AI Chipsets Market by Hardware (Processor, Memory, Network), Technology (Machine Learning, Natural Language Processing, Computer Vision), Function (Training, Interference), End-User Industry and Region - Global Forecast to 2028
[295 Pages Report] The AI Chipsets market was valued at USD 51.2 billion in 2023 and is estimated to reach USD 131.8 billion by 2028, registering a CAGR of 20.8% during the forecast period. The growth of AI Chipsets market is driven by the growing demand of data traffic and need for high computing power, rising trend towards autonomous vehicles, and rising trend towards parallel computing in AI data centers.
AI Chipsets Market Forecast to 2028
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Market Dynamics:
Drivers: Increasing data traffic and need for high computing power.
A compute-intensive chip is one of the critical parameters for processing AI algorithms; the faster the chip, the quicker it can process the data required to create an AI system. AI chips are mostly deployed in data centers/high-end servers as end computers are incapable of handling such huge workloads and do not have enough power and time frame. AMD offers an EPYC processor series with cloud services, data analytics, and visualization. It features up to 4 TB of memory capacity and 8–10 GB of ethernet speed. It offers advanced I/O integration, flexibility, and security capabilities. AMD EPYC processors are ideally used for cloud computing, high-performance computing (HPC), and many other applications.
Restraint: Lack of AI hardware experts and skilled workforce
AI is a complex system; companies require experts and a skilled workforce to develop, manage, and implement AI systems. For instance, individuals working with artificial intelligence should be learned with technologies such as machine learning (ML), cognitive computing, deep learning, machine intelligence, and image recognition. Adding to this, integration of AI technology in existing systems is a challenging as it requires well-funded in-house R&D and patent filing. Even small errors can interpret into system failure or malfunctioning of a solution, drastically affecting the desired result.
Opportunities: Growing potential of AI based tools in healthcare sector.
AI is one such technology that provides improved services such as monitoring for emergency care, real-time patient data collection and offers preventive healthcare recommendations. AI-based tools can be used for health and wellness services, such as mobile applications, to monitor the movement and activities of patients. The efficient implementation of in-home health monitoring and health information access; personalized health management; and the use of treatment devices (such as better hearing aids; visual assistive devices; and physical assistive devices that include intelligent walkers) are possible with the implementation of AI-based tools. Thus, there is a growing focus on adopting AI-based technologies to support the physical, emotional, social, and mental health of the elderly population worldwide. Future applications may include a combination of multiple AI technologies, such as ML, DL, and computer vision, for pose detection and learning elderly behavioural patterns.
Challenge: Availability of limited structured data to develop efficient AI system
Data is vital for training and developing a complete and robust AI system. Earlier, datasets were mostly structured as the data was entered manually. However, the growing digital footprint and technology trends, such as IoT and Industry 4.0, resulted in the generation of large volumes of data from wearable devices, smart homes, smart thermostats, connected cars, IP cameras, smart appliances, manufacturing machines, industrial equipment, and various other remotely connected devices. This data is largely unstructured and is in the form of text, voice, and images. The lack of an orderly internal structure limits developers from extracting relevant information. However, developers require high-quality labelled data and skilled human trainers to train machine learning tools. Extracting and labelling unstructured data is time-consuming and requires a skilled workforce. Thus, structured data is pivotal in developing an efficient AI system. Companies are now building insights from semi-structured data that facilitates information from groupings.
AI Chipsets Ecosystem
The market for processor segment to hold largest market share during the forecast period.
The processor segment accounts for major market share in the AI chipset market and comprises of GPUs, FPGAs, CPUs, ASICs, DSP and microcontrollers. A GPU is designed to promptly manipulate and modify memory to speed the image creation in a frame buffer intended for output on a display device. It is a programmable logic chip that handles graphic applications and display functions that render high-quality images, animations, and videos. GPUs on standalone cards utilize their memory, whereas GPUs in chipsets share the main memory with CPUs. In a traditional setup of GPUs, dynamic random-access memory (DRAM) chips are placed side by side and connected to the GPU via long copper traces on a PCB. GPUs are widely adopted in mobile phones, embedded systems, automotive, personal computers, and gaming consoles, workstations.
Computer vision segment to hold for major share in the AI chipsets market during the forecast period.
