AI Chip Market Size, Share & Industry Trends

AI Chip Market Size, Share & Industry Trends Growth Analysis Report by Offerings (GPU, CPU, FPGA, NPU, TPU, Trainium, Inferentia, T-head, Athena ASIC, MTIA, LPU, Memory (DRAM (HBM, DDR)), Network (NIC/Network Adapters, Interconnects)), Function (Training, Inference) & Region – Global Forecast to 2029

Report Code: SE 5997 Aug, 2024, by marketsandmarkets.com

Updated on : Sep 23, 2024

AI Chip Market Size & Share

[358 Pages Report] The global AI chip market size is projected to grow from USD 123.16 billion in 2024 to USD 311.58 billion by 2029, at a CAGR of 20.4%.

The AI chip market is driven by the increasing adoption of AI servers by hyperscalers and the growing use of Generative AI technologies and applications, such as GenAI and AIoT, across various industries, including BFSI, healthcare, retail & e-commerce, and media & entertainment.

AI chips help achieve high-speed parallel processing in AI servers, offering high performance and efficiently handling AI workloads in the cloud data center ecosystem. Moreover, the surging adoption of edge AI computing and the rising focus on real-time data processing, coupled with robust government-led investments in AI infrastructure development, especially in economies across the Asia Pacific region, further contribute to the AI chip industry growth.

AI Chip Market

AI Chip Market

AI Chip Market Forecast to 2029

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AI Chip Market Trends

Driver: Increasing adoption of AI servers by hyperscalers

There is a spike in demand for AI chips with the rising deployment of AI servers in diversified AI-powered applications across several industries, including BFSI, healthcare, retail & e-commerce, media & entertainment, and automotive. Data center owners and cloud service providers are upgrading their infrastructure to enable AI applications.

According to MarketsandMarkets analysis, AI server penetration represented 8.8% of all servers in 2023 and is anticipated to reach 30% by 2029. The rising inclination toward using chatbots, Artificial Intelligence of Things (AIoT), predictive analytics, and natural language processing drives the need for AI servers to support these applications. These applications require powerful hardware platforms to perform complex computations and process large data volumes.

AI servers have advanced computational capabilities and are designed to handle large datasets. They can also process data in real time and play a crucial role in training AI models. Owing to the growing demand for faster processing speeds and greater energy efficiency, AI servers are primarily used by cloud service providers, enterprises, academic institutions, and commercial end users.

Increasing investments and a growing trend of AI-enhanced infrastructure set the base for the high demand for AI chips.

Restraint: Adverse impact of high-power consuming graphics processing units (GPUs) and application-specific integrated circuits (ASICs) on environment

Data centers and other infrastructure supporting AI workloads use GPUs and ASICs with parallel processing features. This makes them suitable for handling complex AI workloads; however, parallel processing in GPUs results in high power consumption. This increases energy costs for data centers and organizations deploying AI infrastructure. AI systems can handle large-scale AI operations; however, they also consume significant power to carry out these functions.

As AI models become more complex and the volume of data increases, there is a surge in power demands for AI chips. Excessive power consumption results in excessive heating, which can only be handled by more advanced cooling systems. This adds to the complexity and cost of infrastructure.

GPUs and ASICs work in parallel with thousands of cores. This requires immense computational power to carry out advanced AI workloads, including deep learning training and large-scale simulations. Hence, companies adopt network components with higher thermal design power (TDP) values. GPUs with higher TDP are in demand due to their better performance.

Therefore, AI chip manufacturers are focused on developing GPUs with a high TDP range. For example, in August 2022, Intel Corporation (US) launched the Flex140 data center GPU, followed by the Max 1450 GPU in October 2023, both with a TDP rating of around 600 watts compared to their older versions, such as Flex 140 GPU and Flex 170 GPU, both having TDP 150 watts. As data-intensive computing requirements continue to rise, manufacturers are developing chips with high processing power. However, the high energy consumption of GPUs and ASICs raises concerns about the environmental impact, particularly in terms of carbon emissions and sustainability. As governments push for greener practices, the environmental footprint of AI hardware could become a critical factor in decision-making, limiting the adoption of high-power-consuming chips.

Opportunity: Planned investments in data centers by cloud service providers

Cloud service providers (CSPs) are making massive investments in scaling and upgrading data center infrastructures to support accelerating demand for AI-based applications and services. Most investments that CSPs make in data centers aim to attain scalability and operational efficiency.

As they increase their cloud services, demand for AI chips is likely to increase, creating growth opportunities for AI chip providers. For instance, AWS (US) declared an investment of USD 5.30 billion into constructing cloud data centers in Saudi Arabia. Similarly, in November 2023, Microsoft (US) declared its plan to build several new data centers in Quebec, expanding across Canada. In the next two years, it will invest USD 500 million to build up its cloud computing and AI infrastructure in Quebec. It needs state-of-the-art AI chips powered by GPUs, TPUs, and AI accelerators to take control of the ever-increasing computational requirements in AI training and inference.

Challenge: Addressing delivery delays due to supply chain disruptions

Supply chain disruption is one of the major challenges faced by players in the AI chip market. It affects the production quantity, delivery time, and, ultimately, the cost of processors. Component shortages result from either the lack of sufficient semiconductor material or limited production capacity, which creates significant production delays. Production delays may also occur due to equipment breakdown or the complexity of processing cutting-edge AI chips. There is a greater demand for high-performance GPUs with faster real-time large language model (LLM) training and inference capabilities. This can further increase the time to market. Thus, supply chain disruptions significantly impact the entire AI chip market.

Hardware manufacturers face challenges in meeting production schedules due to delays in the availability of AI chips. System integrators that are dependent on the timely delivery of components to set up and configure AI infrastructure face project delays, which prevent the delivery of solutions to clients on time. Setbacks are suffered by cloud service providers scaling up their data center operations to match the surging demand for AI-driven services. For instance, the demand for NVIDIA H1OO and A1OO GPUs is considerably high; therefore, the lead time of GPU servers extends up to 52 weeks. This prolonged lead time creates big problems for organizations deploying high-performance GPUs in their AI infrastructure. Apart from affecting the deployment timeline, this also causes delays and increases costs; for instance, organizations may need to wait longer or find other options at higher prices.

AI Chip Ecosystem

AI Chip Market by Ecosystem

AI Chip Market Segment

GPU segment is expected to record largest market share during forecast period

The GPU segment is projected to witness the largest market share during the forecast period. GPUs can effectively handle huge computational loads required to train and run deep learning models using complex matrix multiplications. This makes them vital in data centers and AI research, where the fast growth of AI applications calls for efficient hardware solutions.

New GPUs, which enhance AI capabilities not only for data centers but also at the edge, are constantly developed and released by major manufacturers such as NVIDIA Corporation (US), Intel Corporation (US), and Advanced Micro Devices, Inc. (US). For example, in November 2023, NVIDIA Corporation released an upgraded HGX H200 platform based on Hopper architecture featuring the H200 Tensor core GPU. The first GPU to pack HBM3e memory provides 141 GB of memory at a blazing speed of 4.8 terabytes per second.

Leading cloud service providers, including Amazon Web Services, Inc.; Google Cloud; Microsoft Azure; and Oracle Cloud Infrastructure, are committed to deploying H200-based GPUs to prove that GPUs are one of the critical components of the cloud computing ecosystem. Improvements in GPU memory capabilities and the growing adoption of highly advanced GPUs by cloud service providers will further accelerate market growth.

Inference segment to account for largest share of AI chip market throughout forecast period

The AI chip market for inference functions accounted for the largest market share in 2023 and is projected to grow at the highest rate during the forecast period. Inference leverages pre-trained AI models to make accurate predictions or timely decisions based on new data. With businesses shifting toward AI integration to improve production efficiency, enhance customer experience, and drive innovation, there is a growing need for robust inference capabilities in the data center.

Data centers are rapidly scaling up their AI capabilities, highlighting the importance of efficiency and performance in inference processing. A critical factor fostering the growth of the AI chip market is the elevating requirement for more energy-efficient and high-performing inference chips. For example, SEMIFIVE has unveiled its 14 nm AI Inference SoC Platform, developed in collaboration with Mobilint, Inc. of South Korea. This platform is designed explicitly for inference tasks and features a quad-core high-performance 64-bit CPU, PCIe Gen4 interfaces, and LPDDR4 memory channels.

It is suitable for custom AI chips, including ASICs. Such chips are designed to power data center accelerators, AI vision processors, and big data analytics tools implemented for image and video recognition. All these tools rely highly on efficient and scalable inference processing. Developing AI inference SoC platforms underpins the increasing demand for special-purpose hardware solutions, which can help optimize inference workload performance within data centers.

Generative AI segment to account for majority of market share throughout forecast period

 Generative AI technology is likely to dominate the AI chip market throughout the forecast period. There is an exponential increase in the demand for AI models that can generate high-quality content, including text, images, and codes.

