Global Artificial Intelligence Chipset Market Size is valued at USD 122.5 Billion in 2024 and is predicted to reach USD 790.44 Billion by the year 2034 at a 20.7% CAGR during the forecast period for 2025-2034.
The most widely used technology in recent years has been artificial intelligence, which is expected to hold great promise for emerging smart devices. It has been used increasingly in many facets of society and the economy. Finance, education, healthcare, logistics, and transportation are just a few of the industries where it has been extensively used since it makes it easier for services and products to be intelligent.
The physical foundation for producing applications with AI is provided by chipsets, thus including them in the development of AI apps is crucial. Autonomous vehicles, intelligent robotics, smart healthcare, smart homes, smart cities, smart finance, intelligent security, intelligent hardware, self-service stores, and intelligent education are some of the application technologies for AI.
AI technology has several facets because it is woven into applications, chipset types, computing technologies, and algorithm mechanisms. The fundamental uses of artificial intelligence are in the processing of image/video, sound and speech, natural language, device control, and large-scale computation. These edge applications can be run more easily thanks to the chipsets.
The development of semiconductor nanowire laser technology, 3D technology, and the expanding use of neural networks & deep learning technologies are key market drivers for artificial intelligence (AI) chipsets. Additionally, the increasing number of projects worldwide for smart homes, buildings, and cities is projected to increase demand for chipsets. The development of cutting-edge artificial intelligence chipsets for many applications is the focus of major players.
The Artificial Intelligence Chipset market is segmented by offering, technology, memory, network, function, and end user. Based on offering, the market is segmented GPU, CPU, FPGA, NPU, TPU, Dojo & FSD, trainium & inferentia, Athena ASIC, T-head, MTIA, LPU, Other ASIC. As per the memory segment is classified into DDR and HBM. The Network segment is divided into, NIC/Network Adapters, Interconnects. Memory is sub segmented into DRAM, and it is sub segmented into HBM and DDR. NIC/Network is sub segmented into adapters and InfiniBand. By Technology market is segmented into Generative AI, machine learning, natural language processing, computer vision. Generative AI is sub segmented into rule based models, statistical models, deep learning, generative adversarial networks (GANs), autoencoders, convolutional neural networks (CNNs), and transformer models. By function market is segmented into training and inference. By End-User market is segmented into consumer, data center, government organizations. Data Center is sub segmented into CSP and enterprises. Enterprises is sub segmented into healthcare, BFSI, automotive, retail & e-commerce, media & entertainment, others.
The GPU segment is set to lead the market, driven by its ability to handle intensive AI workloads through complex matrix operations. Key players like NVIDIA, Intel, and AMD continue to launch advanced GPUs for both data centers and edge applications. In November 2023, NVIDIA released the HGX H200 platform featuring the H200 Tensor Core GPU with 141 GB of HBM3e memory and 4.8 TB/s speed. Cloud giants such as AWS, Google Cloud, Microsoft Azure, and Oracle are adopting these GPUs, underscoring their critical role in AI and cloud infrastructure. Growing GPU capabilities will further accelerate market growth.
Generative AI is driving rapid growth in the Artificial Intelligence Chipset market, fueled by soaring demand for models that generate high-quality text, images, and code. As GenAI models grow increasingly complex, data center providers require Artificial Intelligence Chipsets with greater processing power and memory bandwidth. Enterprises across sectors like retail & e-commerce, BFSI, healthcare, and media & entertainment are rapidly adopting GenAI for dynamic use cases such as natural language processing, content creation, and automated design. This widespread adoption is accelerating the demand for high-performance Artificial Intelligence Chipsets, propelling strong market growth.
During the anticipated period, North America is anticipated to lead the market in terms of revenue share in the global market. The availability of established IT infrastructure and rising government R&D expenditures will probably drive market expansion in North America. The demand for AI chipsets is also increasing in the US and Canada due to the presence of significant important players like NVIDIA Corporation, Intel Corporation, Google LLC, and others. These players are concentrating on releasing cutting-edge AI chipsets to expand their product line.
