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市場調查報告書
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1776735

2032 年人工智慧晶片市場預測：按晶片類型、處理類型、功能、技術節點、記憶體類型、應用、最終用戶和地區進行全球分析

AI Chips Market Forecasts to 2032 - Global Analysis by Chip Type (Central Processing Unit, Graphics Processing Unit and Other Chip Types), Processing Type, Functionality, Technology Node, Memory Type, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 200+ Pages | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的數據，全球 AI 晶片市場規模預計在 2025 年達到 1,703 億美元，到 2032 年將達到 7,215 億美元，預測期內的複合年成長率為 22.9%。

AI晶片是專門設計用於處理機器學習和深度學習等人工智慧任務的處理器。這些晶片透過並行處理大量資料來加速複雜的運算。隨著對更快、更有效率的AI模型的需求不斷成長，這些晶片正成為醫療保健、金融、機器人和智慧型裝置等各行各業的必需品。

用於支援 AI 工作負載的 GPU 運算需求正在激增，據 Nvidia 稱，2024 會計年度第二季資料中心營收達到 226 億美元，年增 171%。

各行各業人工智慧應用爆炸性成長

人工智慧在醫療保健、汽車、金融和製造等領域的快速整合是推動人工智慧晶片市場的主要動力。隨著越來越多的企業利用人工智慧實現自動化、分析和決策，對能夠處理複雜運算的專用晶片的需求激增。這種廣泛的應用並不限於大型企業，中小企業也積極擁抱人工智慧主導的解決方案。此外，資料中心和雲端基礎服務的興起也推動了對高效能人工智慧晶片的需求，進一步推動了市場擴張。

研發和製造成本高

開發和製造先進的人工智慧晶片是一個昂貴而複雜的過程，需要在研發、專業人才和先進的製造設施方面投入大量資金。晶片設計的複雜性，加上需要不斷創新才能跟上不斷發展的人工智慧演算法，造成了較高的進入門檻。此外，供應鏈中斷和關鍵原料的短缺可能會進一步推高成本。總而言之，這些因素可能會抑制市場成長，並減緩產業技術進步的步伐，尤其對於新參與企業和規模較小的公司而言。

人工智慧演算法和模型的進步

人工智慧演算法和模型的持續突破帶來了巨大的機會。隨著模型變得越來越複雜且資源密集，對能夠高效處理這些工作負載的硬體的需求也日益成長。此外，邊緣運算的進步以及機器人、物聯網和自主系統中新型人工智慧應用的湧現，正在推動創新晶片結構的需求。隨著行業尋求兼顧性能和能源效率的硬體，能夠充分利用這些進步的公司將受益於硬體的普及。

道德問題和監管監督

由於倫理考量和法律規範，人工智慧晶片面臨許多挑戰。資料隱私、演算法偏差以及人工智慧技術濫用的可能性等問題，正促使政府和監管機構推出更嚴格的準則。這些監管措施可能會增加合規成本，並延遲產品發布。此外，加強公眾監督可能會影響消費者信任，並減緩人工智慧解決方案的採用。

COVID-19的影響：

新冠疫情最初擾亂了全球供應鏈和製造業務，導致人工智慧晶片的生產和部署延遲。然而，隨著企業轉向遠距辦公並增加對人工智慧驅動技術的依賴，這場危機也加速了數位轉型。這導致醫療保健、物流和電子商務等行業對人工智慧晶片的需求激增。儘管初期遭遇挫折，但市場迅速適應，增加了對人工智慧基礎設施的投資，並為疫情後產業的強勁成長奠定了基礎。

圖形處理單元 (GPU) 部分預計將成為預測期內最大的部分

預計圖形處理器 (GPU) 領域將在預測期內佔據最大的市場佔有率。 GPU 憑藉其平行處理能力，被視為處理資料中心、雲端環境和高效能運算應用中複雜 AI 工作負載的理想選擇。由於持續的技術創新以及深度學習、自然語言處理和電腦視覺等 AI 應用行業的強勁需求，NVIDIA、AMD 和英特爾等領導者已在該領域確立了強勢地位。隨著生成式 AI 和大型語言模型的普及，預計這種主導地位將持續下去。