As GenAI models are becoming more complex, there is a high requirement for AI chips with higher processing capabilities and memory bandwidth from data center service providers. GenAI applications are also adopted at a significantly high rate across various enterprises, including retail & e-commerce, BFSI, healthcare, media & entertainment, in dynamic applications, such as NLP, content generation, and automated design generation and process. The rising demand for GenAI solutions across these industries is expected to fuel the AI chip market growth in the coming years.

Cloud service providers segment to capture largest share of AI chip market during forecast period

The cloud service providers (CSPs) segment is likely to hold the largest share of the AI chip market during the forecast period. Cloud service providers are increasingly implementing high-end AI chips in their data centers to stay competitive in the market.

For instance, in July 2024, Northern Data Group (Germany) unveiled Europe's pioneering cloud services featuring NVIDIA's H200 GPUs. Leveraging 2,000 NVIDIA H200 GPUs, the company is set to deliver a remarkable 32 petaFLOPS of performance. Such significant investments by CSPs will propel the growth of the AI chip market during the forecast period.

AI Chip Market Regional Analysis

Asia Pacific to be fastest-growing market during forecast period

The AI chip market in Asia Pacific is poised to grow at the highest CAGR during the forecast period. The escalating adoption of AI technologies in countries such as China, South Korea, India, and Japan will stimulate market growth.

AI research and development (R&D) activities receive significant funding from regional government entities, fostering a favorable environment for Al developments. Additionally, the presence of high-bandwidth memory (HBM) tech giants, such as Samsung (South Korea), Micron Technology Inc. (US), and SK Hynix Inc (South Korea), which have dedicated HBM manufacturing facilities in South Korea, Taiwan, and China, will further boost the AI chip market growth in Asia Pacific in the next few years.

AI Chip Market by Region

AI Chip Market by Region

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Top AI Chip Companies - Key Market Players

Major vendors in the AI chip companies are

Apart from this, Mythic (US), Kalray (France), Blaize (US), Groq, Inc. (US), HAILO TECHNOLOGIES LTD (Israel), GreenWaves Technologies (France), SiMa Technologies, Inc. (US), Kneron, Inc. (US), Rain Neuromorphics Inc. (US), Tenstorrent (Canada), SambaNova Systems, Inc. (US), Taalas (Canada), SAPEON Inc. (US), Rebellions Inc. (South Korea), Rivos Inc. (US), and Shanghai BiRen Technology Co., Ltd. (China)  are among a few emerging companies in the AI chip market.

AI Chip Market Report Scope

Report Metric

Details

Estimated Market Size USD 123.16 billion in 2024
Projected Market Size USD 311.58 billion by 2029
Growth Rate CAGR of 20.4%.

AI Chip Market size available for years

2020–2029

Base year

2023

Forecast period

2024–2029

Segments covered

Offering, Technology, Function, End User, and Region

Geographic regions covered

North America, Europe, Asia Pacific, and RoW

Companies covered

A total of 28 players have been covered.

The major players include NVIDIA Corporation (US), Intel Corporation (US), Advanced Micro Devices, Inc. (US), Micron Technology, Inc. (US), Google (US), Samsung (South Korea), SK HYNIX INC. (South Korea), Qualcomm Technologies, Inc. (US), Huawei Technologies Co., Ltd. (China), Apple Inc. (US), Imagination Technologies (UK), Graphcore (UK), and Cerebras (US), among others.

AI Chip Market Highlights

This research report categorizes the AI Chip Market by Offerings, Function, Technology, End User, and Region.

Segment

Subsegment

By Offerings:

  • GPU
  • CPU
  • FPGA
  • NPU
  • TPU
  • Dojo & FSD
  • Trainium & Inferentia
  • Athena ASIC
  • T-head
  • MTIA
  • LPU
  • Other ASIC
  • Memory
    • DRAM
      • HBM
      • DDR
  • Network
  • NIC/Network Adapters
    • Infiniband
    • Ethernet
  • Interconnects

By Technology:

  • Generative AI
    • Rule Based Models
    • Statistical Models
    • Deep Learning
    • Generative Adversarial Networks (GANs)
    • Autoencoders
    • Convolutional Neural Networks (CNNs)
    • Transformer Models
  • Machine Learning
  • Natural Language Processing
  • Computer Vision

By Function:

  • Training
  • Inference

By End-User:

  • Consumer
  • Data Center
    • CSP
    • Enterprises
      • Healthcare
      • BFSI
      • Automotive
      • Retail & E-Commerce
      • Media & Entertainment
      • Others
  • Government Organizations

By Region:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • UK
    • Germany
    • France
    • Italy
    • Spain
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Rest of Asia Pacific
  • Rest of the World (RoW)
    • South America
    • Middle East
      • GCC Countries
      • Rest of Middle East
    • Africa

Recent Developments in AI Chip Industry

  • In June 2024, Advanced Micro Devices, Inc. (US) introduced AMD Ryzen AI 300 Series processors with powerful NPUs offering 50 TOPS AI-processing power for next-generation AI PCs. These processors are powered by the new Zen5 architecture with 12 high-performance CPU cores and feature advanced AI architecture for gaming and productivity.
  • In May 2024, Google (US) introduced Trillium, a sixth-generation TPU with improved training and serving times for AI workloads. It also has increased clock speed and the size of matrix multiply units. Trillium TPU powers the next wave of AI models.
  • In April 2024, Micron Technology, Inc. (US) and Silvaco Group, Inc. (US) extended their partnership to develop an AI-based solution: Fab Technology Co-Optimization (FTCO). This solution enables customers to use manufacturing data to perform machine learning software simulations and create a computer model to simulate the wafer fabrication process. Micron Technology, Inc. (US) invested USD 5 million in the development of FTCO.
  • In March 2024, NVIDIA Corporation (US) introduced the NVIDIA Blackwell platform to enable organizations to build and run real-time GenAI featuring six transformative technologies for accelerated computing. The platform allows AI training and real-time LLM inference for models with up to 10 trillion parameters.
  • In February 2024, Intel Corporation (US) and Cadence Design Systems, Inc. (US) expanded their strategic partnership through a multiyear agreement to develop advanced system-on-chip (SoC) designs. The partnership aims to meet the rising demand from the fast-growing markets, including AI, ML, HPC, and premium mobile computing.

Key Questions Addressed in Report:

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TABLE OF CONTENTS
 
1 INTRODUCTION (Page No. - 28)
    1.1 STUDY OBJECTIVES 
    1.2 MARKET DEFINITION 
    1.3 STUDY SCOPE 
           1.3.1 MARKETS COVERED AND REGIONAL SCOPE
           1.3.2 INCLUSIONS AND EXCLUSIONS
           1.3.3 YEARS CONSIDERED
    1.4 CURRENCY CONSIDERED 
    1.5 UNIT CONSIDERED 
    1.6 LIMITATIONS 
    1.7 STAKEHOLDERS 
    1.8 SUMMARY OF CHANGES 
 
2 RESEARCH METHODOLOGY (Page No. - 34)
    2.1 RESEARCH DATA 
           2.1.1 SECONDARY AND PRIMARY RESEARCH
           2.1.2 SECONDARY DATA
                    2.1.2.1 List of key secondary sources
                    2.1.2.2 Key data from secondary sources
           2.1.3 PRIMARY DATA
                    2.1.3.1 List of primary interview participants
                    2.1.3.2 Breakdown of primaries
                    2.1.3.3 Key data from primary sources
                    2.1.3.4 Key industry insights
    2.2 MARKET SIZE ESTIMATION METHODOLOGY 
           2.2.1 BOTTOM-UP APPROACH
                    2.2.1.1 Approach to arrive at market size using bottom-up analysis (demand side)
           2.2.2 TOP-DOWN APPROACH
                    2.2.2.1 Approach to arrive at market size using top-down analysis (supply side)
    2.3 DATA TRIANGULATION 
    2.4 RESEARCH ASSUMPTIONS 
    2.5 RISK ANALYSIS 
    2.6 RESEARCH LIMITATIONS 
 
3 EXECUTIVE SUMMARY (Page No. - 48)
 
4 PREMIUM INSIGHTS (Page No. - 54)
    4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI CHIP MARKET 
    4.2 AI CHIP MARKET, BY COMPUTE 
    4.3 AI CHIP MARKET, BY MEMORY 
    4.4 AI CHIP MARKET, BY NETWORK 
    4.5 AI CHIP MARKET, BY TECHNOLOGY AND FUNCTION 
    4.6 AI CHIP MARKET, BY END USER 
    4.7 AI CHIP MARKET, BY REGION 
    4.8 AI CHIP MARKET, BY COUNTRY 
 