Computer vision is concerns the automatic analysis, extraction, and estimation of useful data from a single image or sequence of images. Computer vision includes the development of theoretical and algorithmic basis to accomplish an automatic visual understanding. Humans use their eyes and brains to see and visually sense the world around them. Moreover, computer vision aims to give a similar capability to machines, robots, and computers. This technology plays a significant role in semiautonomous and autonomous cars as these cars cannot understand human hand signals or any other gestures without computer vision. In the agriculture industry, computer vision technology is widely used for detecting nutrient deficiency in plants, and monitoring crop health.
Training function to register highest market share of the AI chipsets market during the forecast period
ML and DL training are used in various industries to improve performance and efficiency. A few examples of industries and sectors commonly using AI and ML training include healthcare, finance, retail, transportation, manufacturing, agriculture, telecommunication, media, transportation and logistics, and public services. In May 2022, Microsoft announced the use of MAD’s top-tier M1200 Instinct GPUs to run large-scale AI training in the cloud. Also, it is the first public cloud to deploy clusters to AMD’s flagship M1200 GPUs for large-scale AI training.
Consumer electronics industry for AI chipsets market to hold for largest market share from 2023 to 2028
Consumer electronics is the largest industry where AI is deployed. Devices considered under consumer electronics include smartphones, wearables, entertainment robots, and smart home devices. Smartphones are the major contributors to the AI chipset market for consumer electronics. The increasing trend of smart wearables is likely to propel the growth of the AI chipset market.
Fast processors, superior camera quality, connectivity, and applications have made smartphones the most successful electronic device. Next-generation smartphones will leverage innovations such as 5G connectivity, AI capabilities, machine-learning chips, and more processing power. Using dedicated AI chipsets, mobile AI improves the user experience by bringing AI computing to devices. Leading industry players and manufacturers are developing technologies to integrate dedicated AI chips with their products. The growing requirement for higher security, low latency, faster computing, and less reliance on connectivity will drive the adoption of devices with dedicated AI chips.
The AI chipset market in North America is estimated to account for largest share during the forecast period.
North America holds for major share in the AI chipsets market owing to its advanced infrastructure, and initiatives to evolve AI into robust solutions with innovative benefits. The US market is undergoing a major transformation in implementing AI and Machine Learning based solutions. According to Drift, 27% of adults in the US are ready to purchase basic goods through chatbots; 13% of adults in the US have at least once bought expensive items using chatbots. According to Adobe, 28% of leading companies use AI for marketing, while 31% plan to use AI in the next 12 months. According to Edison, 16% of Americans own smart speakers, including Google Home and Amazon Alexa. Some major vendors (IBM, Google, Intel, and Qualcomm) in the AI chipsets market are headquartered in the US. New players are coming up in the US with innovative offerings to bolster the AI chipsets market growth.
AI Chipsets Market by Region
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Key Market Players
Major vendors in the AI chipsets companies include Intel Corporation (US), NVIDIA Corporation (US), IBM (US), AMD (US), Micron Technology Inc (US), Qualcomm Technologies, Inc (US), Samsung Electronics Co., Ltd. (South Korea), Apple Inc. (US), Alphabet Inc. (US), Huawei Technologies Co., Ltd. (China), Texas Instruments Incorporated (US), NXP Semiconductors (Netherlands), Infineon Technologies Inc (Germany), among others. Apart from this, Graphcore (UK), MediaTek Inc. (Taiwan), Analog Devices, Inc. (US), STMicroelectronics (Switzerland), Mythic (US), Kalray (France), Arm Ltd. (UK), Blaize (US), LG Electronics (South Korea), Imagination Technologies (UK), Groq, Inc. (US), Hailo (Israel), Cerebras (US), XMOS (UK), GreenWave (France), SiMa Technologies (US), Kneron (US), Logic Fruit Technologies (India), are among a few emerging companies in the AI chipsets market.
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Report Metric |
Details |
Market size available for years |
2019—2028 |
Base year |
2022 |
Forecast period |
2023—2028 |
Segments covered |
Hardware, Technology, Function, End-User Industry, and Region |
Geographic regions covered |
North America, Europe, Asia Pacific, and RoW |
Companies covered |
The major players include Intel Corporation (US), NVIDIA Corporation (US), IBM (US), AMD (US), Micron Technology Inc (US), Qualcomm Technologies, Inc (US), Samsung Electronics Co., Ltd. (South Korea), Apple Inc. (US), Alphabet Inc. (US), Huawei Technologies Co., Ltd. (China), Texas Instruments Incorporated (US), NXP Semiconductors (Netherlands), Infineon Technologies Inc (Germany), and Others- total 31 players have been covered. |
AI Chipsets Market Highlights
This research report categorizes the AI Chipsets market Hardware, Technology, Function, End-User Industry, and Region.