預計邊緣運算領域在預測期內的複合年成長率最高

預計邊緣運算領域將在預測期內實現最高成長率。自動駕駛汽車、智慧型設備和工業自動化領域對即時數據處理和低延遲人工智慧應用的需求日益成長，這推動了邊緣人工智慧晶片的需求。這些晶片支援本地處理，減少對雲端基礎設施的依賴，並提高速度、隱私和能源效率。隨著物聯網的普及以及更多設備對設備端智慧的需求，邊緣運算領域可能會大幅加速發展。

比最大的地區

預計北美將在預測期內佔據最大的市場佔有率。這種優勢得益於領先的科技公司、強大的創新生態系統以及對人工智慧研發的大量投資。該地區正見證著人工智慧技術在醫療保健、汽車等多個領域的早期應用，這進一步推動了需求。此外，政府的支持措施和創業投資資金籌措為人工智慧晶片的創新和商業化創造了良好的環境，從而鞏固了北美的領先地位。

複合年成長率最高的地區：

預計亞太地區在預測期內的複合年成長率最高。快速數位化、工業自動化的擴張以及人工智慧基礎設施投資的不斷增加是該地區發展的關鍵驅動力。在強力的政府政策和日益壯大的科技新興企業生態系統的支持下，中國、日本和韓國等國家在人工智慧晶片的製造和部署方面處於領先地位。智慧型設備和物聯網應用的激增，加上對經濟實惠的人工智慧解決方案日益成長的需求，使亞太地區成為成長最快的地區。

提供免費客製化：

此報告的訂閱者將獲得以下免費自訂選項之一：

  • 公司簡介
    • 對最多三家其他市場公司進行全面分析
    • 主要企業的SWOT分析（最多3家公司）
  • 地理細分
    • 根據客戶興趣對主要國家進行的市場估計、預測和複合年成長率（註：基於可行性檢查）
  • 競爭基準化分析
    • 根據產品系列、地理分佈和策略聯盟對主要企業基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 研究範圍
  • 調查方法
    • 資料探勘
    • 數據分析
    • 數據檢驗
    • 研究途徑
  • 研究材料
    • 主要研究資料
    • 次級研究資訊來源
    • 先決條件

第3章市場走勢分析

  • 驅動程式
  • 抑制因素
  • 機會
  • 威脅
  • 技術分析
  • 應用分析
  • 最終用戶分析
  • 新興市場
  • COVID-19的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買家的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章 全球AI晶片市場（依晶片類型）

  • 中央處理器（CPU）
  • 圖形處理單元 (GPU)
  • 現場可程式閘陣列（FPGA）
  • 專用積體電路（ASIC）
    • 神經處理單元（NPU）
    • 張量處理單元 (TPU)
    • 其他客製化AI加速器
  • 其他晶片類型

6. 全球AI晶片市場（依處理類型）

  • 邊緣
  • 雲
  • 本地

第7章 全球AI晶片市場（按功能）

  • 訓練
  • 推理

第8章 全球AI晶片市場（依技術節點）

  • 10奈米或更小
  • 10nm～20nm
  • 20奈米或以上

第9章全球AI晶片市場（按記憶體類型）

  • DDR（DRAM）
  • HBM（高頻寬記憶體）
  • 其他記憶體類型

第10章 全球人工智慧晶片市場（按應用）

  • 自然語言處理（NLP）
  • 電腦視覺
  • 人工智慧世代
  • 網路安全
  • 機器人技術
  • 預測分析
  • 其他應用

第 11 章全球 AI 晶片市場（按最終用戶）

  • 家電
  • 資料中心
  • 車
  • 衛生保健
  • BFSI
  • 資訊科技/通訊
  • 產業
  • 航太/國防
  • 零售
  • 農業
  • 其他最終用戶

