Al Chip Market 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 2032

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USD 564.87 BN
MARKET SIZE, 2032
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CAGR 15.7%
(2025-2032)
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360
REPORT PAGES
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150
MARKET TABLES

OVERVIEW

artificial-intelligence-chipset-market Overview

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

The AI chip market is projected to reach USD 564.87 billion by 2032 from USD 203.24 billion in 2025, at a CAGR of 15.7% from 2025 to 2032. The growth of the AI chip market is driven by pressing need for large-scale data handling and real-time analytics.

KEY TAKEAWAYS

  • By Region
    North America is estimated to account for a share of 36.4% of the global AI chip market in 2025.
  • By Offering
    By offering, the network segment is expected to register the highest CAGR of 26.7%.
  • By Compute
    By compute, the CPU segment is projected to grow at the fastest rate from 2025 to 2032.
  • By Memory
    By memory, the HBM segment is expected to dominate the market.
  • By Network
    By network, the NIC/network adapters segment is expected to record the fastestgrowth rate during the forecast period.
  • Competitive Landscape - Key Players
    NVIDIA Corporation; Advanced Micro Devices, Inc; Intel Corporation; and Micron Technology, Inc. were identified as star players in the AI chip market (global), given their strong market share and product footprint.
  • Competitive Landscape - Startups
    Companies such as Mythic; Kalray; Blaize; Groq, Inc.; HAILO TECHNOLOGIES LTD; GreenWaves Technologies; SiMa Technologies, Inc; among others have distinguished themselves as key startups and SMEs by securing strong footholds in specialized niche areas, underscoring their potential as emerging market leaders

The AI chip market is experiencing rapid expansion, fueled by soaring demand for high-performance GPUs, accelerators, and specialized processors that power large-scale training, inference, and edge intelligence workloads. Advancements in architectures such as tensor cores, chiplets, optical interconnects, and energy-efficient AI compute are accelerating adoption across cloud, enterprise, automotive, and industrial sectors. Product launches and ecosystem developments, including strategic partnerships between hyperscalers and semiconductor leaders, multi-billion-dollar supply agreements, and co-developed AI accelerator platforms are reshaping competitive dynamics. At the same time, massive investments in advanced packaging, HBM capacity, and next-generation foundry technologies are further propelling innovation and strengthening the market’s long-term growth trajectory.

TRENDS & DISRUPTIONS IMPACTING CUSTOMERS' CUSTOMERS

The AI chip market is reshaping value creation across the technology ecosystem, extending far beyond direct semiconductor buyers. As cloud providers, data center operators, OEMs, and infrastructure vendors integrate advanced AI processors into their platforms, their downstream stakeholders ranging from AI developers and industrial operators to healthcare, automotive, and telecom teams gain access to significantly enhanced computational capabilities. This multi-tier impact ultimately delivers measurable outcomes such as faster inference, improved automation, reduced operating costs, and new intelligent services that accelerate digital transformation across enterprises and consumer markets.

artificial-intelligence-chipset-market Disruptions

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

MARKET DYNAMICS

Drivers
Impact
Level
  • Surging use of GPUs and ASICs in AI servers
  • Pressing need for large-scale data handling and real-time analytics
RESTRAINTS
Impact
Level
  • Computational workloads and power consumption in AI chips
  • Shortage of skilled workforce with technical know-how
OPPORTUNITIES
Impact
Level
  • Increasing investments in AI-enabled data centers by cloud service providers
  • Government initiatives to deploy AI-enabled defense systems
CHALLENGES
Impact
Level
  • Supply chain disruptions
  • Data privacy concerns associated with AI platforms

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

Driver: Surging use of GPUs and ASICs in AI servers

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. 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.

Restraint: Computational workloads and power consumption in AI Chip

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.