5 MARKET OVERVIEW (Page No. - 58)
    5.1 INTRODUCTION 
    5.2 MARKET DYNAMICS 
           5.2.1 DRIVERS
                    5.2.1.1 Pressing need for large-scale data handling and real-time analytics
                    5.2.1.2 Rising adoption of autonomous vehicles
                    5.2.1.3 Surging use of GPUs and ASICs in AI servers
                    5.2.1.4 Continuous advancements in machine learning and deep learning technologies
                    5.2.1.5 Increasing penetration of AI servers
           5.2.2 RESTRAINTS
                    5.2.2.1 Shortage of skilled workforce with technical know-how
                    5.2.2.2 Computational workloads and power consumption in AI Chip
                    5.2.2.3 Unreliability of AI algorithms
           5.2.3 OPPORTUNITIES
                    5.2.3.1 Elevating demand for AI-based FPGA chips
                    5.2.3.2 Government initiatives to deploy AI-enabled defense systems
                    5.2.3.3 Rising trend of AI-driven diagnostics and treatments
                    5.2.3.4 Increasing investments in AI-enabled data centers by cloud service providers
                    5.2.3.5 Rise in adoption of AI-based ASIC technology
           5.2.4 CHALLENGES
                    5.2.4.1 Data privacy concerns associated with AI platforms
                    5.2.4.2 Availability of limited structured data to develop efficient AI systems
                    5.2.4.3 Supply chain disruptions
    5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS 
    5.4 PRICING ANALYSIS 
           5.4.1 AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY COMPUTE
           5.4.2 AVERAGE SELLING PRICE TREND, BY REGION
    5.5 VALUE CHAIN ANALYSIS 
    5.6 ECOSYSTEM ANALYSIS 
    5.7 INVESTMENT AND FUNDING SCENARIO 
    5.8 TECHNOLOGY ANALYSIS 
           5.8.1 KEY TECHNOLOGIES
                    5.8.1.1 High-bandwidth Memory (HBM)
                    5.8.1.2 GenAI workload
           5.8.2 COMPLEMENTARY TECHNOLOGIES
                    5.8.2.1 Data center power management and cooling system
                    5.8.2.2 High-speed interconnects
           5.8.3 ADJACENT TECHNOLOGIES
                    5.8.3.1 AI development frameworks
                    5.8.3.2 Quantum AI
    5.9 SERVER COST STRUCTURE/BILL OF MATERIAL 
           5.9.1 CPU SERVER
           5.9.2 GPU SERVER
    5.10 PENETRATION AND GROWTH OF AI SERVERS 
    5.11 UPCOMING DEPLOYMENT OF DATA CENTERS BY CLOUD SERVICE PROVIDERS (CSPS) 
    5.12 CLOUD SERVICE PROVIDERS’ CAPEX 
    5.13 SERVER PROCUREMENT BY CLOUD SERVICE PROVIDERS, 2020–2029 
    5.14 PROCESSOR BENCHMARKING 
           5.14.1 GPU BENCHMARKING
           5.14.2 CPU BENCHMARKING
    5.15 PATENT ANALYSIS 
    5.16 TRADE ANALYSIS 
           5.16.1 IMPORT SCENARIO (HS CODE 854231)
           5.16.2 EXPORT SCENARIO (HS CODE 854231)
    5.17 KEY CONFERENCES AND EVENTS, 2024–2025 
    5.18 CASE STUDY ANALYSIS 
           5.18.1 CDW INTEGRATED AMD EPYC SOLUTIONS TO ENSURE ENERGY EFFICIENCY AND OPTIMUM SPACE UTILIZATION
           5.18.2 OVH SAS LEVERAGED AMD EPYC PROCESSOR TO OPTIMIZE PERFORMANCE OF CLOUD SOLUTIONS IN AI WORKLOADS
           5.18.3 INTEL XEON SCALABLE PROCESSORS POWER TENCENT CLOUD’S XIAOWEI INTELLIGENT SPEECH AND VIDEO SERVICE ACCESS PLATFORM
           5.18.4 AIC HELPS WESTERN DIGITAL TO ENHANCE SSD TESTING AND VALIDATION EFFICIENCY USING AMD PROCESSOR
    5.19 REGULATORY LANDSCAPE 
           5.19.1 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
           5.19.2 STANDARDS
    5.2 PORTER’S FIVE FORCES ANALYSIS 
           5.20.1 THREAT OF NEW ENTRANTS
           5.20.2 THREAT OF SUBSTITUTES
           5.20.3 BARGAINING POWER OF SUPPLIERS
           5.20.4 BARGAINING POWER OF BUYERS
           5.20.5 INTENSITY OF COMPETITION RIVALRY
    5.21 KEY STAKEHOLDERS AND BUYING CRITERIA 
           5.21.1 KEY STAKEHOLDERS IN BUYING PROCESS
           5.21.2 BUYING CRITERIA
 
6 AI CHIP MARKET, BY COMPUTE (Page No. - 117)
    6.1 INTRODUCTION 
    6.2 GPU 
           6.2.1 ABILITY TO HANDLE AI WORKLOADS AND PROCESS VAST DATA VOLUMES TO BOOST ADOPTION
    6.3 CPU 
           6.3.1 RISING DEMAND FOR VERSATILE AND GENERAL-PURPOSE AI PROCESSING TO AUGMENT MARKET GROWTH
    6.4 FPGA 
           6.4.1 GROWING NEED FOR FLEXIBILITY AND CUSTOMIZATION FOR AI WORKLOADS TO SPUR DEMAND
    6.5 NPU 
           6.5.1 RISING DEMAND FOR HIGH-END SMARTPHONES TO DRIVE SEGMENTAL GROWTH
    6.6 TPU 
           6.6.1 PRESSING NEED FOR FASTER PROCESSING IN AI RESEARCH AND APPLICATION DEVELOPMENT TO BOOST DEMAND
    6.7 DOJO & FSD 
           6.7.1 ACCELERATING DEMAND FOR HIGH-PERFORMANCE, ENERGY-EFFICIENT AI PROCESSING IN AUTONOMOUS VEHICLES TO FUEL ADOPTION
    6.8 TRAINIUM & INFERENTIA 
           6.8.1 ABILITY TO TRAIN COMPLEX AI AND DEEP LEARNING MODELS TO DRIVE ADOPTION
    6.9 ATHENA ASIC 
           6.9.1 INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED AI TASKS TO ACCELERATE MARKET GROWTH
    6.10 T-HEAD 
           6.10.1 RISING DEMAND FOR CUSTOMIZED, HIGH-PERFORMANCE AI CHIPS ACROSS CHINESE DATA CENTERS TO STIMULATE MARKET GROWTH
    6.11 MTIA 
           6.11.1 META'S EXPANSION INTO AR, VR, AND METAVERSE TO FUEL MARKET GROWTH
    6.12 LPU 
           6.12.1 INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED AI TASKS TO ACCELERATE MARKET GROWTH
    6.13 OTHER ASIC 
 
7 AI CHIP MARKET, BY MEMORY (Page No. - 131)
    7.1 INTRODUCTION 
    7.2 DDR 
           7.2.1 RISING ADOPTION OF AI-ENABLED CPUS IN DATA CENTERS TO SUPPORT MARKET GROWTH
    7.3 HBM 
           7.3.1 ELEVATING NEED FOR HIGH THROUGHPUT IN DATA-INTENSIVE AI TASKS TO FUEL MARKET GROWTH
 
8 AI CHIP MARKET, BY NETWORK (Page No. - 136)
    8.1 INTRODUCTION 
    8.2 NIC/NETWORK ADAPTERS 
           8.2.1 INFINIBAND
                    8.2.1.1 Growing utilization of HPC and AI models to minimize latency and maximize throughput to boost segmental growth
           8.2.2 ETHERNET
                    8.2.2.1 Rising demand for scalable and cost-effective networking solutions to propel growth
    8.3 INTERCONNECTS 
           8.3.1 GROWING COMPLEXITY OF AI MODELS REQUIRING HIGH-BANDWIDTH DATA PATHS TO FUEL DEMAND
 
9 AI CHIP MARKET, BY TECHNOLOGY (Page No. - 143)
    9.1 INTRODUCTION 
    9.2 GENERATIVE AI 
           9.2.1 RULE-BASED MODELS
                    9.2.1.1 Rising need to detect fraud in finance sector to propel market
           9.2.2 STATISTICAL MODELS
                    9.2.2.1 Requirement to make accurate predictions from complex data structures to boost segmental growth
           9.2.3 DEEP LEARNING
                    9.2.3.1 Ability to advance AI technologies to boost demand
           9.2.4 GENERATIVE ADVERSARIAL NETWORKS (GAN)
                    9.2.4.1 Pressing need to handle large-scale data to fuel segmental growth
           9.2.5 AUTOENCODERS
                    9.2.5.1 Ability to compress and restructure data to ensure optimum storage space in data centers to stimulate demand
           9.2.6 CONVOLUTIONAL NEURAL NETWORKS (CNNS)
                    9.2.6.1 Surging demand for realistic and high-quality images and videos to accelerate market growth
           9.2.7 TRANSFORMER MODELS
                    9.2.7.1 Increasing utilization in image synthesis and captioning applications to foster segmental growth
    9.3 MACHINE LEARNING 
           9.3.1 RISING USE IN IMAGE AND SPEECH RECOGNITION AND PREDICTIVE ANALYTICS TO CONTRIBUTE TO MARKET GROWTH
    9.4 NATURAL LANGUAGE PROCESSING 
           9.4.1 INCREASING NEED FOR REAL-TIME APPLICATIONS TO SUPPORT MARKET GROWTH
    9.5 COMPUTER VISION 
           9.5.1 ESCALATING NEED FOR ADVANCED PROCESSING CAPABILITIES TO BOOST DEMAND
 