第12章 全球人工智慧晶片市場（按地區）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲國家
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 其他亞太地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 南美洲其他地區
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第13章 重大進展

  • 協議、夥伴關係、合作和合資企業
  • 收購與合併
  • 新產品發布
  • 業務擴展
  • 其他關鍵策略

第14章 公司概況

  • NVIDIA Corporation
  • Intel Corporation
  • Advanced Micro Devices, Inc.（AMD）
  • Qualcomm Technologies, Inc.
  • Alphabet Inc.（Google LLC）
  • IBM Corporation
  • Samsung Electronics Co., Ltd.
  • Huawei Technologies Co., Ltd.
  • Baidu, Inc.
  • Apple Inc.
  • Microsoft Corporation
  • Amazon Web Services, Inc.
  • Broadcom Inc.
  • MediaTek Inc.
  • Graphcore Limited
  • Rebellions Inc.
  • SK Hynix Inc.
  • Sapeon Inc.
Product Code: SMRC30066

According to Stratistics MRC, the Global AI Chips Market is accounted for $170.3 billion in 2025 and is expected to reach $721.5 billion by 2032 growing at a CAGR of 22.9% during the forecast period. AI chips are specialized processors designed to handle artificial intelligence tasks like machine learning and deep learning. These chips accelerate complex computations by processing large volumes of data in parallel. With growing demand for faster, more efficient AI models, these chips are becoming essential across industries, from healthcare and finance to robotics and smart devices.

According to NVIDIA, the demand for GPU computing to support AI workloads has surged, with data center revenue reaching $22.6 billion in Q2 FY2024, a 171% increase year-over-year.

Market Dynamics:

Driver:

Explosive growth of Ai adoption across industries

The rapid integration of artificial intelligence across sectors such as healthcare, automotive, finance, and manufacturing is a primary driver for the AI chips market. As organizations increasingly leverage AI for automation, analytics, and decision-making, the demand for specialized chips capable of handling complex computations has surged. This widespread adoption is not limited to large enterprises; small and medium-sized businesses are also embracing AI-driven solutions. Furthermore, the proliferation of data centers and cloud-based services has intensified the need for high-performance AI chips, fueling market expansion.

Restraint:

High research & development and manufacturing costs

Developing and manufacturing advanced AI chips is an expensive and intricate process, requiring significant investments in R&D, specialized talent, and state-of-the-art fabrication facilities. The complexity of chip design, coupled with the need for constant innovation to keep pace with evolving AI algorithms, creates high entry barriers. Additionally, supply chain disruptions and the scarcity of critical raw materials can further escalate costs. These factors collectively constrain market growth, particularly for new entrants and smaller firms, and may slow the pace of technological advancement in the industry.

Opportunity:

Advancements in Ai algorithms and models

Ongoing breakthroughs in AI algorithms and models present substantial opportunities. As models become more sophisticated and resource-intensive, there is a growing need for hardware that can efficiently process these workloads. Moreover, the evolution of edge computing and the emergence of new AI applications in robotics, IoT, and autonomous systems are driving demand for innovative chip architectures. Companies that successfully harness these advancements stand to benefit from increased adoption, as industries seek hardware optimized for both performance and energy efficiency.

Threat:

Ethical concerns and regulatory scrutiny

AI chips face mounting challenges from ethical considerations and regulatory oversight. Issues such as data privacy, algorithmic bias, and the potential misuse of AI technologies have prompted governments and regulatory bodies to introduce stricter guidelines. These evolving regulations can increase compliance costs and delay product launches. Additionally, heightened public scrutiny may impact consumer trust and slow the adoption of AI-powered solutions.

Covid-19 Impact:

The Covid-19 pandemic initially disrupted global supply chains and manufacturing operations, causing delays in AI chip production and deployment. However, the crisis also accelerated digital transformation as organizations shifted to remote work and increased reliance on AI-driven technologies. This led to a surge in demand for AI chips in sectors such as healthcare, logistics, and e-commerce. Despite early setbacks, the market quickly adapted, and investments in AI infrastructure rose, positioning the industry for robust post-pandemic growth.