Opportunity: Increasing investments in AI-enabled 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: 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.

artificial-intelligence-chipset-market: COMMERCIAL USE CASES ACROSS INDUSTRIES

COMPANY USE CASE DESCRIPTION BENEFITS
OVH SAS integrated 4th Gen AMD EPYC processors into its Bare Metal server lineup to boost performance and reliability for demanding AI inference workloads. The deployment delivered a 15–20% performance uplift, higher resilience, and improved core density, enabling OVH SAS to provide more cost-efficient, high-performance cloud solutions.
Tencent adopted 3rd Gen Intel Xeon Scalable Processors with advanced acceleration features to power its Xiaowei intelligent speech and video service platform, enabling high-quality neural TTS processing. The Intel-optimized solution enhanced speech synthesis performance, delivering faster, more efficient TTS capabilities for enterprises and intelligent device vendors.
AIC deployed AMD EPYC-powered custom servers to build Western Digital’s high-density SSD test and validation chamber, enabling faster and more flexible drive testing in a compact environment. The solution enhanced batch processing speeds, improved overall QA efficiency, and ensured rigorous SSD reliability validation to protect customer data.

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

MARKET ECOSYSTEM

The AI chip ecosystem consists of chip designers (Analog Devices, Texas Instruments, SK HYNIX, Intel, Samsung), semiconductor manufacturers (TSMC, Intel, ASML, Lam Research), chip providers (NVIDIA, AMD, Google, and end users (Siemens, Google, AWS, Microsoft). Designers create advanced processor architectures that are fabricated by manufacturing partners using leading-edge semiconductor equipment. Chip providers deliver high-performance AI accelerators that power cloud, enterprise, and edge applications. End users drive demand for faster compute, energy efficiency, and scalable AI workloads, while close collaboration across the value chain enables continuous innovation and market expansion.

artificial-intelligence-chipset-market Ecosystem

Logos and trademarks shown above are the property of their respective owners. Their use here is for informational and illustrative purposes only.

MARKET SEGMENTS

artificial-intelligence-chipset-market Segments

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

AI Chip Market, by Compute

The GPU segment is expected to hold the largest market share throughout 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 rapid growth of AI applications requires 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.

AI Chip Market, by Function

the inference function accounted for the largest market share and is estimated to register the highest CAGR 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.

AI Chip Market, by Technology

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.

REGION

Asia Pacific to be fastest-growing region in global AI chip 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 AI developments. Additionally, the presence of high-bandwidth memory (HBM) tech giants, such as Samsung (South Korea), Micron Technology Inc. (US), and SK HYNIX (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.

artificial-intelligence-chipset-market Region

artificial-intelligence-chipset-market: COMPANY EVALUATION MATRIX

In the AI chip market matrix, NVIDIA (Star) leads with a dominant market share and a broad, mature product portfolio spanning data center GPUs, AI accelerators, and integrated software ecosystems that power training and inference at scale. Graphcore (Emerging Leader) is gaining strong industry attention with its innovative Intelligence Processing Units (IPUs) and purpose-built architectures for high-efficiency AI computation, positioning itself as a differentiated challenger in specialized workloads. While NVIDIA maintains its leadership through scale, ecosystem depth, and continuous architectural advancements, Graphcore demonstrates clear potential to advance toward the leaders’ quadrant as demand for alternative, energy-efficient AI architectures accelerates across global markets.

artificial-intelligence-chipset-market Evaluation Metrics

Source: Secondary Research, Interviews with Experts, MarketsandMarkets Analysis

KEY MARKET PLAYERS

MARKET SCOPE

REPORT METRIC DETAILS
Market Size in 2024 (Value) USD 123.16 Billion
Market Forecast in 2032 (Value) USD 564.87 Billion
Growth Rate CAGR of 15.7% from 2025-2032
Years Considered 2021-2032
Base Year 2024
Forecast Period 2025-2032
Units Considered Value (USD Billion), Volume (Kiloton)
Report Coverage Revenue Forecast, Company Ranking, Competitive Landscape, Growth Factors, and Trends
Segments Covered
  • By Compute:
    • GPU
    • CPU
    • FPGA
    • NPU
    • Dojo & FSD
    • Trainium & Inferentia
    • Athena ASIC
    • T-Head
    • MTIA
    • LPU
    • Other ASIC
  • By Memory:
    • DDR
    • HBM
  • By Network:
    • NIC/Network Adaptors
    • Interconnects
  • By Technology:
    • Generative AI
    • Machine Learning
    • Natural Language Processing
    • Computer Vision
  • By Function:
    • Training
    • Inference
  • By End User:
    • Consumers
    • Data Centers
    • Government Organizations
Regions Covered North America, Asia Pacific, Europe, South America, Middle East, Africa