10 AI CHIP MARKET, BY FUNCTION (Page No. - 154)
     10.1 INTRODUCTION 
     10.2 TRAINING 
             10.2.1 SURGING NEED TO PROCESS LARGE DATA SETS AND PERFORM PARALLEL COMPUTATION TO CREATE OPPORTUNITIES
     10.3 INFERENCE 
             10.3.1 SURGING DEPLOYMENT ACROSS VARIOUS INDUSTRIES TO BOOST DEMAND
 
11 AI CHIP MARKET, BY END USER (Page No. - 159)
     11.1 INTRODUCTION 
     11.2 CONSUMER 
             11.2.1 GROWING ADOPTION OF AI-ENABLED PERSONAL DEVICES TO PROPEL MARKET
     11.3 DATA CENTERS 
             11.3.1 CLOUD SERVICE PROVIDERS
                        11.3.1.1 Surging AI workloads and cloud adoption to stimulate market growth
             11.3.2 ENTERPRISES
                        11.3.2.1 Escalating use of NLP, image recognition, and predictive analytics to create growth opportunities
                        11.3.2.2 Healthcare
                                     11.3.2.2.1 Integration of AI in computer-aided drug discovery and development to foster market growth
                        11.3.2.3 BFSI
                                     11.3.2.3.1 Surging need for fraud detection in financial institutions to boost demand
                        11.3.2.4 Automotive
                                     11.3.2.4.1 Growing focus on safe and enhanced driving experiences to fuel demand
                        11.3.2.5 Retail & ecommerce
                                     11.3.2.5.1 Increasing use of chatbots and virtual assistants to offer improved customer services to drive market
                        11.3.2.6 Media & entertainment
                                     11.3.2.6.1 Real-time analysis of viewer preferences, engagement patterns, and demographic information to augment market growth
                        11.3.2.7 Others
     11.4 GOVERNMENT ORGANIZATIONS 
             11.4.1 SIGNIFICANT FOCUS ON AUTOMATING ROUTINE TASKS AND EXTRACTING REAL-TIME ACTIONABLE INSIGHTS TO SUPPORT MARKET GROWTH
 
12 AI CHIP MARKET, BY REGION (Page No. - 174)
     12.1 INTRODUCTION 
     12.2 NORTH AMERICA 
             12.2.1 MACROECONOMIC OUTLOOK FOR NORTH AMERICA
             12.2.2 US
                        12.2.2.1 Government-led initiatives to boost semiconductor manufacturing to drive market
             12.2.3 CANADA
                        12.2.3.1 Growing emphasis on commercializing AI to spur demand
             12.2.4 MEXICO
                        12.2.4.1 Increasing shift toward digital platforms and cloud-based solutions to accelerate demand
     12.3 EUROPE 
             12.3.1 MACROECONOMIC OUTLOOK FOR EUROPE
             12.3.2 UK
                        12.3.2.1 Growing investments in data center infrastructure to boost demand
             12.3.3 GERMANY
                        12.3.3.1 Presence of robust industrial base to offer lucrative growth opportunities
             12.3.4 FRANCE
                        12.3.4.1 Increasing number of AI startups to accelerate demand
             12.3.5 ITALY
                        12.3.5.1 Rising adoption of digitalization in automotive and healthcare sectors to drive market
             12.3.6 SPAIN
                        12.3.6.1 Growing collaborations and partnerships among AI manufacturers to spur demand
             12.3.7 REST OF EUROPE
     12.4 ASIA PACIFIC 
             12.4.1 MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
             12.4.2 CHINA
                        12.4.2.1 Surge in research funding and implementation of supportive regulatory policy to augment market growth
             12.4.3 JAPAN
                        12.4.3.1 Rising adoption of AI chips to advance robotic systems to offer lucrative growth opportunities
             12.4.4 INDIA
                        12.4.4.1 Government-led initiatives to boost AI infrastructure to foster market growth
             12.4.5 SOUTH KOREA
                        12.4.5.1 Thriving semiconductor industry to drive market growth
             12.4.6 REST OF ASIA PACIFIC
     12.5 ROW 
             12.5.1 MACROECONOMIC OUTLOOK FOR ROW
             12.5.2 MIDDLE EAST
                        12.5.2.1 Growing emphasis on digital transformation and technological innovation to drive market growth
                        12.5.2.2 GCC countries
                        12.5.2.3 Rest of Middle East
             12.5.3 AFRICA
                        12.5.3.1 Rising internet penetration and mobile subscriptions to offer lucrative growth opportunities
             12.5.4 SOUTH AMERICA
                        12.5.4.1 Growing need to store vast volumes of data to boost demand
 
13 COMPETITIVE LANDSCAPE (Page No. - 207)
     13.1 INTRODUCTION 
     13.2 KEY PLAYER STRATEGIES/RIGHT TO WIN, 2019–2024 
     13.3 REVENUE ANALYSIS, 2021–2023 
     13.4 MARKET SHARE ANALYSIS, 2023 
     13.5 COMPANY VALUATION AND FINANCIAL METRICS 
     13.6 BRAND/PRODUCT COMPARISON 
     13.7 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2023 
             13.7.1 STARS
             13.7.2 EMERGING LEADERS
             13.7.3 PERVASIVE PLAYERS
             13.7.4 PARTICIPANTS
             13.7.5 COMPANY FOOTPRINT: KEY PLAYERS, 2023
                        13.7.5.1 Company footprint
                        13.7.5.2 Compute footprint
                        13.7.5.3 Memory footprint
                        13.7.5.4 Network footprint
                        13.7.5.5 Technology footprint
                        13.7.5.6 Function footprint
                        13.7.5.7 End user footprint
                        13.7.5.8 Region footprint
     13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023 
             13.8.1 PROGRESSIVE COMPANIES
             13.8.2 RESPONSIVE COMPANIES
             13.8.3 DYNAMIC COMPANIES
             13.8.4 STARTING BLOCKS
             13.8.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
                        13.8.5.1 Detailed list of key startups/SMEs
                        13.8.5.2 Competitive benchmarking of key startups/SMEs
     13.9 COMPETITIVE SCENARIO 
             13.9.1 PRODUCT LAUNCHES
             13.9.2 DEALS
 
14 COMPANY PROFILES (Page No. - 256)
     14.1 KEY PLAYERS 
             14.1.1 NVIDIA CORPORATION
                        14.1.1.1 Business overview
                        14.1.1.2 Products/Solutions/Services offered
                        14.1.1.3 Recent developments
                                     14.1.1.3.1 Product launches
                                     14.1.1.3.2 Deals
                        14.1.1.4 MnM view
                                     14.1.1.4.1 Key strengths
                                     14.1.1.4.2 Strategic choices
                                     14.1.1.4.3 Weaknesses and competitive threats
             14.1.2 ADVANCED MICRO DEVICES, INC.
                        14.1.2.1 Business overview
                        14.1.2.2 Products/Solutions/Services offered
                        14.1.2.3 Recent developments
                                     14.1.2.3.1 Product launches
                                     14.1.2.3.2 Deals
                        14.1.2.4 MnM view
                                     14.1.2.4.1 Key strengths
                                     14.1.2.4.2 Strategic choices
                                     14.1.2.4.3 Weaknesses and competitive threats
             14.1.3 INTEL CORPORATION
                        14.1.3.1 Business overview
                        14.1.3.2 Products/Solutions/Services offered
                        14.1.3.3 Recent developments
                                     14.1.3.3.1 Product launches
                                     14.1.3.3.2 Deals
                                     14.1.3.3.3 Other developments
                        14.1.3.4 MnM view
                                     14.1.3.4.1 Key strengths
                                     14.1.3.4.2 Strategic choices
                                     14.1.3.4.3 Weaknesses and competitive threats
             14.1.4 SK HYNIX INC.
                        14.1.4.1 Business overview
                        14.1.4.2 Products/Solutions/Services offered
                        14.1.4.3 Recent developments
                                     14.1.4.3.1 Product launches
                                     14.1.4.3.2 Deals
                                     14.1.4.3.3 Other developments
                        14.1.4.4 MnM view
                                     14.1.4.4.1 Key strengths
                                     14.1.4.4.2 Strategic choices
                                     14.1.4.4.3 Weaknesses and competitive threats
             14.1.5 SAMSUNG
                        14.1.5.1 Business overview
                        14.1.5.2 Products/Solutions/Services offered
                        14.1.5.3 Recent developments
                                     14.1.5.3.1 Product launches
                                     14.1.5.3.2 Deals
                        14.1.5.4 MnM view
                                     14.1.5.4.1 Key strengths
                                     14.1.5.4.2 Strategic choices
                                     14.1.5.4.3 Weaknesses and competitive threats
             14.1.6 MICRON TECHNOLOGY, INC.
                        14.1.6.1 Business overview
                        14.1.6.2 Products/Solutions/Services offered
                        14.1.6.3 Recent developments
                                     14.1.6.3.1 Product launches
                                     14.1.6.3.2 Deals
             14.1.7 APPLE INC.
                        14.1.7.1 Business overview
                        14.1.7.2 Products/Solutions/Services offered
                        14.1.7.3 Recent developments
                                     14.1.7.3.1 Product launches
                                     14.1.7.3.2 Deals
             14.1.8 QUALCOMM TECHNOLOGIES, INC.
                        14.1.8.1 Business overview
                        14.1.8.2 Products/Solutions/Services offered
                        14.1.8.3 Recent developments
                                     14.1.8.3.1 Product launches
                                     14.1.8.3.2 Deals
             14.1.9 HUAWEI TECHNOLOGIES CO., LTD.
                        14.1.9.1 Business overview
                        14.1.9.2 Products/Solutions/Services offered
                        14.1.9.3 Recent developments
                                     14.1.9.3.1 Product launches
                                     14.1.9.3.2 Deals
             14.1.10 GOOGLE
                        14.1.10.1 Business overview
                        14.1.10.2 Products/Solutions/Services offered
                        14.1.10.3 Recent developments
                                     14.1.10.3.1 Product launches
                                     14.1.10.3.2 Deals
             14.1.11 AMAZON WEB SERVICES, INC.
                        14.1.11.1 Business overview
                        14.1.11.2 Products/Solutions/Services offered
                        14.1.11.3 Recent developments
                                     14.1.11.3.1 Product launches
                                     14.1.11.3.2 Deals
             14.1.12 TESLA
                        14.1.12.1 Business overview
                        14.1.12.2 Products/Solutions/Services offered
             14.1.13 MICROSOFT
                        14.1.13.1 Business overview
 