The graphics processing unit (GPU) segment is expected to be the largest during the forecast period

The graphics processing unit (GPU) segment is expected to account for the largest market share during the forecast period. GPUs are favored for their parallel processing capabilities, making them ideal for handling complex AI workloads in data centers, cloud environments, and high-performance computing applications. Major players such as NVIDIA, AMD, and Intel have established strong positions in this segment, driven by continuous innovation and robust demand from industries leveraging AI for deep learning, natural language processing, and computer vision. This dominance is set to persist as generative AI and large language models become more prevalent.

The edge segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the edge segment is predicted to witness the highest growth rate. The increasing need for real-time data processing and low-latency AI applications in autonomous vehicles, smart devices, and industrial automation is propelling demand for edge AI chips. These chips enable local processing, reducing reliance on cloud infrastructure and improving speed, privacy, and energy efficiency. As IoT adoption expands and more devices require on-device intelligence, the edge segment will experience significant acceleration.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. This dominance is attributed to the presence of leading technology companies, robust innovation ecosystems, and substantial investments in AI research and development. The region's early adoption of AI technologies across diverse sectors ranging from healthcare to automotive further bolsters demand. Additionally, supportive government initiatives and venture capital funding have fostered a favorable environment for AI chip innovation and commercialization, solidifying North America's leadership.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. Rapid digitalization, expanding industrial automation, and increasing investments in AI infrastructure are key drivers in this region. Countries like China, Japan, and South Korea are at the forefront of AI chip manufacturing and deployment, supported by strong government policies and a growing ecosystem of tech startups. The proliferation of smart devices and IoT applications, coupled with rising demand for affordable AI solutions, positions Asia Pacific as the fastest-growing region.

Key players in the market

Some of the key players in AI Chips Market include NVIDIA Corporation, Intel Corporation, Advanced Micro Devices, Inc. (AMD), Qualcomm Technologies, Inc., Alphabet Inc. (Google LLC), IBM Corporation, Samsung Electronics Co., Ltd., Huawei Technologies Co., Ltd., Baidu, Inc., Apple Inc., Microsoft Corporation, Amazon Web Services, Inc., Broadcom Inc., MediaTek Inc., Graphcore Limited, Rebellions Inc., SK Hynix Inc. and Sapeon Inc.

Key Developments:

In June 2025, AMD launched the AMD Instinct(TM) MI350 Series, delivering up to 4 x generation-on-generations AI compute improvement and up to 35x leap in inferencing performance. AMD also showcased its new developer cloud to empowering AI developers with seamless access to AMD Instinct GPUs and ROCm for their AI innovation. The company also previewed its next-gen "Helios" AI rack infrastructure, integrating MI400 GPUs, EPYC "Venice" CPUs, and Pensando "Vulcano" NICs for unprecedented AI compute density and scalability

In May 2025, NVIDIA announced that Taiwan's leading system manufacturers are set to build NVIDIA DGX Spark and DGX Station(TM) systems. Growing partnerships with Acer, GIGABYTE and MSI will extend the availability of DGX Spark and DGX Station personal AI supercomputers - empowering a global ecosystem of developers, data scientists and researchers with unprecedented performance and efficiency. Enterprises, software providers, government agencies, startups and research institutions need robust systems that can deliver the performance and capabilities of an AI server in a desktop form factor without compromising data size, proprietary model privacy or the speed of scalability.

In May 2025, At Embedded World Germany, Qualcomm Technologies, Inc. announced the entry into an agreement to acquire EdgeImpulse Inc., which will enhance its offering for developers and expand its leadership in AI capabilities to power AI-enabled products and services across IoT. The closing of this deal is subject to customary closing conditions. This acquisition is anticipated to complement Qualcomm Technologies' strategic approach to IoT transformation, which includes a comprehensive chipset roadmap, unified software architecture, a suite of services, developer resources, ecosystem partners, comprehensive solutions, and IoT blueprints to address diverse industry needs and challenges.

