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Global Artificial Intelligence (AI) Hardware Market Research Report - Segmentation By Size By Type (Processors, Memory and Network), and Geography – Forecast to 2027

Published: January, 2022
ID: 10231
Pages: 150
Formats: report pdf report excel report power bi report ppt

Artificial Intelligence (AI) Hardware Market Size (2022 - 2027)

The global artificial intelligence (AI) hardware market is likely to record a CAGR of 26% during the outlook period (2022 - 2027).

AI Hardware stems from the need to create perfect hardware to accelerate artificial intelligence applications. The physical infrastructure consists of three main parts, namely computing, storage and networking. In recent years, the computer has made the most significant progress. The other two areas, storage and networking, which are not as advanced, have yet to see any major innovations in AI applications.

The continued increase in the number of Internet users and the advent of Industry 4.0 have intensified the market for artificial intelligence (AI) hardware. The growth of big data and the advancement of computer applications and software, along with significant improvements in the business aspects of artificial intelligence, are driving the growth of the industry. Technological advancements due to the increasing adoption of AI and robotics in end-use industries such as IT, automotive, healthcare and manufacturing will drive demand for the forecast period. The recent advancements in the smartphone industry and the rising application of semiconductors have supported the call for AI hardware market. Also, machine learning and deep learning will act as crucial aspects for the development of the global artificial intelligence (AI) hardware market.

The demand for AI hardware in the defense sector is driving the market. The Air Force needs unconventional computer architectures for pattern recognition, event reasoning, decision making, adaptive learning, and autonomous tasks in fuel-efficient manned and unmanned aircraft. According to the researchers, the main area of interest is neuromorphic computing or brain-inspired computing which involves more advanced processors than more traditional Von Neumann architectures. This type of design could lead to unconventional circuits based on emerging nanotechnologies, such as memristors and nano-photonics.

Market growth and trends

The automotive sector will experience significant growth in AI hardware market in future

  • The automotive industry is going through a decade of rapid change, as vehicles become more connected, new powertrains, such as electric motors, reach the general public and the level of autonomy of vehicles increases. Many automakers have already responded by announcing pilot projects in the field of autonomous driving, which may require artificial intelligence hardware.
  • Additionally, Xpeng P7 is the first range-ready production L3 vehicle on the Chinese market, powered by NVIDIA's DRIVE AGX Xavier system-on-chip, delivering 30 TOPS (trillion operations per second) performance while consuming. only 30 watts of power. Its autonomous driving system, XPILOT3.0, is designed for the tough roads of China.

Market Drivers and Limitations

The main drivers expected to drive the Global AI hardware market are the demand for an increasingly large and complex dataset, adoption of AI to improve consumer services and reduce operating costs, rising number of AI applications and enhanced computing power and affordable hardware costs.

The continued increase in the number of Internet users around the world is expected to further strengthen the overall IoT market due to the growth of Internet-enabled smart devices such as Radio Frequency Identification (RFID) devices, card readers, barcodes and mobile computers.

With AI technology still in the early stages of your product lifecycle, your workforce with deep knowledge of this technology is limited. Therefore, the impact of this limiting factor is likely to remain high during the early years of the forecast period.

The lack of standards and protocols further hinders the growth of the global AI hardware market. New metrics and standards must be developed to implement safe, usable, reliable and interoperable artificial intelligence technologies that make decisions based on data-driven models, such as machine learning. This can be done by working with stakeholders to develop AI assessment methodologies, best practices, and standard test/work protocols.




Market Size Available

2020 – 2026

Base Year


Forecast Period

2022 - 2027



Segments Covered

By Type, and Region

Various Analyses Covered

Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities

Regions Covered

North America, Europe, APAC, Latin America, Middle East & Africa

Market Leaders Profiled

Nvidia (United States), Intel (United States), Xilink (United States), Samsung Electronics (South Korea), Micron Technology (United States), Qualcomm Technologies (United States), IBM (United States), Google (United States), Microsoft (United States) and Amazon Web Services (United States) and Others.


Artificial Intelligence (AI) Hardware Market segmentation

Artificial Intelligence (AI) Hardware Market - By Type:

  • Processors
  • Memory
  • Network

The processor segment is estimated to experience the highest CAGR for the forecast period. The factors can be attributed to the increased speed, which enables fast data transmission. High parallel processing capabilities and improved computing power have driven acceptance into the processor segment.

Regional Analysis

On the basis of region, the global AI hardware market is divided into:

  1. North America
  2. Europe
  3. Asia-Pacific
  4. Rest of the world

North America is likely to experience the highest growth rate during the outlook period. The growing adoption of cloud services in developed countries such as the United States and Canada, along with a strong technical adoption base and the availability of government funds will drive the market in this area.

Key market players

Nvidia (United States), Intel (United States), Xilink (United States), Samsung Electronics (South Korea), Micron Technology (United States), Qualcomm Technologies (United States), IBM (United States), Google (United States), Microsoft (United States) and Amazon Web Services (United States).

Impact of Covid-19 on Artificial Intelligence Hardware Market

The impact of COVID-19 is affecting market growth due to the massive supply chain slowdown. In the chip business, revenues fell nearly 12% globally during the pandemic, dropping nearly $ 57 billion from 2018, which could ultimately affect IT processors. Intel saw zero growth in its core microprocessor segment in 2019, while logic chip sales increased 7%.

Also, the market growth can be seen in healthcare to provide processors which help doctors. In April 2020, AMD announced a COVID-19 HPC (High Performance Computing) fund to provide research institutions with computing resources to accelerate medical research into COVID-19 and other diseases. For medical customers, AMD prioritizes and expedites product shipments, including AMD integrated processors used in ventilators and respirators.

Recent Developments:

  • In December 2017, NVIDIA introduced TITAN V, the world's most powerful PC GPU, powered by the world's most advanced GPU architecture, NVIDIA Volta. TITAN V excels in computer processing for scientific simulation. Its 21.1 billion transistors deliver 110 teraflops of raw power, 9 times more than its predecessor and extremely energy efficient.
  • In December 2017, IBM presented its next generation Power Systems servers with its new POWER9 processor. Designed specifically for compute-intensive artificial intelligence workloads, the new POWER9 systems are capable of improving training times for deep learning executives by nearly 4x, enabling organizations to build more applications precise and faster.
  • In December 2017, Qualcomm Technologies introduced the new Qualcomm Snapdragon 845 mobile platform. Snapdragon 845 uses cutting-edge computing experience Qualcomm Technologies to create a platform for alluring multimedia experiences, which comprises extended reality (XR), on-device AI and lightning-fast connectivity.
  • In October 2017, Intel is expected to deliver the industry's first silicon for neural network processing, Intel Nervana Neural Network Processor (NNP), before the end of 2017. Intel collaborated with Facebook to bring technical knowledge from Facebook to develop this new AI material. Intel Nervana NNP promises to revolutionize AI computing in all industries. With Intel Nervana technology, end-user companies will be able to develop entirely new classes of artificial intelligence applications that maximize the amount of data processed and enable customers to find better information, thereby transforming their businesses.

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