WHAT IS IN IT FOR YOU: artificial-intelligence-chipset-market REPORT CONTENT GUIDE

artificial-intelligence-chipset-market Content Guide

DELIVERED CUSTOMIZATIONS

We have successfully delivered the following deep-dive customizations:

CLIENT REQUEST CUSTOMIZATION DELIVERED VALUE ADDS
Hyperscale Cloud Provider
  • Competitive profiling of GPU/CPU/AI accelerator suppliers (performance, pricing, roadmap)
  • Benchmarking of chip deployment across cloud instances
  • Data center footprint and rack-level power benchmarking
  • Optimize hardware procurement strategies
  • Identify cost-efficient compute configurations
  • Address power density and cooling gaps in upcoming AI clusters
AI Hardware OEM (Servers/Workstations)
  • Market adoption benchmarking for GPUs vs AI-optimized CPUs
  • System-level TCO comparisons
  • Component-level integration mapping across data center, edge, and enterprise
  • Accelerate design alignment with market trends
  • Identify high-growth workload segments
  • Reduce bill-of-materials risk by planning multi-vendor adoption
Semiconductor Designer (CPU/GPU/Accelerators)
  • Technical & performance benchmarking across HPC, LLM training, inference workloads
  • Competitive roadmap analysis
  • Forecast of AI accelerator adoption across cloud and enterprise
  • Strengthen positioning in next-generation compute platforms
  • Detect whitespace in AI workloads
  • Support entry into new hyperscale and enterprise verticals
Data Center Operator/Colocation Provider
  • Global and regional capacity mapping for AI-optimized racks
  • Air/liquid cooling readiness analysis
  • Customer adoption mapping (cloud, telecom, enterprise)
  • Identify demand clusters for AI-ready facilities
  • Build differentiated high-density offering
  • Mitigate power and thermal bottlenecks for future deployments
AI Model Developers/Cloud AI Teams
  • Benchmarking of training/inference cost per token across GPUs and accelerators
  • Optimization of hardware selection for model performance
  • Vendor landscape mapping
  • Reduce compute cost for LLM and generative AI training
  • Improve inference efficiency at scale
  • Support model deployment across diverse hardware backends

RECENT DEVELOPMENTS

  • January 2025 : NVIDIA introduced its next-generation Blackwell Ultra GPUs for hyperscale data centers, delivering major improvements in training throughput for large language models. Several cloud providers, including AWS and Google Cloud, announced early integration plans into their AI compute clusters.
  • November 2024 : Intel launched the Xeon 6 platform and updated Gaudi 3 AI accelerators, targeting cost-efficient generative AI training and inference. The company secured partnerships with Dell and Lenovo to integrate the platform into new enterprise AI servers.
  • October 2024 : AMD unveiled the Instinct MI325X accelerator, offering expanded memory and improved efficiency for transformer-based workloads. Microsoft and Meta announced deployments to support scaling of next-gen AI models.
  • August 2024 : TSMC confirmed volume production of its 2 nm process node, enabling advanced AI chips for customers such as Apple and NVIDIA. The node promises significantly lower power consumption and higher transistor density for high-performance AI compute.
  • June 2024 : Google introduced TPU v5p, optimized for large-scale training of multimodal AI systems. The TPU is deployed within Google Cloud’s AI Hypercomputer architecture, offering enhanced interconnect speeds and higher model parallelism.
  • April 2024 : Graphcore expanded its IPU-based compute systems through a partnership with Fujitsu, integrating Graphcore AI platforms into Fujitsu’s enterprise AI infrastructure for inference-intensive workloads.
  • February 2024 : Samsung announced mass production of HBM3E high-bandwidth memory, aimed at next-generation AI accelerators. NVIDIA and AMD were among the first customers to adopt the new memory standard to enhance AI training performance.

