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The artificial intelligence (AI) chips market size is estimated to grow at a CAGR of 61.51% between 2022 and 2027. The artificial intelligence (AI) chips market size is forecast to increase by USD 2,10,506.47 million. The growth of the market depends on several factors, including increasing adoption of AI chips in data centers, increased focus on developing AI chips for smartphones, and development of AI chips in autonomous vehicles.
This artificial intelligence (AI) chips market report extensively covers market segmentation by product (ASICs, GPUs, CPUs, FPGAs), end-user (media and advertising, BFSI, IT and telecommunication, automotive, and others), and geography (North America, Europe, APAC, South America, and Middle East and Africa). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market data from 2017 to 2021.
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The increasing adoption of AI chips in data centers is notably driving market growth, although factors such as complexities in understanding data may impede market growth. Our researchers analyzed the data with 2022 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
The increasing adoption of AI chips in data centers is notably driving the AI Chips Market growth. Most businesses use data centers, which have thousands of servers, to run all of their online services. These servers are all operated with the aid of a CPU chip. Companies have added additional processors to complement CPUs as the demand for AI has increased. These neural networks use extensive data analysis to aid in task learning. Data centers process a lot of data, so it is important to increase their efficiency and lower power usage to increase uptime and lower operating expenses. As a result, data center providers use AI technology for a variety of purposes including security, server optimization, energy efficiency, and infrastructure management.
AI chips that are specifically made for data center applications are being introduced by chip manufacturers to take advantage of the expanding opportunities presented by AI chips in data centers. For example, NVIDIA launched its BlueField-3 DPU, in 2021, which is specifically designed for AI and accelerated computing within data center infrastructure. Moreover, the incorporation of AI chips by a number of smartphone vendors in their products is one of the main factors contributing to the significant growth of the global market for AI chips. Hence, these factors will drive the growth of the AI chips market during the forecast period.
Increasing investments in AI start-ups is an emerging trend influencing the growth of AI Chips Market. Since AI technology is still in its infant stage, its adoption is expanding rapidly across many industries. As a result, a number of businesses, including start-ups, are entering the market for AI chips to benefit from the rising demand for AI technology. Approximately 70%-75% of businesses are predicted to have adopted AI technology in some capacity within the next 20 years.
Furthermore, due to the enormous market potential for AI chips, major chip manufacturers and venture capitalists have been making sizeable investments in a number of start-up companies for the creation of AI platforms and chipsets. For example, Shanghai-based startup Innostar Semiconductor raised USD 100 million funding in a pre-series A round of funding in 2021. This was led by Shanghai Lianhe Investment and joined by New Alliance as well as new investors Atlas Capital and KQ Capital. The money will be used by the business to create chips for resistive RAM and storage. Hence, these factors will drive the growth of the AI chips market during the forecast period.
Complexities in understanding data are major challenges impeding artificial intelligence chips market growth. Language, context, and reasoning are three obstacles that AI must get past in order to understand data at its best. Currently used AI technologies face challenge processing information in the same way that humans do. This is due to the fact that the majority of information is processed as data rather than as language. Since AI interprets the data as spatial text, contextual issues arise. However, natural language must be processed in the appropriate context, which can only be created when the language is actually understood rather than just being read.
To make decisions, AI technologies must process the data and arrive at the proper understanding. AI technology cannot solve complex problems without the ability to understand. This poses a significant challenge for the market because numerous AI systems must analyze enormous amounts of data that are processed continuously. The market will continue to observe limited growth unless highly efficient AI chips and systems are created to overcome the complexities involved in understanding data. Therefore, such factors will hinder the artificial intelligence chips market growth during the forecast period.
The report includes the adoption lifecycle of the market, covering from the innovator’s stage to the laggard’s stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Global Artificial Intelligence (AI) Chips Market Customer Landscape
Vendors are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Cerebras Systems Inc. - The company primarily focuses on manufacturing computer hardware products and develops AI computing chips. The key offerings of the company include artificial intelligence chips such as WSE-2.
The report also includes detailed analyses of the competitive landscape of the market and information about 15 market vendors, including:
Qualitative and quantitative analysis of vendors has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.
The market share growth by the ASICs segment will be significant during the forecast period. ASICs are specialized, non-configurable chips that are highly customized. ASICs are programmable integrated circuits (ICs) that resemble GPUs in appearance but provide an instruction set and libraries that enable the IC to operate on locally stored data and serve as an accelerator for numerous parallel algorithms. Moreover, ASICs perform faster than GPUs and FPGAs but cannot be reconfigured.