Chip Types Covered:

  • Central Processing Unit (CPU)
  • Graphics Processing Unit (GPU)
  • Field Programmable Gate Array (FPGA)
  • Application-Specific Integrated Circuit (ASIC)
  • Other Chip Types

Processing Types:

  • Edge
  • Cloud
  • On-premise

Functionalities Covered:

  • Training
  • Inference

Technology Nodes Covered:

  • 10nm and Below
  • 10nm to 20nm
  • 20nm and Above

Memory Types Covered:

  • DDR (DRAM)
  • HBM (High-Bandwidth Memory)
  • Other Memory Types

Applications Covered:

  • Natural Language Processing (NLP)
  • Computer Vision
  • Generative AI
  • Network Security
  • Robotics
  • Predictive Analysis
  • Other Applications

End Users Covered:

  • Consumer Electronics
  • Data Centers
  • Automotive
  • Healthcare
  • BFSI
  • IT & Telecom
  • Industrial
  • Aerospace & Defense
  • Retail
  • Agriculture
  • Other End Users

Regions Covered:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • UK
    • Italy
    • France
    • Spain
    • Rest of Europe
  • Asia Pacific
    • Japan
    • China
    • India
    • Australia
    • New Zealand
    • South Korea
    • Rest of Asia Pacific
  • South America
    • Argentina
    • Brazil
    • Chile
    • Rest of South America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • Qatar
    • South Africa
    • Rest of Middle East & Africa

What our report offers:

  • Market share assessments for the regional and country-level segments
  • Strategic recommendations for the new entrants
  • Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
  • Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
  • Strategic recommendations in key business segments based on the market estimations
  • Competitive landscaping mapping the key common trends
  • Company profiling with detailed strategies, financials, and recent developments
  • Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

  • Company Profiling
    • Comprehensive profiling of additional market players (up to 3)
    • SWOT Analysis of key players (up to 3)
  • Regional Segmentation
    • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
  • Competitive Benchmarking
    • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

  • 2.1 Abstract
  • 2.2 Stake Holders
  • 2.3 Research Scope
  • 2.4 Research Methodology
    • 2.4.1 Data Mining
    • 2.4.2 Data Analysis
    • 2.4.3 Data Validation
    • 2.4.4 Research Approach
  • 2.5 Research Sources
    • 2.5.1 Primary Research Sources
    • 2.5.2 Secondary Research Sources
    • 2.5.3 Assumptions

3 Market Trend Analysis

  • 3.1 Introduction
  • 3.2 Drivers
  • 3.3 Restraints
  • 3.4 Opportunities
  • 3.5 Threats
  • 3.6 Technology Analysis
  • 3.7 Application Analysis
  • 3.8 End User Analysis
  • 3.9 Emerging Markets
  • 3.10 Impact of Covid-19

4 Porters Five Force Analysis

  • 4.1 Bargaining power of suppliers
  • 4.2 Bargaining power of buyers
  • 4.3 Threat of substitutes
  • 4.4 Threat of new entrants
  • 4.5 Competitive rivalry

5 Global AI Chips Market, By Chip Type

  • 5.1 Introduction
  • 5.2 Central Processing Unit (CPU)
  • 5.3 Graphics Processing Unit (GPU)
  • 5.4 Field Programmable Gate Array (FPGA)
  • 5.5 Application-Specific Integrated Circuit (ASIC)
    • 5.5.1 Neural Processing Units (NPUs)
    • 5.5.2 Tensor Processing Units (TPUs)
    • 5.5.3 Other Custom AI Accelerators
  • 5.6 Other Chip Types