Table of Contents

Exclusive indicates content/data unique to MarketsandMarkets and not available with any competitors.

TITLE
PAGE NO
INTRODUCTION
28
RESEARCH METHODOLOGY
34
EXECUTIVE SUMMARY
48
PREMIUM INSIGHTS
54
MARKET OVERVIEW
58
  • 5.1 INTRODUCTION
  • 5.2 MARKET DYNAMICS
    DRIVERS
    - Pressing need for large-scale data handling and real-time analytics
    - Rising adoption of autonomous vehicles
    - Surging use of GPUs and ASICs in AI servers
    - Continuous advancements in machine learning and deep learning technologies
    - Increasing penetration of AI servers
    RESTRAINTS
    - Shortage of skilled workforce with technical know-how
    - Computational workloads and power consumption in AI Chip
    - Unreliability of AI algorithms
    OPPORTUNITIES
    - Elevating demand for AI-based FPGA chips
    - Government initiatives to deploy AI-enabled defense systems
    - Rising trend of AI-driven diagnostics and treatments
    - Increasing investments in AI-enabled data centers by cloud service providers
    - Rise in adoption of AI-based ASIC technology
    CHALLENGES
    - Data privacy concerns associated with AI platforms
    - Availability of limited structured data to develop efficient AI systems
    - Supply chain disruptions
  • 5.3 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
  • 5.4 PRICING ANALYSIS
    AVERAGE SELLING PRICE TREND OF KEY PLAYERS, BY COMPUTE
    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
    KEY TECHNOLOGIES
    - High-bandwidth Memory (HBM)
    - GenAI workload
    COMPLEMENTARY TECHNOLOGIES
    - Data center power management and cooling system
    - High-speed interconnects
    ADJACENT TECHNOLOGIES
    - AI development frameworks
    - Quantum AI
  • 5.9 SERVER COST STRUCTURE/BILL OF MATERIAL
    CPU SERVER
    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
    GPU BENCHMARKING
    CPU BENCHMARKING
  • 5.15 PATENT ANALYSIS
  • 5.16 TRADE ANALYSIS
    IMPORT SCENARIO (HS CODE 854231)
    EXPORT SCENARIO (HS CODE 854231)
  • 5.17 KEY CONFERENCES AND EVENTS, 2024–2025
  • 5.18 CASE STUDY ANALYSIS
    CDW INTEGRATED AMD EPYC SOLUTIONS TO ENSURE ENERGY EFFICIENCY AND OPTIMUM SPACE UTILIZATION
    OVH SAS LEVERAGED AMD EPYC PROCESSOR TO OPTIMIZE PERFORMANCE OF CLOUD SOLUTIONS IN AI WORKLOADS
    INTEL XEON SCALABLE PROCESSORS POWER TENCENT CLOUD’S XIAOWEI INTELLIGENT SPEECH AND VIDEO SERVICE ACCESS PLATFORM
    AIC HELPS WESTERN DIGITAL TO ENHANCE SSD TESTING AND VALIDATION EFFICIENCY USING AMD PROCESSOR
  • 5.19 REGULATORY LANDSCAPE
    REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
    STANDARDS
  • 5.20 PORTER’S FIVE FORCES ANALYSIS
    THREAT OF NEW ENTRANTS
    THREAT OF SUBSTITUTES
    BARGAINING POWER OF SUPPLIERS
    BARGAINING POWER OF BUYERS
    INTENSITY OF COMPETITION RIVALRY
  • 5.21 KEY STAKEHOLDERS AND BUYING CRITERIA
    KEY STAKEHOLDERS IN BUYING PROCESS
    BUYING CRITERIA
AI CHIP MARKET, BY COMPUTE
117
  • 6.1 INTRODUCTION
  • 6.2 GPU
    ABILITY TO HANDLE AI WORKLOADS AND PROCESS VAST DATA VOLUMES TO BOOST ADOPTION
  • 6.3 CPU
    RISING DEMAND FOR VERSATILE AND GENERAL-PURPOSE AI PROCESSING TO AUGMENT MARKET GROWTH
  • 6.4 FPGA
    GROWING NEED FOR FLEXIBILITY AND CUSTOMIZATION FOR AI WORKLOADS TO SPUR DEMAND
  • 6.5 NPU
    RISING DEMAND FOR HIGH-END SMARTPHONES TO DRIVE SEGMENTAL GROWTH
  • 6.6 TPU
    PRESSING NEED FOR FASTER PROCESSING IN AI RESEARCH AND APPLICATION DEVELOPMENT TO BOOST DEMAND
  • 6.7 DOJO & FSD
    ACCELERATING DEMAND FOR HIGH-PERFORMANCE, ENERGY-EFFICIENT AI PROCESSING IN AUTONOMOUS VEHICLES TO FUEL ADOPTION
  • 6.8 TRAINIUM & INFERENTIA
    ABILITY TO TRAIN COMPLEX AI AND DEEP LEARNING MODELS TO DRIVE ADOPTION
  • 6.9 ATHENA ASIC
    INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED AI TASKS TO ACCELERATE MARKET GROWTH