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The ASICs segment was valued at USD 3,206.60 million in 2017 and continued to grow until 2021. The segment is being driven by the use of ASICs in cloud-based data centers. ASIC-based AI chips are expanding their market share as data center applications favor them over GPUs and FPGAs. When compared to GPUs, FPGAs, and CPUs, these chips deliver greater performance and speed. For instance, Google has created an ASIC for deep neural networks called the Tensor Processing Unit (TPU). TPU is a network of hardware and software that can analyze a lot of data to learn specific tasks. Applications like Google Street View and Google Search already make use of it. To effectively manage the data, many data centers are, therefore, integrating TPUs at the back end of servers. These TPUs have a set of instructions that can be used to modify TensorFlow programs and create new algorithms. Tensor Processing Units (TPU) v4 was successfully introduced by Google in May 2021. Compared to TPU v3 hardware, TPU v4 will double TPU hardware performance. On the Google cloud platform, the new version will speed up machine learning training. Microsoft and Amazon.com are also working on TPUs and are planning to implement them in their cloud offerings. Therefore, AI chips based on ASICs are expected to witness significant growth during the forecast period.
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North America is estimated to contribute 37% to the growth of the global market during the forecast period. Technavio’s analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
The increase in investments in autonomous vehicles is the primary factor fueling the North American artificial intelligence chips market growth. Advanced systems like advanced driver assistance systems (ADAS), heads-up displays (HUD), light detection and ranging (LiDAR), and radio detection and ranging (RADAR) are integrated into these vehicles. Electronic components that generate and process a lot of data in real time include sensors, microcontrollers, microprocessors, and other RF components. As a result, chip makers are making significant investments in the R&D of AI chips that are intended specifically for autonomous vehicles.
Some of the top automakers in the world are headquartered in North America, including Ford, GM, Chrysler, and Porsche. The top three countries for producing luxury and sports cars are Canada, the US, and Mexico. The nation has seen significant investment inflows in the form of facility construction and capacity expansion. Factors such as reducing the number of automobile accidents by eliminating manual errors, lowering carbon dioxide emissions, improving battery capacity, and decreasing the consumption of fuel are driving the demand for autonomous cars in the region. Hence, automotive OEMs are increasingly investing in AI technologies and are collaborating with vendors in the market to develop systems that lead to the realize Level 5 autonomous vehicles. Thus, all of the abovementioned factors will boost the artificial intelligence chips market growth during the forecast period.
The COVID-19 pandemic-induced lockdowns led to the temporary closure of end-user industries. Thus, the closure of these industries led to the increasing adoption of remote working, and employees were asked to work from home. Such factors led to the increased adoption of cloud-based analytics platform solutions, such as AI-based CRM, in the retail and e-commerce sector. In addition, the implementation of vaccination drives in the North American countries that led to a decline in the number of COVID-19 cases was also a success due to the existence of artificial intelligence. As the economy reopened and resumed operations, it is expected to significantly drive the demand for artificial intelligence chips, henceforth augmenting the growth of the artificial intelligence chips market in focus during the forecast period.
The artificial intelligence (AI) chips market report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027.
Technavio categorizes the global artificial intelligence (AI) chips market as a part of the global communications equipment market within the overall global information technology sector. The parent global communications equipment market covers manufacturers of enterprise networking products, including LANs, WANs, routers, telephones, switchboards, and exchanges. Our market research report has extensively covered external factors influencing the parent market growth during the forecast period.
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Artificial Intelligence (AI) Chips Market Scope |
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Report Coverage |
Details |
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Page number |
181 |
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Base year |
2022 |
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Historic period |
2017-2021 |
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Forecast period |
2023-2027 |
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Growth momentum & CAGR |
Accelerate at a CAGR of 61.51% |
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Market growth 2023-2027 |
USD 2,10,506.47 million |
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Market structure |
Fragmented |
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YoY growth 2022-2023(%) |
48.54 |
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Regional analysis |
North America, Europe, APAC, South America, and Middle East and Africa |
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Performing market contribution |
North America at 37% |
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Key countries |
US, China, Taiwan, UK, and Germany |
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Competitive landscape |
Leading Vendors, Market Positioning of Vendors, Competitive Strategies, and Industry Risks |
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Key companies profiled |
Advanced Micro Devices Inc., Alphabet Inc., Baidu Inc., Broadcom Inc., Cerebras Systems Inc., Fujitsu Ltd., Graphcore Ltd., Huawei Technologies Co. Ltd., Intel Corp., International Business Machines Corp., MediaTek Inc., Microchip Technology Inc., NVIDIA Corp., NXP Semiconductors NV, Qualcomm Inc., SambaNova Systems Inc., Samsung Electronics Co. Ltd., SenseTime Group Inc., Taiwan Semiconductor Manufacturing Co. Ltd., and Tesla Inc. |
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Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, COVID-19 impact and recovery analysis and future consumer dynamics, and Market condition analysis for the forecast period. |
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Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Product
7 Market Segmentation by End-user
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Trends
11 Vendor Landscape
12 Vendor Analysis
13 Appendix
Research Framework
Technavio presents a detailed picture of the market by way of study, synthesis, and summation of data from multiple sources. The analysts have presented the various facets of the market with a particular focus on identifying the key industry influencers. The data thus presented is comprehensive, reliable, and the result of extensive research, both primary and secondary.
INFORMATION SOURCES
Primary sources
Secondary sources
DATA ANALYSIS
Data Synthesis
Data Validation
REPORT WRITING
Qualitative
Quantitative
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