6 Global AI Chips Market, By Processing Type

  • 6.1 Introduction
  • 6.2 Edge
  • 6.3 Cloud
  • 6.4 On-premise

7 Global AI Chips Market, By Functionality

  • 7.1 Introduction
  • 7.2 Training
  • 7.3 Inference

8 Global AI Chips Market, By Technology Node

  • 8.1 Introduction
  • 8.2 10nm and Below
  • 8.3 10nm to 20nm
  • 8.4 20nm and Above

9 Global AI Chips Market, By Memory Type

  • 9.1 Introduction
  • 9.2 DDR (DRAM)
  • 9.3 HBM (High-Bandwidth Memory)
  • 9.4 Other Memory Types

10 Global AI Chips Market, By Application

  • 10.1 Introduction
  • 10.2 Natural Language Processing (NLP)
  • 10.3 Computer Vision
  • 10.4 Generative AI
  • 10.5 Network Security
  • 10.6 Robotics
  • 10.7 Predictive Analysis
  • 10.8 Other Applications

11 Global AI Chips Market, By End User

  • 11.1 Introduction
  • 11.2 Consumer Electronics
  • 11.3 Data Centers
  • 11.4 Automotive
  • 11.5 Healthcare
  • 11.6 BFSI
  • 11.7 IT & Telecom
  • 11.8 Industrial
  • 11.9 Aerospace & Defense
  • 11.10 Retail
  • 11.11 Agriculture
  • 11.12 Other End Users

12 Global AI Chips Market, By Geography

  • 12.1 Introduction
  • 12.2 North America
    • 12.2.1 US
    • 12.2.2 Canada
    • 12.2.3 Mexico
  • 12.3 Europe
    • 12.3.1 Germany
    • 12.3.2 UK
    • 12.3.3 Italy
    • 12.3.4 France
    • 12.3.5 Spain
    • 12.3.6 Rest of Europe
  • 12.4 Asia Pacific
    • 12.4.1 Japan
    • 12.4.2 China
    • 12.4.3 India
    • 12.4.4 Australia
    • 12.4.5 New Zealand
    • 12.4.6 South Korea
    • 12.4.7 Rest of Asia Pacific
  • 12.5 South America
    • 12.5.1 Argentina
    • 12.5.2 Brazil
    • 12.5.3 Chile
    • 12.5.4 Rest of South America
  • 12.6 Middle East & Africa
    • 12.6.1 Saudi Arabia
    • 12.6.2 UAE
    • 12.6.3 Qatar
    • 12.6.4 South Africa
    • 12.6.5 Rest of Middle East & Africa

13 Key Developments

  • 13.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 13.2 Acquisitions & Mergers
  • 13.3 New Product Launch
  • 13.4 Expansions
  • 13.5 Other Key Strategies

14 Company Profiling

  • 14.1 NVIDIA Corporation
  • 14.2 Intel Corporation
  • 14.3 Advanced Micro Devices, Inc. (AMD)
  • 14.4 Qualcomm Technologies, Inc.
  • 14.5 Alphabet Inc. (Google LLC)
  • 14.6 IBM Corporation
  • 14.7 Samsung Electronics Co., Ltd.
  • 14.8 Huawei Technologies Co., Ltd.
  • 14.9 Baidu, Inc.
  • 14.10 Apple Inc.
  • 14.11 Microsoft Corporation
  • 14.12 Amazon Web Services, Inc.
  • 14.13 Broadcom Inc.
  • 14.14 MediaTek Inc.
  • 14.15 Graphcore Limited
  • 14.16 Rebellions Inc.
  • 14.17 SK Hynix Inc.
  • 14.18 Sapeon Inc.