  • 6.10 T-HEAD
    RISING DEMAND FOR CUSTOMIZED, HIGH-PERFORMANCE AI CHIPS ACROSS CHINESE DATA CENTERS TO STIMULATE MARKET GROWTH
  • 6.11 MTIA
    META'S EXPANSION INTO AR, VR, AND METAVERSE TO FUEL MARKET GROWTH
  • 6.12 LPU
    INCREASING NEED TO HANDLE COMPLEX NLP AND LANGUAGE-BASED AI TASKS TO ACCELERATE MARKET GROWTH
  • 6.13 OTHER ASIC
AI CHIP MARKET, BY MEMORY
131
  • 7.1 INTRODUCTION
  • 7.2 DDR
    RISING ADOPTION OF AI-ENABLED CPUS IN DATA CENTERS TO SUPPORT MARKET GROWTH
  • 7.3 HBM
    ELEVATING NEED FOR HIGH THROUGHPUT IN DATA-INTENSIVE AI TASKS TO FUEL MARKET GROWTH
AI CHIP MARKET, BY NETWORK
136
  • 8.1 INTRODUCTION
  • 8.2 NIC/NETWORK ADAPTERS
    INFINIBAND
    - Growing utilization of HPC and AI models to minimize latency and maximize throughput to boost segmental growth
    ETHERNET
    - Rising demand for scalable and cost-effective networking solutions to propel growth
  • 8.3 INTERCONNECTS
    GROWING COMPLEXITY OF AI MODELS REQUIRING HIGH-BANDWIDTH DATA PATHS TO FUEL DEMAND
AI CHIP MARKET, BY TECHNOLOGY
143
  • 9.1 INTRODUCTION
  • 9.2 GENERATIVE AI
    RULE-BASED MODELS
    - Rising need to detect fraud in finance sector to propel market
    STATISTICAL MODELS
    - Requirement to make accurate predictions from complex data structures to boost segmental growth
    DEEP LEARNING
    - Ability to advance AI technologies to boost demand
    GENERATIVE ADVERSARIAL NETWORKS (GAN)
    - Pressing need to handle large-scale data to fuel segmental growth
    AUTOENCODERS
    - Ability to compress and restructure data to ensure optimum storage space in data centers to stimulate demand
    CONVOLUTIONAL NEURAL NETWORKS (CNNS)
    - Surging demand for realistic and high-quality images and videos to accelerate market growth
    TRANSFORMER MODELS
    - Increasing utilization in image synthesis and captioning applications to foster segmental growth
  • 9.3 MACHINE LEARNING
    RISING USE IN IMAGE AND SPEECH RECOGNITION AND PREDICTIVE ANALYTICS TO CONTRIBUTE TO MARKET GROWTH
  • 9.4 NATURAL LANGUAGE PROCESSING
    INCREASING NEED FOR REAL-TIME APPLICATIONS TO SUPPORT MARKET GROWTH
  • 9.5 COMPUTER VISION
    ESCALATING NEED FOR ADVANCED PROCESSING CAPABILITIES TO BOOST DEMAND
AI CHIP MARKET, BY FUNCTION
154
  • 10.1 INTRODUCTION
  • 10.2 TRAINING
    SURGING NEED TO PROCESS LARGE DATA SETS AND PERFORM PARALLEL COMPUTATION TO CREATE OPPORTUNITIES
  • 10.3 INFERENCE
    SURGING DEPLOYMENT ACROSS VARIOUS INDUSTRIES TO BOOST DEMAND
AI CHIP MARKET, BY END USER
159
  • 11.1 INTRODUCTION
  • 11.2 CONSUMER
    GROWING ADOPTION OF AI-ENABLED PERSONAL DEVICES TO PROPEL MARKET
  • 11.3 DATA CENTERS
    CLOUD SERVICE PROVIDERS
    - Surging AI workloads and cloud adoption to stimulate market growth
    ENTERPRISES
    - Escalating use of NLP, image recognition, and predictive analytics to create growth opportunities
    - Healthcare
    - BFSI
    - Automotive
    - Retail & ecommerce
    - Media & entertainment
    - Others
  • 11.4 GOVERNMENT ORGANIZATIONS
    SIGNIFICANT FOCUS ON AUTOMATING ROUTINE TASKS AND EXTRACTING REAL-TIME ACTIONABLE INSIGHTS TO SUPPORT MARKET GROWTH
AI CHIP MARKET, BY REGION
174
  • 12.1 INTRODUCTION
  • 12.2 NORTH AMERICA
    MACROECONOMIC OUTLOOK FOR NORTH AMERICA
    US
    - Government-led initiatives to boost semiconductor manufacturing to drive market
    CANADA
    - Growing emphasis on commercializing AI to spur demand
    MEXICO
    - Increasing shift toward digital platforms and cloud-based solutions to accelerate demand
  • 12.3 EUROPE
    MACROECONOMIC OUTLOOK FOR EUROPE
    UK
    - Growing investments in data center infrastructure to boost demand
    GERMANY
    - Presence of robust industrial base to offer lucrative growth opportunities