                        14.1.13.3 Recent developments
                                     14.1.13.3.1 Product launches
                                     14.1.13.3.2 Deals
             14.1.14 META
                        14.1.14.1 Business overview
                        14.1.14.2 Products/Solutions/Services offered
                        14.1.14.3 Recent developments
                                     14.1.14.3.1 Product launches
                                     14.1.14.3.2 Deals
             14.1.15 T-HEAD
                        14.1.15.1 Business overview
                        14.1.15.2 Products/Solutions/Services offered
             14.1.16 IMAGINATION TECHNOLOGIES
                        14.1.16.1 Business overview
                        14.1.16.2 Products/Solutions/Services offered
                        14.1.16.3 Recent developments
                                     14.1.16.3.1 Product launches
                                     14.1.16.3.2 Deals
             14.1.17 GRAPHCORE
                        14.1.17.1 Business overview
                        14.1.17.2 Products/Solutions/Services offered
                        14.1.17.3 Recent developments
                                     14.1.17.3.1 Product launches
                                     14.1.17.3.2 Deals
             14.1.18 CEREBRAS
                        14.1.18.1 Business overview
                        14.1.18.2 Products/Solutions/Services offered
                        14.1.18.3 Recent developments
                                     14.1.18.3.1 Product launches
                                     14.1.18.3.2 Deals
     14.2 OTHER PLAYERS 
             14.2.1 MYTHIC
             14.2.2 KALRAY
             14.2.3 BLAIZE
             14.2.4 GROQ, INC.
             14.2.5 HAILO TECHNOLOGIES LTD
             14.2.6 GREENWAVES TECHNOLOGIES
             14.2.7 SIMA TECHNOLOGIES, INC.
             14.2.8 KNERON, INC.
             14.2.9 RAIN NEUROMORPHICS INC.
             14.2.10 TENSTORRENT
             14.2.11 SAMBANOVA SYSTEMS, INC.
             14.2.12 TAALAS
             14.2.13 SAPEON INC.
             14.2.14 REBELLIONS INC.
             14.2.15 RIVOS INC.
             14.2.16 SHANGHAI BIREN TECHNOLOGY CO., LTD.
 
15 APPENDIX (Page No. - 351)
     15.1 DISCUSSION GUIDE 
     15.2 KNOWLEDGESTORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 
     15.3 CUSTOMIZATION OPTIONS 
     15.4 RELATED REPORTS 
     15.5 AUTHOR DETAILS 
 
LIST OF TABLES (214)
 