Segment |
Subsegment |
By Hardware: |
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By Technology: |
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By Function: |
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By End-User Industry: |
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Recent Developments
- In December 2022, Samsung (South Korea) and NAVER Corporation (South Korea), which operates the search engine Naver, announced a collaboration to develop semiconductor solutions tailored for hyper-scale artificial intelligence (AI) models. The companies intend to pool their hardware and software resources to accelerate massive AI workload handling.
- In November 2022, Qualcomm Technologies Inc. (US) launched the Snapdragon 8 Generation 2 processor featuring an 8-core CPU and fused AI Neural Network for smartphones, tablets, laptops, and smartwatches applications.
- In October 2022, Google (US) unveiled the latest Tensor SoC, Tensor G2, of the Pixel 7 series. The SoC features an 8-core CPU with clock speed up to 2.85 GHz, LPDDR5 RAM, and integrated TPU & GPU.
Key Questions Addressed in the Report:
What is the total CAGR expected to be recorded for the AI chipsets market during 2023-2028?
The global AI chipsets market is expected to record a CAGR of 20.8% from 2023-2028.
Which regions are expected to pose significant demand for the AI chipsets market from 2023-2028?
North America & Asia Pacific are expected to pose significant demand from 2023 to 2028. Major economies such as US, China, UK, Japan, and Germany are expected to have a high potential for the future growth of the market.
What are the major market opportunities for the AI chipsets market?
Surging demand for AI based FPGA technology, growing adoption of industrial robot, increasing data traffic and need for high computing power, and growth potential of AI based tools in healthcare are the significant market opportunities in the AI chipsets market during the forecast period.
Which are the significant players operating in the AI chipsets market?
Key players operating in the AI chipsets market are Intel Corporation (US), NVIDIA Corporation (US), IBM (US), AMD (US), Micron Technology Inc (US), Qualcomm Technologies, Inc (US), Samsung Electronics Co., Ltd. (South Korea), Apple Inc. (US), Alphabet Inc. (US), Huawei Technologies Co., Ltd. (China), Texas Instruments Incorporated (US), NXP Semiconductors (Netherlands), Infineon Technologies Inc (Germany), among others.
What are the major industries of the AI chipsets market?
Consumer Electronics, Healthcare, Cybersecurity, Marketing, and Fintech are the major industries of AI chipsets market.
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The research study involved the extensive use of secondary sources, directories, and databases (annual reports or presentations of companies, industry association publications, directories, technical handbooks, World Economic Outlook (WEO), trade websites, Hoovers, Bloomberg Businessweek, Factiva, and OneSource) to identify and collect information useful for this technical, market-oriented, and commercial study of the AI Chipsets market. Primary sources mainly comprise several experts from the core and related industries, along with preferred suppliers, manufacturers, distributors, service providers, system providers, technology developers, alliances, and standards and certification organizations related to various phases of this industry’s value chain.
Secondary Research
Various secondary sources have been referred to in the secondary research process for identifying and collecting information important for this study. The secondary sources include annual reports, press releases, and investor presentations of companies; white papers; journals and certified publications; and articles from recognized authors, websites, directories, and databases. Secondary research has been conducted to obtain key information about the industry’s supply chain, market’s value chain, the total pool of key players, market segmentation according to the industry trends (to the bottom-most level), geographic markets, and key developments from both market- and technology-oriented perspectives. The secondary data has been collected and analyzed to determine the overall market size, further validated by primary research.
Primary Research
In the primary research process, various primary sources from the supply and demand sides have been interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side include industry experts, such as CEOs, vice presidents, marketing directors, technology & innovation directors, and related key executives from key companies and organizations operating in the AI Chipsets market across four major regions: North America, Europe, Asia Pacific, and RoW (South America, and Middle East and Africa). Primary data has been collected through questionnaires, e-mails, and telephonic interviews. Approximately 40% and 60% of primary interviews have been conducted from the demand and supply sides, respectively.
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Market Size Estimation
In the complete market engineering process, both top-down and bottom-up approaches have been used along with several data triangulation methods to perform market estimation and forecasting for the overall market segments and subsegments listed in this report. Key players in the market have been identified through secondary research, and their market shares in the respective regions have been determined through primary and secondary research. This entire procedure includes the study of annual and financial reports of the top market players and extensive interviews for key insights (quantitative and qualitative) with industry experts (CEOs, VPs, directors, and marketing executives).