    FRANCE
    - Increasing number of AI startups to accelerate demand
    ITALY
    - Rising adoption of digitalization in automotive and healthcare sectors to drive market
    SPAIN
    - Growing collaborations and partnerships among AI manufacturers to spur demand
    REST OF EUROPE
  • 12.4 ASIA PACIFIC
    MACROECONOMIC OUTLOOK FOR ASIA PACIFIC
    CHINA
    - Surge in research funding and implementation of supportive regulatory policy to augment market growth
    JAPAN
    - Rising adoption of AI chips to advance robotic systems to offer lucrative growth opportunities
    INDIA
    - Government-led initiatives to boost AI infrastructure to foster market growth
    SOUTH KOREA
    - Thriving semiconductor industry to drive market growth
    REST OF ASIA PACIFIC
  • 12.5 ROW
    MACROECONOMIC OUTLOOK FOR ROW
    MIDDLE EAST
    - Growing emphasis on digital transformation and technological innovation to drive market growth
    - GCC countries
    - Rest of Middle East
    AFRICA
    - Rising internet penetration and mobile subscriptions to offer lucrative growth opportunities
    SOUTH AMERICA
    - Growing need to store vast volumes of data to boost demand
COMPETITIVE LANDSCAPE
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
    STARS
    EMERGING LEADERS
    PERVASIVE PLAYERS
    PARTICIPANTS
    COMPANY FOOTPRINT: KEY PLAYERS, 2023
    - Company footprint
    - Compute footprint
    - Memory footprint
    - Network footprint
    - Technology footprint
    - Function footprint
    - End user footprint
    - Region footprint
  • 13.8 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2023
    PROGRESSIVE COMPANIES
    RESPONSIVE COMPANIES
    DYNAMIC COMPANIES
    STARTING BLOCKS
    COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2023
    - Detailed list of key startups/SMEs
    - Competitive benchmarking of key startups/SMEs
  • 13.9 COMPETITIVE SCENARIO
    PRODUCT LAUNCHES
    DEALS
COMPANY PROFILES
256
  • 14.1 KEY PLAYERS
    NVIDIA CORPORATION
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    ADVANCED MICRO DEVICES, INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    INTEL CORPORATION
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    SK HYNIX INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    SAMSUNG
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    - MnM view
    MICRON TECHNOLOGY, INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    APPLE INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    QUALCOMM TECHNOLOGIES, INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    HUAWEI TECHNOLOGIES CO., LTD.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    GOOGLE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    AMAZON WEB SERVICES, INC.
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    TESLA
    - Business overview
    - Products/Solutions/Services offered
    MICROSOFT
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    META
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    T-HEAD
    - Business overview
    - Products/Solutions/Services offered
    IMAGINATION TECHNOLOGIES
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    GRAPHCORE
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
    CEREBRAS
    - Business overview
    - Products/Solutions/Services offered
    - Recent developments
  • 14.2 OTHER PLAYERS
    MYTHIC
    KALRAY
    BLAIZE
    GROQ, INC.
    HAILO TECHNOLOGIES LTD
    GREENWAVES TECHNOLOGIES
    SIMA TECHNOLOGIES, INC.
    KNERON, INC.
    RAIN NEUROMORPHICS INC.
    TENSTORRENT
    SAMBANOVA SYSTEMS, INC.
    TAALAS
    SAPEON INC.
    REBELLIONS INC.
    RIVOS INC.
    SHANGHAI BIREN TECHNOLOGY CO., LTD.
APPENDIX
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
 
