and others. According to the report, system-on-chip (SoC) represented the largest segment.
Chip Type Insights:
A detailed breakup and analysis of the machine learning chip market based on the chip type has also been provided in the report. This includes GPU, ASIC, FPGA, CPU, and others. According to the report, GPU accounted for the largest market share.
Industry Vertical Insights:
- BFSI
- IT and Telecom
- Media and Advertising
- Retail
- Healthcare
- Automotive
- Others
A detailed breakup and analysis of the machine learning chip market based on the industry vertical has also been provided in the report. This includes BFSI, IT and telecom, media and advertising, retail, healthcare, automotive, and others. According to the report, BFSI accounted for the largest market share.
Regional Insights:
- North America
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia
- Indonesia
- Others
- Europe
- Germany
- France
- United Kingdom
- Italy
- Spain
- Russia
- Others
- Latin America
- Middle East and Africa
The report has also provided a comprehensive analysis of all the major regional markets, which include North America (the United States and Canada); Asia Pacific (China, Japan, India, South Korea, Australia, Indonesia, and others); Europe (Germany, France, the United Kingdom, Italy, Spain, Russia, and others); Latin America (Brazil, Mexico, and others); and the Middle East and Africa. According to the report, North America (the United States and Canada) was the largest market for machine learning chip. Some of the factors driving the North America machine learning chip market included the growing concern about security of critical infrastructure, increasing demand for quantum computing, rising utilization in the IT industry, etc.
Competitive Landscape:
The report has also provided a comprehensive analysis of the competitive landscape in the global machine learning chip market. Competitive analysis such as market structure, market share by key players, player positioning, top winning strategies, competitive dashboard, and company evaluation quadrant has been covered in the report. Also, detailed profiles of all major companies have been provided. Some of the companies covered include Advanced Micro Devices Inc., Amazon Web Services Inc. (Amazon.com Inc.), Cerebras Inc., Google LLC, Graphcore, Intel Corporation, International Business Machines Corporation, NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics Co. Ltd., Taiwan Semiconductor Manufacturing Company Limited., etc. Kindly note that this only represents a partial list of companies, and the complete list has been provided in the report.
Report Coverage:
Report Features |
Details |
Base Year of the Analysis |
2023 |
Historical Period |
2018-2023 |
Forecast Period |
2024-2032 |
Units |
US$ Billion |
Segment Coverage |
Technology, Chip Type, Industry Vertical, Region |
Region Covered |
Asia Pacific, Europe, North America, Latin America, Middle East and Africa |
Countries Covered |
United States, Canada, Germany, France, United Kingdom, Italy, Spain, Russia, China, Japan, India, South Korea, Australia, Indonesia, Brazil, Mexico |
Companies Covered |
Advanced Micro Devices Inc., Amazon Web Services Inc. (Amazon.com Inc.), Cerebras Inc., Google LLC, Graphcore, Intel Corporation, International Business Machines Corporation, NVIDIA Corporation, Qualcomm Incorporated, Samsung Electronics Co. Ltd. and Taiwan Semiconductor Manufacturing Company Limited |
Customization Scope |
10% Free Customization |
Report Price and Purchase Option |
Single User License: US$ 3899
Five User License: US$ 4899
Corporate License: US$ 5899 |
Post-Sale Analyst Support |
10-12 Weeks |
Delivery Format |
PDF and Excel through Email (We can also provide the editable version of the report in PPT/Word format on special request) |
Key Benefits for Stakeholders:
- IMARC’s report offers a comprehensive quantitative analysis of various market segments, historical and current market trends, market forecasts, and dynamics of the machine learning chip market from 2018-2032.
- The research study provides the latest information on the market drivers, challenges, and opportunities in the global machine learning chip market.
- The study maps the leading, as well as the fastest-growing, regional markets. It further enables stakeholders to identify the key country-level markets within each region.
- Porter's five forces analysis assist stakeholders in assessing the impact of new entrants, competitive rivalry, supplier power, buyer power, and the threat of substitution. It helps stakeholders to analyze the level of competition within the machine learning chip industry and its attractiveness.
- Competitive landscape allows stakeholders to understand their competitive environment and provides an insight into the current positions of key players in the market.