List of Tables

  • Table 1 Global AI Chips Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI Chips Market Outlook, By Chip Type (2024-2032) ($MN)
  • Table 3 Global AI Chips Market Outlook, By Central Processing Unit (CPU) (2024-2032) ($MN)
  • Table 4 Global AI Chips Market Outlook, By Graphics Processing Unit (GPU) (2024-2032) ($MN)
  • Table 5 Global AI Chips Market Outlook, By Field Programmable Gate Array (FPGA) (2024-2032) ($MN)
  • Table 6 Global AI Chips Market Outlook, By Application-Specific Integrated Circuit (ASIC) (2024-2032) ($MN)
  • Table 7 Global AI Chips Market Outlook, By Neural Processing Units (NPUs) (2024-2032) ($MN)
  • Table 8 Global AI Chips Market Outlook, By Tensor Processing Units (TPUs) (2024-2032) ($MN)
  • Table 9 Global AI Chips Market Outlook, By Other Custom AI Accelerators (2024-2032) ($MN)
  • Table 10 Global AI Chips Market Outlook, By Other Chip Types (2024-2032) ($MN)
  • Table 11 Global AI Chips Market Outlook, By Processing Type (2024-2032) ($MN)
  • Table 12 Global AI Chips Market Outlook, By Edge (2024-2032) ($MN)
  • Table 13 Global AI Chips Market Outlook, By Cloud (2024-2032) ($MN)
  • Table 14 Global AI Chips Market Outlook, By On-premise (2024-2032) ($MN)
  • Table 15 Global AI Chips Market Outlook, By Functionality (2024-2032) ($MN)
  • Table 16 Global AI Chips Market Outlook, By Training (2024-2032) ($MN)
  • Table 17 Global AI Chips Market Outlook, By Inference (2024-2032) ($MN)
  • Table 18 Global AI Chips Market Outlook, By Technology Node (2024-2032) ($MN)
  • Table 19 Global AI Chips Market Outlook, By 10nm and Below (2024-2032) ($MN)
  • Table 20 Global AI Chips Market Outlook, By 10nm to 20nm (2024-2032) ($MN)
  • Table 21 Global AI Chips Market Outlook, By 20nm and Above (2024-2032) ($MN)
  • Table 22 Global AI Chips Market Outlook, By Memory Type (2024-2032) ($MN)
  • Table 23 Global AI Chips Market Outlook, By DDR (DRAM) (2024-2032) ($MN)
  • Table 24 Global AI Chips Market Outlook, By HBM (High-Bandwidth Memory) (2024-2032) ($MN)
  • Table 25 Global AI Chips Market Outlook, By Other Memory Types (2024-2032) ($MN)
  • Table 26 Global AI Chips Market Outlook, By Application (2024-2032) ($MN)
  • Table 27 Global AI Chips Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 28 Global AI Chips Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 29 Global AI Chips Market Outlook, By Generative AI (2024-2032) ($MN)
  • Table 30 Global AI Chips Market Outlook, By Network Security (2024-2032) ($MN)
  • Table 31 Global AI Chips Market Outlook, By Robotics (2024-2032) ($MN)
  • Table 32 Global AI Chips Market Outlook, By Predictive Analysis (2024-2032) ($MN)
  • Table 33 Global AI Chips Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 34 Global AI Chips Market Outlook, By End User (2024-2032) ($MN)
  • Table 35 Global AI Chips Market Outlook, By Consumer Electronics (2024-2032) ($MN)
  • Table 36 Global AI Chips Market Outlook, By Data Centers (2024-2032) ($MN)
  • Table 37 Global AI Chips Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 38 Global AI Chips Market Outlook, By Healthcare (2024-2032) ($MN)
  • Table 39 Global AI Chips Market Outlook, By BFSI (2024-2032) ($MN)
  • Table 40 Global AI Chips Market Outlook, By IT & Telecom (2024-2032) ($MN)
  • Table 41 Global AI Chips Market Outlook, By Industrial (2024-2032) ($MN)
  • Table 42 Global AI Chips Market Outlook, By Aerospace & Defense (2024-2032) ($MN)
  • Table 43 Global AI Chips Market Outlook, By Retail (2024-2032) ($MN)
  • Table 44 Global AI Chips Market Outlook, By Agriculture (2024-2032) ($MN)
  • Table 45 Global AI Chips Market Outlook, By Other End Users (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.