TABLE 1 AI CHIP MARKET: RESEARCH ASSUMPTIONS
TABLE 2 AI CHIP MARKET: RISK ANALYSIS
TABLE 3 BLACKWELL PLATFORM OF NVIDIA TO EXCEED TDP OF 1 KW
TABLE 4 INDICATIVE PRICING TREND OF COMPUTE OFFERED BY KEY PLAYERS, 2023 (USD)
TABLE 5 INDICATIVE PRICING TREND OF COMPUTE, 2020–2023 (USD)
TABLE 6 AVERAGE SELLING PRICE TREND OF GPU, BY REGION, 2020–2023 (USD)
TABLE 7 AVERAGE SELLING PRICE TREND OF CPU, BY REGION, 2020–2023 (USD)
TABLE 8 AVERAGE SELLING PRICE TREND OF FPGA, BY REGION, 2020–2023 (USD)
TABLE 9 AI CHIP MARKET: ROLE OF COMPANIES IN ECOSYSTEM
TABLE 10 CPU SERVER BILL OF MATERIAL (BOM), 2023
TABLE 11 GPU/AI SERVERS COST STRUCTURE FOR NVIDIA’S ‘A100’, 2023
TABLE 12 GPU/AI SERVERS COST STRUCTURE FOR NVIDIA’S ‘H100’, 2023
TABLE 13 COMPARISON OF NVIDIA AI GPU SPECIFICATIONS
TABLE 14 COMPARISON OF CPU SPECIFICATIONS
TABLE 15 AI CHIP MARKET: LIST OF MAJOR PATENTS
TABLE 16 IMPORT DATA FOR HS CODE 854231-COMPLIANT PRODUCTS, BY COUNTRY, 2019–2023 (USD MILLION)
TABLE 17 EXPORT DATA FOR HS CODE 854231-COMPLIANT PRODUCTS, BY COUNTRY, 2019–2023 (USD MILLION)
TABLE 18 AI CHIP MARKET: KEY CONFERENCES AND EVENTS
TABLE 19 NORTH AMERICA: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 20 EUROPE: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 21 ASIA PACIFIC: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 22 ROW: LIST OF REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
TABLE 23 AI CHIP MARKET: STANDARDS
TABLE 24 AI CHIP MARKET: PORTER’S FIVE FORCES ANALYSIS
TABLE 25 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END USERS (%)
TABLE 26 KEY BUYING CRITERIA FOR TOP THREE END USERS
TABLE 27 AI CHIP MARKET, BY COMPUTE, 2020–2023 (USD MILLION)
TABLE 28 AI CHIP MARKET, BY COMPUTE, 2024–2029 (USD MILLION)
TABLE 29 AI CHIP MARKET, BY COMPUTE, 2020–2023 (THOUSAND UNITS)
TABLE 30 AI CHIP MARKET, BY COMPUTE, 2024–2029 (THOUSAND UNITS)
TABLE 31 GPU: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 32 GPU: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 33 CPU: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 34 CPU: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 35 FPGA: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 36 FPGA: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 37 NPU: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 38 NPU: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 39 AI CHIP MARKET, BY MEMORY, 2020–2023 (USD MILLION)
TABLE 40 AI CHIP MARKET, BY MEMORY, 2024–2029 (USD MILLION)
TABLE 41 AI CHIP MARKET, BY MEMORY, 2020–2023 (PETABYTE)
TABLE 42 AI CHIP MARKET, BY MEMORY, 2024–2029 (PETABYTE)
TABLE 43 AI CHIP MARKET FOR MEMORY, BY REGION, 2020–2023 (USD MILLION)
TABLE 44 AI CHIP MARKET FOR MEMORY, BY REGION, 2024–2029 (USD MILLION)
TABLE 45 AI CHIP MARKET, BY NETWORK, 2020–2023 (USD MILLION)
TABLE 46 AI CHIP MARKET, BY NETWORK, 2024–2029 (USD MILLION)
TABLE 47 AI CHIP MARKET, BY NETWORK, 2020–2023 (THOUSAND UNITS)
TABLE 48 AI CHIP MARKET, BY NETWORK, 2024–2029 (THOUSAND UNITS)
TABLE 49 AI CHIP MARKET FOR NETWORK, BY REGION, 2020–2023 (USD MILLION)
TABLE 50 AI CHIP MARKET FOR NETWORK, BY REGION, 2024–2029 (USD MILLION)
TABLE 51 NIC/NETWORK ADAPTERS: AI CHIP MARKET, BY TYPE, 2020–2023 (USD MILLION)
TABLE 52 NIC/NETWORK ADAPTERS: AI CHIP MARKET, BY TYPE, 2024–2029 (USD MILLION)
TABLE 53 NIC/NETWORK ADAPTERS: AI CHIP MARKET, BY TYPE, 2020–2023 (THOUSAND UNITS)
TABLE 54 NIC/NETWORK ADAPTERS: AI CHIP MARKET, BY TYPE, 2024–2029 (THOUSAND UNITS)
TABLE 55 AI CHIP MARKET, BY TECHNOLOGY, 2020–2023 (USD MILLION)
TABLE 56 AI CHIP MARKET, BY TECHNOLOGY, 2024–2029 (USD MILLION)
TABLE 57 GENERATIVE AI: AI CHIP MARKET, BY TECHNOLOGY TYPE, 2020–2023 (USD MILLION)
TABLE 58 GENERATIVE AI: AI CHIP MARKET, BY TECHNOLOGY TYPE, 2024–2029 (USD MILLION)
TABLE 59 AI CHIP MARKET, BY FUNCTION, 2020–2023 (USD MILLION)
TABLE 60 AI CHIP MARKET, BY FUNCTION, 2024–2029 (USD MILLION)
TABLE 61 AI CHIP MARKET FOR COMPUTE, BY FUNCTION, 2020–2023 (THOUSAND UNITS)
TABLE 62 AI CHIP MARKET FOR COMPUTE, BY FUNCTION, 2024–2029 (THOUSAND UNITS)
TABLE 63 AI CHIP MARKET, BY END USER, 2020–2023 (USD MILLION)
TABLE 64 AI CHIP MARKET, BY END USER, 2024–2029 (USD MILLION)
TABLE 65 CONSUMER: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 66 CONSUMER: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 67 DATA CENTERS: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 68 DATA CENTERS: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 69 CLOUD SERVICE PROVIDERS: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 70 CLOUD SERVICE PROVIDERS: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 71 ENTERPRISES: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 72 ENTERPRISES: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 73 HEALTHCARE: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 74 HEALTHCARE: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 75 BFSI: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 76 BFSI: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 77 AUTOMOTIVE: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 78 AUTOMOTIVE: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 79 RETAIL & ECOMMERCE: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 80 RETAIL & ECOMMERCE: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 81 MEDIA & ENTERTAINMENT: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 82 MEDIA & ENTERTAINMENT: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 83 OTHERS: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 84 OTHERS: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 85 GOVERNMENT ORGANIZATIONS: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 86 GOVERNMENT ORGANIZATIONS: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 87 AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 88 AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 89 NORTH AMERICA: AI CHIP MARKET, BY COUNTRY, 2020–2023 (USD MILLION)
TABLE 90 NORTH AMERICA: AI CHIP MARKET, BY COUNTRY, 2024–2029 (USD MILLION)
TABLE 91 NORTH AMERICA: AI CHIP MARKET, BY END USER, 2020–2023 (USD MILLION)
TABLE 92 NORTH AMERICA: AI CHIP MARKET, BY END USER, 2024–2029 (USD MILLION)
TABLE 93 NORTH AMERICA: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2020–2023 (USD MILLION)
TABLE 94 NORTH AMERICA: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2024–2029 (USD MILLION)
TABLE 95 NORTH AMERICA: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2020–2023 (USD MILLION)
TABLE 96 NORTH AMERICA: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2024–2029 (USD MILLION)
TABLE 97 NORTH AMERICA: AI CHIP MARKET, BY COMPUTE, 2020–2023 (USD MILLION)
TABLE 98 NORTH AMERICA: AI CHIP MARKET, BY COMPUTE, 2024–2029 (USD MILLION)
TABLE 99 EUROPE: AI CHIP MARKET, BY COUNTRY, 2020–2023 (USD MILLION)
TABLE 100 EUROPE: AI CHIP MARKET, BY COUNTRY, 2024–2029 (USD MILLION)
TABLE 101 EUROPE: AI CHIP MARKET, BY END USER, 2020–2023 (USD MILLION)
TABLE 102 EUROPE: AI CHIP MARKET, BY END USER, 2024–2029 (USD MILLION)
TABLE 103 EUROPE: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2020–2023 (USD MILLION)
TABLE 104 EUROPE: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2024–2029 (USD MILLION)
TABLE 105 EUROPE: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2020–2023 (USD MILLION)
TABLE 106 EUROPE: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2024–2029 (USD MILLION)
TABLE 107 EUROPE: AI CHIP MARKET, BY COMPUTE, 2020–2023 (USD MILLION)
TABLE 108 EUROPE: AI CHIP MARKET, BY COMPUTE, 2024–2029 (USD MILLION)
TABLE 109 ASIA PACIFIC: AI CHIP MARKET, BY COUNTRY, 2020–2023 (USD MILLION)
TABLE 110 ASIA PACIFIC: AI CHIP MARKET, BY COUNTRY, 2024–2029 (USD MILLION)
TABLE 111 ASIA PACIFIC: AI CHIP MARKET, BY END USER, 2020–2023 (USD MILLION)
TABLE 112 ASIA PACIFIC: AI CHIP MARKET, BY END USER, 2024–2029 (USD MILLION)
TABLE 113 ASIA PACIFIC: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2020–2023 (USD MILLION)
TABLE 114 ASIA PACIFIC: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2024–2029 (USD MILLION)
TABLE 115 ASIA PACIFIC: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2020–2023 (USD MILLION)
TABLE 116 ASIA PACIFIC: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2024–2029 (USD MILLION)
TABLE 117 ASIA PACIFIC: AI CHIP MARKET, BY COMPUTE, 2020–2023 (USD MILLION)
TABLE 118 ASIA PACIFIC: AI CHIP MARKET, BY COMPUTE, 2024–2029 (USD MILLION)
TABLE 119 ROW: AI CHIP MARKET, BY REGION, 2020–2023 (USD MILLION)
TABLE 120 ROW: AI CHIP MARKET, BY REGION, 2024–2029 (USD MILLION)
TABLE 121 ROW: AI CHIP MARKET, BY END USER, 2020–2023 (USD THOUSAND)
TABLE 122 ROW: AI CHIP MARKET, BY END USER, 2024–2029 (USD THOUSAND)
TABLE 123 ROW: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2020–2023 (USD THOUSAND)
TABLE 124 ROW: AI CHIP MARKET FOR DATA CENTERS, BY END USER, 2024–2029 (USD THOUSAND)
TABLE 125 ROW: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2020–2023 (USD THOUSAND)
TABLE 126 ROW: AI CHIP MARKET FOR ENTERPRISES, BY END USER, 2024–2029 (USD THOUSAND)
TABLE 127 ROW: AI CHIP MARKET, BY COMPUTE, 2020–2023 (USD MILLION)
TABLE 128 ROW: AI CHIP MARKET, BY COMPUTE, 2024–2029 (USD MILLION)
TABLE 129 MIDDLE EAST: AI CHIP MARKET, BY COUNTRY, 2020–2023 (USD MILLION)
TABLE 130 MIDDLE EAST: AI CHIP MARKET, BY COUNTRY, 2024–2029 (USD MILLION)
TABLE 131 AI CHIP MARKET: OVERVIEW OF STRATEGIES ADOPTED BY KEY PLAYERS, 2019–2024
TABLE 132 COMPUTE MARKET: DEGREE OF COMPETITION
TABLE 133 MEMORY (HBM) MARKET: DEGREE OF COMPETITION
TABLE 134 AI CHIP MARKET: COMPUTE FOOTPRINT
TABLE 135 AI CHIP MARKET: MEMORY FOOTPRINT
TABLE 136 AI CHIP MARKET: NETWORK FOOTPRINT
TABLE 137 AI CHIP MARKET: TECHNOLOGY FOOTPRINT
TABLE 138 AI CHIP MARKET: FUNCTION FOOTPRINT
TABLE 139 AI CHIP MARKET: END USER FOOTPRINT
TABLE 140 AI CHIP MARKET: REGION FOOTPRINT
TABLE 141 AI CHIP MARKET: DETAILED LIST OF KEY STARTUPS/SMES, 2023
TABLE 142 AI CHIP MARKET: COMPETITIVE BENCHMARKING OF KEY STARTUPS/SMES, 2023
TABLE 143 AI CHIP MARKET: PRODUCT LAUNCHES, FEBRUARY 2019–JULY 2024
TABLE 144 AI CHIP MARKET: DEALS, FEBRUARY 2019–JULY 2024
TABLE 145 NVIDIA CORPORATION: COMPANY OVERVIEW
TABLE 146 NVIDIA CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 147 NVIDIA CORPORATION: PRODUCT LAUNCHES
TABLE 148 NVIDIA CORPORATION: DEALS
TABLE 149 ADVANCED MICRO DEVICES, INC.: COMPANY OVERVIEW
TABLE 150 ADVANCED MICRO DEVICES, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 151 ADVANCED MICRO DEVICES, INC.: PRODUCT LAUNCHES
TABLE 152 ADVANCED MICRO DEVICES, INC.: DEALS
TABLE 153 INTEL CORPORATION: COMPANY OVERVIEW
TABLE 154 INTEL CORPORATION: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 155 INTEL CORPORATION: PRODUCT LAUNCHES
TABLE 156 INTEL CORPORATION: DEALS
TABLE 157 INTEL CORPORATION: OTHER DEVELOPMENTS
TABLE 158 SK HYNIX INC.: COMPANY OVERVIEW
TABLE 159 SK HYNIX INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 160 SK HYNIX INC.: PRODUCT LAUNCHES
TABLE 161 SK HYNIX INC.: DEALS
TABLE 162 SK HYNIX INC.: OTHER DEVELOPMENTS
TABLE 163 SAMSUNG: COMPANY OVERVIEW
TABLE 164 SAMSUNG: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 165 SAMSUNG: PRODUCT LAUNCHES
TABLE 166 SAMSUNG: DEALS
TABLE 167 MICRON TECHNOLOGY, INC.: COMPANY OVERVIEW
TABLE 168 MICRON TECHNOLOGY, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 169 MICRON TECHNOLOGY, INC.: PRODUCT LAUNCHES
TABLE 170 MICRON TECHNOLOGY, INC.: DEALS
TABLE 171 APPLE INC.: COMPANY OVERVIEW
TABLE 172 APPLE INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 173 APPLE INC.: PRODUCT LAUNCHES
TABLE 174 APPLE INC.: DEALS
TABLE 175 QUALCOMM TECHNOLOGIES, INC.: COMPANY OVERVIEW
TABLE 176 QUALCOMM TECHNOLOGIES, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 177 QUALCOMM TECHNOLOGIES, INC.: PRODUCT LAUNCHES
TABLE 178 QUALCOMM TECHNOLOGIES, INC.: DEALS
TABLE 179 HUAWEI TECHNOLOGIES CO., LTD.: COMPANY OVERVIEW
TABLE 180 HUAWEI TECHNOLOGIES CO., LTD.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 181 HUAWEI TECHNOLOGIES CO., LTD.: PRODUCT LAUNCHES
TABLE 182 HUAWEI TECHNOLOGIES CO., LTD.: DEALS
TABLE 183 GOOGLE: COMPANY OVERVIEW
TABLE 184 GOOGLE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 185 GOOGLE: PRODUCT LAUNCHES
TABLE 186 GOOGLE: DEALS
TABLE 187 AMAZON WEB SERVICES, INC.: COMPANY OVERVIEW
TABLE 188 AMAZON WEB SERVICES, INC.: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 189 AMAZON WEB SERVICES, INC.: PRODUCT LAUNCHES
TABLE 190 AMAZON WEB SERVICES, INC.: DEALS
TABLE 191 TESLA: COMPANY OVERVIEW
TABLE 192 TESLA: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 193 MICROSOFT: COMPANY OVERVIEW
TABLE 194 MICROSOFT: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 195 MICROSOFT: PRODUCT LAUNCHES
TABLE 196 MICROSOFT: DEALS
TABLE 197 META: COMPANY OVERVIEW
TABLE 198 META: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 199 META: PRODUCT LAUNCHES
TABLE 200 META: DEALS
TABLE 201 T-HEAD: COMPANY OVERVIEW
TABLE 202 T-HEAD: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 203 IMAGINATION TECHNOLOGIES: COMPANY OVERVIEW
TABLE 204 IMAGINATION TECHNOLOGIES: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 205 IMAGINATION TECHNOLOGIES: PRODUCT LAUNCHES
TABLE 206 IMAGINATION TECHNOLOGIES: DEALS
TABLE 207 GRAPHCORE: COMPANY OVERVIEW
TABLE 208 GRAPHCORE: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 209 GRAPHCORE: PRODUCT LAUNCHES
TABLE 210 GRAPHCORE: DEALS
TABLE 211 CEREBRAS: COMPANY OVERVIEW
TABLE 212 CEREBRAS: PRODUCTS/SOLUTIONS/SERVICES OFFERED
TABLE 213 CEREBRAS: PRODUCT LAUNCHES
TABLE 214 CEREBRAS: DEALS
 