In this approach, important players, such Intel Corporation (US), NVIDIA Corporation (US), IBM (US), AMD (US), and Micron Technology, Inc. (US) have been identified. After confirming these companies through primary interviews with industry experts, their total revenue has been estimated by referring to annual reports, SEC filings, and paid databases. Revenues of these companies pertaining to the business units (Bus) that offer AI Chipsets have been identified through similar sources. Industry experts have reconfirmed these revenues through primary interviews.
AI Chipsets Market: Bottom-Up Approach
The bottom-up approach has been employed to arrive at the overall size of the AI Chipsets market from the revenues of key players and their share in the market.
AI Chipsets Market: Top-Down Approach
In the top-down approach, the overall market size has been used to estimate the size of the individual markets (mentioned in the market segmentation) through percentage splits from secondary and primary research. The most appropriate immediate parent market size has been used to implement the top-down approach to calculate the market size of specific segments. The top-down approach has been implemented for the data extracted from the secondary research to validate the market size obtained.
Each company’s market share has been estimated to verify the revenue shares used earlier in the supply-side approach. The overall parent market size and individual market sizes were determined and confirmed in this study by the data triangulation method and the validation of data through primaries. The data triangulation method used in this study is explained in the next section.
Data Triangulation
After arriving at the overall market size from the market size estimation process explained earlier, the total market was split into several segments and subsegments. Data triangulation and market breakdown procedures have been employed to complete the overall market engineering process and arrive at the exact statistics for all segments and subsegments, wherever applicable. The data has been triangulated by studying various factors and trends from both the demand and supply sides. Along with this, the AI Chipsets market has been validated using both top-down and bottom-up approaches.
Market Definition
Al chipset, also known as an Al processor, is a specialized hardware component designed to accelerate the processing of artificial intelligence (Al) workloads. These workloads involve computationally intensive tasks such as machine learning, deep learning, natural language processing, and computer vision. Al chipsets in cloud and data centers are entirely high-performance chips designed to handle compute-intensive training and high-volume interference workloads.
Artificial intelligence (AI) technology is now implemented in smartphones, automobiles, drones, and robots. Edge Al is the combination of edge computing and artificial intelligence. Edge Al is the implementation of Al applications in devices throughout the physical world. In this technique, the computation of Al is done near the user at the edge of the network, close to where the data is located, rather than centrally in a cloud computing facility or at private data centers. Edge Al offers a way to process data faster than cloud processing. The release of low-power and high-computing processors has led to the integration Al algorithms into devices. Developing dedicated Al processors for edge devices has resulted in Al inference performed on devices rather than the cloud platform.
Key Stakeholders
- Government and financial institutions and investment communities
- Analysts and strategic business planners
- Semiconductor product designers and fabricators
- Application providers
- Al solution providers
- Al platform providers
- Business providers
- Professional service/solution providers
- Research organizations
- Technology standard organizations, forums, alliances, and associations
- Technology investors
Report Objectives
- To define, describe, and forecast the Al chipsets market based on technology, hardware, function, and end-user industry (for both cloud and data center, and edge)
- To forecast the size of the market segments for four major regions-North America, Europe, Asia Pacific, and the Rest of the World (ROW)
- To forecast the size and market segments of the Al chipsets market by volume based on processors (for both cloud and data center and edge devices)
- To forecast the size and market segments of the Al chipsets market by revenue based on processors (for Cloud and data center)
- The scope of processors in the Al chipset market for Cloud and data centers includes CPU, GPU, ASIC, and FPGA.
- The processor scope in the Al chipset market for edge devices includes CPU, GPU, ASIC, FPGA, DSP, and Microcontrollers.
- To provide detailed information regarding the major factors influencing the growth of the market (drivers, restraints, opportunities, and challenges)
- To strategically analyze micrornarkets with respect to individual growth trends, prospects, and contributions to the total market
- To study the complete value chain and allied industry segments and perforin a market value chain analysis
- To strategically profile the key players and comprehensively analyze their market shares and core competencies
- To analyze the opportunities in the market for stakeholders and describe the competitive landscape of the market
- To analyze competitive developments such as collaborations, agreements, partnerships, product developments, and research & development (R&D) in the market
- To analyze the impact of the recession on the Al chipsets market
Available Customizations
With the given market data, MarketsandMarkets offers customizations according to the company’s specific needs. The following customization options are available for the report:
Company Information
- Detailed analysis and profiling of additional market players (up to 7)
Growth opportunities and latent adjacency in AI Chipsets Market