The region with the fastest rate of growth is Asia Pacific in the anticipated time frame. The expansion of this industry is fueled by the region's developing economies, like South Korea, India, and others, which have strong startup ecosystems and an expanding pool of skilled labour. A council on AI ethics has also been established by the Singaporean government as part of the country's AI strategy, which calls for the deployment of AI applications across multiple industries in 2018. Due to the presence of a sizable number of AI solution providers, Europe is predicted to experience rapid growth.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 122.5 Bn |
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Revenue Forecast In 2034 |
USD 790.44 Bn |
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Growth Rate CAGR |
CAGR of 20.7% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
Chipset Type Analysis, Function Analysis, and Industry Analysis |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; Germany; China; Japan; Brazil; Mexico; The UK; France; Italy; Spain; Japan; India; South Korea; South East Asia |
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Competitive Landscape |
Intel Corporation (US), Nvidia Corporation (US), Qualcomm Technologies Inc. (US), Micron Technology, Inc. (US), Advanced Micro Devices, Inc. (US), Samsung Electronics Co., Ltd. (South Korea), Apple Inc. (US), IBM (US), Alphabet, Inc. (US), Huawei Technologies (China). |
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Customization Scope |
Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing and Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions
Chapter 2. Executive Summary
Chapter 3. Global AI Chip Market Snapshot
Chapter 4. Global AI Chip Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis
Chapter 5. Market Segmentation 1: by Offering Estimates & Trend Analysis
5.1. by Offering & Market Share, 2024 & 2034
5.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Offering:
5.2.1. GPU
5.2.2. CPU
5.2.3. FPGA
5.2.4. NPU
5.2.5. TPU
5.2.6. Dojo & FSD
5.2.7. Trainium & Inferentia
5.2.8. Athena ASIC
5.2.9. T-head
5.2.10. MTIA
5.2.11. LPU
5.2.12. Other ASIC
Chapter 6. Market Segmentation 2: by Memory Estimates & Trend Analysis
6.1. by Memory & Market Share, 2024 & 2034
6.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Memory:
6.2.1. HBM
6.2.2. DDR
Chapter 7. Market Segmentation 3: by Network Estimates & Trend Analysis
7.1. by Network & Market Share, 2024 & 2034
7.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Network:
7.2.1. NIC/Network Adapters
7.2.1.1. Infiniband
7.2.1.2. Ethernet
7.2.2. Interconnects
Chapter 8. Market Segmentation 4: by Technology Estimates & Trend Analysis
8.1. by Technology & Market Share, 2024 & 2034
8.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Technology:
8.2.1. Generative AI
8.2.1.1. Rule Based Models
8.2.1.2. Statistical Models
8.2.1.3. Deep Learning
8.2.1.4. Generative Adversarial Networks (GANs)
8.2.1.5. Autoencoders
8.2.1.6. Convolutional Neural Networks (CNNs)
8.2.1.7. Transformer Models
8.2.2. Machine Learning
8.2.3. Natural Language Processing
8.2.4. Computer Vision
Chapter 9. Market Segmentation 5: by Function Estimates & Trend Analysis
9.1. by Function & Market Share, 2024 & 2034
9.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by Function:
9.2.1. Training
9.2.2. Inference
Chapter 10. Market Segmentation 6: by End User Estimates & Trend Analysis
10.1. by End User & Market Share, 2024 & 2034
10.2. Market Size (Value (US$ Mn) & Volume (Unit)) & Forecasts and Trend Analyses, 2021 to 2034 for the following by End User:
10.2.1. Consumer
10.2.2. Data Center
10.2.2.1. CSP
10.2.2.2. Enterprises
10.2.2.2.1. Healthcare
10.2.2.2.2. BFSI
10.2.2.2.3. Automotive
10.2.2.2.4. Retail & E-Commerce
10.2.2.2.5. Media & Entertainment
10.2.2.2.6. Others
10.2.3. Government Organizations
Chapter 11. AI Chip Market Segmentation 7: Regional Estimates & Trend Analysis
11.1. North America
11.1.1. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.1.2. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.1.3. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.1.4. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.1.5. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.1.6. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.1.7. North America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.2. Europe
11.2.1. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.2.2. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.2.3. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.2.4. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.2.5. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.2.6. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.2.7. Europe AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.3. Asia Pacific
11.3.1. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.3.2. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.3.3. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.3.4. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.3.5. Asia-Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.3.6. Asia-Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.3.7. Asia Pacific AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.4. Latin America
11.4.1. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.4.2. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.4.3. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.4.4. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.4.5. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.4.6. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.4.7. Latin America AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
11.5. Middle East & Africa
11.5.1. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Offering, 2021-2034
11.5.2. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Memory, 2021-2034
11.5.3. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Network, 2021-2034
11.5.4. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Technology, 2021-2034
11.5.5. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by Function, 2021-2034
11.5.6. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by End User, 2021-2034
11.5.7. Middle East & Africa AI Chip Market Revenue (US$ Million) & Volume (Unit) Estimates and Forecasts by country, 2021-2034
Chapter 12. Competitive Landscape
12.1. Major Mergers and Acquisitions/Strategic Alliances
12.2. Company Profiles
12.2.1. Advanced Micro Devices, Inc. (AMD)
12.2.2. Alibaba Group Holding Limited
12.2.3. Alphabet Inc. (Google LLC)
12.2.4. Amazon Web Services (AWS)
12.2.5. Fujitsu Limited
12.2.6. General Vision, Inc.
12.2.7. Graphcore Limited
12.2.8. GreenWaves Technologies
12.2.9. Huawei Technologies Co., Ltd.
12.2.10. Intel Corporation
12.2.11. International Business Machines Corporation (IBM)
12.2.12. Kalray Corporation
12.2.13. Kneron
12.2.14. Koniku Inc
12.2.15. MediaTek Inc.
12.2.16. Micron Technology, Inc.
12.2.17. Microsoft Corporation
12.2.18. Mythic Inc.
12.2.19. NVIDIA Corporation
12.2.20. Qualcomm Technologies, Inc.
12.2.21. SambaNova Systems Inc
12.2.22. Samsung Electronics Co., Ltd.
12.2.23. Tenstorrent Inc.
12.2.24. Wave Computing, Inc.
12.2.25. Xilinx, Inc.
12.2.26. XMOS Limited
12.2.27. Other Prominent Players
Artificial Intelligence Chipset Market By Offering:
Artificial Intelligence Chipset Market By Memory:
Artificial Intelligence Chipset Market By Network:
Artificial Intelligence Chipset Market By Function
Artificial Intelligence Chipset Market By Technology
Artificial Intelligence Chipset Market By End-User
Artificial Intelligence Chipset Market By Region-
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
To know more about the research methodology used for this study, kindly contact us/click here.