  • 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
 
  • 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

Methodology

The research process for this study involved the systematic gathering, recording, and analysis of data on customers and companies operating in the AI chip market. This process involved the extensive use of secondary sources, directories, and databases (Factiva and Oanda) to identify and collect valuable information for a comprehensive, technical, market-oriented, and commercial study of the AI chip market. In-depth interviews were conducted with primary respondents, including experts from core and related industries, as well as preferred manufacturers, to obtain and verify critical qualitative and quantitative information, and to assess growth prospects. Key players in the AI chip market were identified through secondary research, and their market rankings were determined through a combination of primary and secondary research. This research involved studying the annual reports of top players and conducting interviews with key industry experts, including CEOs, directors, and marketing executives.

Secondary Research

During the secondary research process, various sources were utilized to identify and collect information relevant to this study. These include annual reports, press releases, and investor presentations from companies, as well as white papers, technology journals, certified publications, articles by recognized authors, directories, and databases.

Secondary research was primarily used to gather key information about the industry's value chain, the total pool of market players, the classification of the market according to industry trends, and regional markets, as well as key developments from both market- and technology-oriented perspectives.

Primary Research

Primary research was also conducted to identify the segmentation types, key players, competitive landscape, and key market dynamics, including drivers, restraints, opportunities, challenges, and industry trends, as well as the key strategies adopted by players operating in the AI chip market. Extensive qualitative and quantitative analyses were performed on the complete market engineering process to list key information and insights throughout the report.

Extensive primary research has been conducted following the acquisition of knowledge about the AI chip market scenario through secondary research. Several primary interviews have been conducted with experts from both the demand side (end use and region) and the supply side (offering, technology, and function) across four major geographic regions: North America, Europe, Asia Pacific, and RoW. Approximately 80% and 20% of the primary interviews were conducted from the supply and demand sides, respectively. This primary data was collected through questionnaires, emails, and telephonic interviews.

Al Chip Market Size, and Share

Note: Other designations include technology heads, media analysts, sales managers, marketing managers, and product managers.

The three tiers of the companies are based on their total revenues as of 2024 ? Tier 1: >USD 1 billion, Tier 2: USD 500 million–1 billion, and Tier 3: USD 500 million.