 
LIST OF FIGURES (92 FIGURES)
 
FIGURE 1 AI CHIP MARKET: SEGMENTATION AND REGIONAL SCOPE
FIGURE 2 AI CHIP MARKET: RESEARCH DESIGN
FIGURE 3 AI CHIP MARKET: RESEARCH FLOW
FIGURE 4 REVENUE GENERATED FROM SALES OF AI CHIPS IN 2023
FIGURE 5 AI CHIP MARKET: REVENUE ANALYSIS OF NVIDIA CORPORATION
FIGURE 6 AI CHIP MARKET: BOTTOM-UP APPROACH
FIGURE 7 AI CHIP MARKET: TOP-DOWN APPROACH
FIGURE 8 AI CHIP MARKET: DATA TRIANGULATION
FIGURE 9 GPU SEGMENT TO CAPTURE LARGEST MARKET SHARE IN 2029
FIGURE 10 HBM SEGMENT TO GROW AT HIGHER CAGR DURING FORECAST PERIOD
FIGURE 11 NIC/NETWORK ADAPTERS TO ACCOUNT FOR LARGER MARKET SHARE IN 2029
FIGURE 12 GENERATIVE AI SEGMENT TO GROW AT HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 13 INFERENCE SEGMENT TO CAPTURE LARGER MARKET SHARE IN 2029
FIGURE 14 DATA CENTERS SEGMENT TO SECURE LARGEST MARKET SHARE IN 2024
FIGURE 15 NORTH AMERICA DOMINATED GLOBAL AI CHIP MARKET IN 2023
FIGURE 16 RISING DEMAND FOR AI CHIPS AMONG CLOUD SERVICE PROVIDERS TO DRIVE MARKET
FIGURE 17 GPU SEGMENT TO DOMINATE MARKET IN 2024
FIGURE 18 HBM SEGMENT TO HOLD LARGER MARKET SHARE DURING FORECAST PERIOD
FIGURE 19 NIC/NETWORK ADAPTERS SEGMENT TO RECORD HIGHER CAGR DURING FORECAST PERIOD
FIGURE 20 MACHINE LEARNING AND INFERENCE SEGMENTS TO HOLD LARGEST MARKET SHARES IN 2024
FIGURE 21 DATA CENTERS TO WITNESS HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 22 ASIA PACIFIC TO REGISTER HIGHEST CAGR DURING FORECAST PERIOD
FIGURE 23 CHINA TO RECORD HIGHEST CAGR IN GLOBAL AI CHIP MARKET DURING FORECAST PERIOD
FIGURE 24 AI CHIP MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
FIGURE 25 MOBILE DATA TRAFFIC, 2022–2029
FIGURE 26 AI CHIP MARKET: IMPACT ANALYSIS OF DRIVERS
FIGURE 27 NVIDIA’S DATACENTER GPU POWER CONSUMPTION IN TDP
FIGURE 28 INTEL DATACENTER GPU POWER CONSUMPTION IN TDP
FIGURE 29 AI CHIP MARKET: IMPACT ANALYSIS OF RESTRAINTS
FIGURE 30 AI CHIP MARKET: IMPACT ANALYSIS OF OPPORTUNITIES
FIGURE 31 AI CHIP MARKET: IMPACT ANALYSIS OF CHALLENGES
FIGURE 32 TRENDS/DISRUPTIONS INFLUENCING CUSTOMER BUSINESS
FIGURE 33 AVERAGE SELLING PRICE TREND OF COMPUTE PROVIDED BY KEY PLAYERS, 2023
FIGURE 34 AVERAGE SELLING PRICE TREND OF GPU, BY REGION, 2020–2023
FIGURE 35 AVERAGE SELLING PRICE TREND OF CPU, BY REGION, 2020–2023
FIGURE 36 AVERAGE SELLING PRICE TREND OF FPGA, BY REGION, 2020–2023
FIGURE 37 AI CHIP MARKET: VALUE CHAIN ANALYSIS
FIGURE 38 AI CHIP MARKET: ECOSYSTEM ANALYSIS
FIGURE 39 INVESTMENT AND FUNDING IN AI CHIPS INDUSTRY, 2023–2024
FIGURE 40 NVIDIA AI CHIPS WITH HIGH-BANDWIDTH MEMORY
FIGURE 41 CPU SERVER: BILL OF MATERIAL (BOM) SHARE, 2023
FIGURE 42 NVIDIA A100 SERVER: BILL OF MATERIAL (BOM) SHARE, 2023
FIGURE 43 NVIDIA H100 SERVER: BILL OF MATERIAL (BOM) SHARE, 2023
FIGURE 44 GLOBAL OVERALL SERVER AND AI SERVER SHIPMENT, 2023–2029 (THOUSAND UNITS)
FIGURE 45 UPCOMING DEPLOYMENT OF DATA CENTERS BY CLOUD SERVICE PROVIDERS (CSPS) IN VARIOUS REGIONS
FIGURE 46 CAPEX AND IT EQUIPMENT SPENDS BY GLOBAL CSPS/HYPERSCALERS, 2020–2029 (USD BILLION)
FIGURE 47 CAPEX OF GLOBAL TOP CSPS/HYPERSCALERS, 2023
FIGURE 48 GLOBAL IT EQUIPMENT SPENDS BY CSP/HYPERSCALERS, 2023
FIGURE 49 AI SERVER PROCUREMENT BY CSPS, 2020–2029 (THOUSAND UNITS)
FIGURE 50 NUMBER OF PATENTS GRANTED PER YEAR, 2013–2023
FIGURE 51 IMPORT DATA FOR HS CODE 854231-COMPLIANT PRODUCTS FOR TOP FIVE COUNTRIES, 2019–2023
FIGURE 52 EXPORT DATA FOR HS CODE 854231-COMPLIANT PRODUCTS FOR TOP FIVE COUNTRIES, 2019–2023
FIGURE 53 AI CHIP MARKET: PORTER’S FIVE FORCES ANALYSIS
FIGURE 54 INFLUENCE OF STAKEHOLDERS ON BUYING PROCESS FOR TOP THREE END USERS
FIGURE 55 KEY BUYING CRITERIA FOR TOP THREE END USERS
FIGURE 56 GPU SEGMENT TO HOLD LARGER MARKET SHARE DURING FORECAST PERIOD
FIGURE 57 HBM SEGMENT TO ACCOUNT FOR LARGER MARKET SHARE DURING FORECAST PERIOD
FIGURE 58 NIC/NETWORK ADAPTERS TO REGISTER HIGHER CAGR DURING FORECAST PERIOD
FIGURE 59 MACHINE LEARNING SEGMENT TO HOLD LARGEST MARKET SHARE DURING FORECAST PERIOD
FIGURE 60 INFERENCE SEGMENT TO HOLD LARGER MARKET SHARE DURING FORECAST PERIOD
FIGURE 61 DATA CENTERS TO HOLD LARGEST MARKET SHARE DURING FORECAST PERIOD
FIGURE 62 ASIA PACIFIC TO BE FASTEST-GROWING MARKET DURING FORECAST PERIOD
FIGURE 63 NORTH AMERICA: AI CHIP MARKET SNAPSHOT
FIGURE 64 US TO ACCOUNT FOR LARGEST SHARE OF NORTH AMERICAN AI CHIP MARKET THROUGHOUT FORECAST PERIOD
FIGURE 65 EUROPE: AI CHIP MARKET SNAPSHOT
FIGURE 66 GERMANY TO EXHIBIT HIGHEST CAGR IN EUROPEAN MARKET DURING FORECAST PERIOD
FIGURE 67 ASIA PACIFIC: AI CHIP MARKET SNAPSHOT
FIGURE 68 CHINA TO EXHIBIT HIGHEST CAGR IN ASIA PACIFIC MARKET DURING FORECAST PERIOD
FIGURE 69 SOUTH AMERICA TO DOMINATE AI CHIP MARKET IN ROW IN 2024
FIGURE 70 AI CHIP MARKET: REVENUE ANALYSIS OF TOP THREE PLAYERS, 2021–2023
FIGURE 71 COMPUTE MARKET SHARE, 2023
FIGURE 72 MEMORY (HBM) MARKET SHARE, 2023
FIGURE 73 AI CHIP MARKET: COMPANY VALUATION
FIGURE 74 AI CHIP MARKET: FINANCIAL METRICS (EV/EBITDA)
FIGURE 75 AI CHIP MARKET: BRAND/PRODUCT COMPARISON
FIGURE 76 AI CHIP MARKET: COMPANY EVALUATION MATRIX (KEY PLAYERS), 2023
FIGURE 77 AI CHIP MARKET: COMPANY FOOTPRINT
FIGURE 78 AI CHIP MARKET: COMPANY EVALUATION MATRIX (STARTUPS/SMES), 2023
FIGURE 79 NVIDIA CORPORATION: COMPANY SNAPSHOT
FIGURE 80 ADVANCED MICRO DEVICES, INC.: COMPANY SNAPSHOT
FIGURE 81 INTEL CORPORATION: COMPANY SNAPSHOT
FIGURE 82 SK HYNIX INC.: COMPANY SNAPSHOT
FIGURE 83 SAMSUNG: COMPANY SNAPSHOT
FIGURE 84 MICRON TECHNOLOGY, INC.: COMPANY SNAPSHOT
FIGURE 85 APPLE INC.: COMPANY SNAPSHOT
FIGURE 86 QUALCOMM TECHNOLOGIES, INC.: COMPANY SNAPSHOT
FIGURE 87 HUAWEI TECHNOLOGIES CO., LTD.: COMPANY SNAPSHOT
FIGURE 88 GOOGLE: COMPANY SNAPSHOT
FIGURE 89 AMAZON WEB SERVICES, INC.: COMPANY SNAPSHOT
FIGURE 90 TESLA: COMPANY SNAPSHOT
FIGURE 91 MICROSOFT: COMPANY SNAPSHOT
FIGURE 92 META: COMPANY SNAPSHOT

 

 

The study involved four major activities in estimating the size for AI Chip market. Exhaustive secondary research was done to collect information on the market, peer market, and parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across value chains through primary research. The bottom-up approach was employed to estimate the overall market size. After that, market breakdown and data triangulation were used to estimate the market size of segments and subsegments.

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

Extensive primary research has been conducted after acquiring knowledge about the AI Chip market scenario through secondary research. Several primary interviews have been conducted with market experts from both the demand and supply sides across four major geographies: North America, Europe, Asia Pacific, and RoW (the Middle East, Africa, and South America). Approximately 60% and 40% of primary interviews were conducted with both the supply and demand sides, respectively. This primary data has been collected through emails, questionnaires, and telephonic interviews.

AI Chip Market
 Size, and Share

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

In the complete market engineering process, both top-down and bottom-up approaches, along with several data triangulation methods, have been used to perform the market size estimation and forecasting for the overall market segments and subsegments listed in this report. Extensive qualitative and quantitative analyses have been conducted on the complete market engineering process to list the key information/insights throughout the report.

The key players in the market such as Intel Corporation (US), NVIDIA Corporation (US), Google (US), Advanced Micro Devices, Inc. (US), and Micron Technology, Inc. (US)  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 players as well as extensive interviews with industry experts (such as CEOs, VPs, directors, and marketing executives) for key insights (both quantitative and qualitative) on the AI Chip market. All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources. All the possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. This data has been consolidated and supplemented with detailed inputs and analysis from MarketsandMarkets and presented in this report.

AI Chip Market: Bottom-Up Approach

AI Chip Market
 Size, and Bottom-Up Approach

The bottom-up approach has been employed to arrive at the overall size of the AI chip market. The bottom-up methodology for AI chip market calculations begins with determining AI chip demand by multiplying AI server numbers by chip attach-rates per server. Average Selling Prices for each AI chip offering type are then identified. Revenues are calculated for each region or country by multiplying the local AI chip demand by the corresponding ASP, considering product billing locations. These regional revenues are summed to provide a global figure. The total market size is derived by combining all calculated revenues.

AI Chip Market: Top-Down Approach

AI Chip Market
 Size, and 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 top-down methodology for the AI chip market analysis starts with the total market size as the foundation. This overall figure is then broken down into percentage splits for key segments such as Function, Technology, and End User. Each of these segments is further divided into geographic regions, providing a clear picture of market distribution across different areas. The analysis then delves deeper, offering region and country-wise splits for each sub-segment. This approach allows for a comprehensive view of the market, starting from the broadest perspective and progressively narrowing down to specific details. This privides an effectively mapped out entire AI chip market landscape, identifying trends, opportunities, and potential growth areas across various dimensions and geographical locations.

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 chip market has been validated using both top-down and bottom-up approaches.

Definition

An AI chip, is a type of specialized AI processor which is designed to efficiently perform the artificial intelligence tasks, particularly in the machine learning, natural language processing, generative AI, computer vision, and neural network computations. These chips are capable of conducting parallel processing in complex AI operations including AI training and inference, allowing for faster executions of AI workloads compard to the general-purpose processors.

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 chip market based on offerings, function, technology, and end-user
  • 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 chip market by volume based on offerings
  • To provide detailed information regarding drivers, restraints, opportunities, and challenges influencing the growth of the market
  • To provide an ecosystem analysis, case study analysis, patent analysis, technology analysis, pricing analysis, Porter's five forces analysis, investment and funding scenario, and regulations pertaining to the market
  • To provide a detailed overview of the value chain analysis of the AI chip ecosystem
  • To strategically analyze micro markets with regard to individual growth trends, prospects, and contributions to the total market
  • To analyze opportunities for stakeholders by identifying high-growth segments of the market
  • To strategically profile the key players, comprehensively analyze their market positions in terms of ranking and core competencies, and provide a competitive landscape of the market
  • To analyze strategic approaches such as product launches, acquisitions, agreements, and partnerships in the AI chip 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)
Custom Market Research Services

We will customize the research for you, in case the report listed above does not meet with your exact requirements. Our custom research will comprehensively cover the business information you require to help you arrive at strategic and profitable business decisions.

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