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

Market Size Estimation

Throughout the comprehensive market engineering process, both top-down and bottom-up approaches were employed, along with several data triangulation methods, to estimate and validate the size of the AI chip market and its various dependent submarkets. Key players in the market were identified through secondary research, and their market share in the respective regions was determined through a combination of primary and secondary research. This entire research methodology involved studying the annual and financial reports of the top players, as well as conducting interviews with experts (including CEOs, VPs, directors, and marketing executives) to gather key insights (both quantitative and qualitative).

All percentage shares, splits, and breakdowns were determined using secondary sources and verified through primary sources. All the possible parameters that affect the markets covered in this research study were accounted for, viewed in detail, verified through primary research, and analyzed to obtain the final quantitative and qualitative data. This data was consolidated and supplemented with detailed inputs and analysis from MarketsandMarkets and presented in this report.

Bottom-Up Approach

  • Initially, the companies offering AI chips were identified. Their products were categorized based on compute, memory, network, technology, function, and end user.
  • After understanding the different types of AI chips offered by various manufacturers, the market was categorized into segments based on the data gathered through primary and secondary sources.
  • To derive the global AI chip market, global chip shipments of top players for AI servers considered in the report's scope were tracked.
  • A suitable penetration rate was assigned for compute, memory, and network offerings to derive the shipments of AI chips.
  • We derived the AI chip market based on different offerings using the average selling price (ASP) at which a particular company offers its devices. The ASP of each offering was identified based on secondary sources and validated through primary sources.
  • For the CAGR, a market trend analysis was conducted by examining the industry penetration rate, as well as the demand and supply of AI chips for various end users.
  • The AI chip market is also tracked through the data sanity method. The revenues of key providers were analyzed through annual reports and press releases and summed to derive the overall market.
  • For each company, a percentage is assigned to its overall revenue or, in a few cases, segmental revenue to derive its revenue for the AI chips. This percentage for each company is assigned based on its product portfolio and the range of AI chip offerings it provides.
  • The estimates at every level were verified and cross-checked through discussions with key opinion leaders, including CXOs, directors, and operations managers, and subsequently validated by domain experts at MarketsandMarkets.
  • Various paid and unpaid sources of information, such as annual reports, press releases, white papers, and databases, were studied.

Top-Down Approach

  • The global market size of AI chips was estimated based on data from major companies.
  • The growth of the AI chip market exhibited an upward trend during the studied period, as it is currently in the initial stage of the product cycle, with major players beginning to expand their business into various market application areas.
  • The types of AI chips, their features and properties, geographic presence, and key applications served by all players in the AI chip market were studied to estimate and determine the percentage split of the segments.
  • Different types of AI chip offerings, including compute, memory, and network, and their penetration among end users, were also studied.
  • Based on secondary research, the market was categorized by compute, memory, network, technology, function, and end user.
  • The demand generated by companies operating in different end-use application segments was analyzed.
  • Multiple discussions were conducted with key opinion leaders across major companies involved in developing AI chips and related components to validate the market split by compute, memory, network, technology, function, and end user.
  • The regional splits were estimated using secondary sources, based on factors such as the number of players in a specific country and region, as well as the adoption and use cases of each implementation type in relation to applications within the region.

Al Chip Market : Top-Down and Bottom-Up Approach

Al Chip Market Top Down and Bottom Up Approach

Data Triangulation

After determining the overall market size through the market size estimation process explained earlier, the total market was divided into several segments and subsegments. Data triangulation and market breakdown procedures were employed to complete the overall market engineering process and derive precise statistics for all segments and subsegments, as applicable. The data was triangulated by studying various factors and trends from both the demand and supply sides. Additionally, the AI chip market size was validated using both top-down and bottom-up approaches.

Market Definition

An AI chip is a type of specialized processor designed to efficiently perform artificial intelligence tasks, particularly in 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 execution of AI workloads compared to general-purpose processors.

Key Stakeholders

  • Government and financial institutions, and investment communities
  • Analysts and strategic business planners
  • Semiconductor product designers and fabricators
  • Application providers
  • AI solution providers
  • AI 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 AI chip market based on offering, 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 AI 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
  • To understand and analyze the impact of the 2025 US trump tariff on 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 5)

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