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封面
市场调查报告书
商品编码
1947502

人工智慧晶片市场：依晶片类型、功能、处理类型、应用和最终用途划分－全球预测至2036年

AI Chip Market by Chip Type, Function, Processing Type, Application, and End-use -- Global Forecast to 2036
出版日期: | 出版商: Meticulous Research | 英文 298 Pages | 商品交期: 5-7个工作天内

价格
简介目录

全球人工智慧晶片市场预计将以22.6%的复合年增长率成长，从2026年的876亿美元成长到2036年的约6702亿美元。

本报告对全球五大主要区域的人工智慧晶片市场进行了详细分析，重点关注当前市场趋势、市场规模、近期发展以及至2036年的预测。透过广泛的二级和一级研究以及对市场情景的深入分析，我们对关键产业驱动因素、限制因素、机会和挑战进行了影响分析。

推动人工智慧晶片市场成长的关键因素包括生成式人工智慧应用的爆炸性成长、跨行业智慧系统的快速普及以及对专用运算硬体需求的不断增长。 此外，边缘运算计画的快速扩张、对自动驾驶汽车日益增长的需求、资料中心基础设施的扩展以及数位转型计画预计将为人工智慧晶片市场的企业创造巨大的成长机会。

市场区隔

目录

第一章：引言

第二章：摘要整理

第三章：市场概览

  • 市场动态
    • 驱动因素
    • 限制因素
    • 机遇
    • 挑战
  • 生成式人工智慧和边缘运算对人工智慧晶片的影响
  • 监管环境与半导体贸易政策
  • 波特五力分析

第四章 全球人工智慧晶片市场（依晶片类型划分）

  • 图形处理器 (GPU)
  • 中央处理器 (CPU)
  • 专用积体电路 (ASIC)
  • 张量处理器 (TPU)
  • 现场可程式闸阵列 (FPGA)
  • 神经处理器 (NPU)
  • 其他（神经形态晶片、光子处理器）

第五章：全球人工智慧晶片市场（依功能划分）

  • 训练
  • 推理

第六章：全球人工智慧晶片市场（依处理类型划分）

  • 云端/资料中心
  • 边缘运算

第七章：全球人工智慧晶片市场（依最终用途划分）

  • 资料中心与云端运算
  • 自动驾驶汽车和ADAS
  • 消费性电子产品（智慧型手机、个人电脑、穿戴式装置）
  • 工业物联网与机器人
  • 医疗保健和医学影像
  • 自然语言处理与生成式人工智慧
  • 其他（智慧城市、监控与游戏）

第八章 全球人工智慧晶片市场（依最终用途划分）

  • 资料中心与云端运算
  • 汽车
  • 消费性电子产品
  • 工业
  • 医疗保健
  • 电信
  • 其他（航空航太与国防、金融服务）

第九章 全球人工智慧晶片市场（依地区划分）

  • 北美
    • 美国美国
    • 加拿大
  • 欧洲
    • 德国
    • 法国
    • 英国
    • 义大利
    • 西班牙
    • 荷兰
    • 欧洲其他国家
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 韩国
    • 台湾
    • 东南亚
    • 澳大利亚
    • 亚太其他国家
  • 拉丁美洲
    • 巴西
    • 墨西哥 拉丁美洲其他国家
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯联合大公国
    • 南非
    • 中东和非洲其他国家

第十章 竞争概论

  • 关键成长策略
  • 竞争基准分析
  • 竞争概览
    • 行业领导者
    • 市场差异化因素
    • 先锋企业
    • 新兴企业
  • 主要企业市场排名/定位分析（2025 年）

第11章 企业简介(製造商及提供业者)

  • NVIDIA Corporation
  • Intel Corporation
  • Advanced Micro Devices Inc.(AMD)
  • Qualcomm Technologies Inc.
  • Google LLC(Alphabet Inc.)
  • Apple Inc.
  • Microsoft Corporation
  • Amazon Web Services Inc.
  • Broadcom Inc.
  • Samsung Electronics Co., Ltd.
  • Taiwan Semiconductor Manufacturing Company(TSMC)
  • Cerebras Systems
  • Groq Inc.
  • Tenstorrent
  • SambaNova Systems
  • Graphcore
  • Hailo
  • Habana Labs(Intel)
  • Biren Technology
  • Cambricon Technologies

第12章 附录

简介目录
Product Code: MRSE - 1041761

AI Chip Market by Chip Type (GPU, CPU, ASIC, TPU, FPGA, NPU), Function (Training, Inference), Processing Type (Cloud/Data Center, Edge), Application (Data Centers, Autonomous Vehicles, Consumer Electronics, Industrial IoT, Healthcare), and End-use (Data Centers & Cloud, Automotive, Consumer Electronics, Industrial, Healthcare, Telecommunications) - Global Forecast to 2036

According to the research report titled, 'AI Chip Market by Chip Type (GPU, CPU, ASIC, TPU, FPGA, NPU), Function (Training, Inference), Processing Type (Cloud/Data Center, Edge), Application (Data Centers, Autonomous Vehicles, Consumer Electronics, Industrial IoT, Healthcare), and End-use (Data Centers & Cloud, Automotive, Consumer Electronics, Industrial, Healthcare, Telecommunications) - Global Forecast to 2036,' the global AI chip market is expected to reach approximately USD 670.2 billion by 2036 from USD 87.6 billion in 2026, at a CAGR of 22.6% during the forecast period (2026-2036).

The report provides an in-depth analysis of the global AI chip market across five major regions, emphasizing the current market trends, market sizes, recent developments, and forecasts till 2036. Following extensive secondary and primary research and an in-depth analysis of the market scenario, the report conducts the impact analysis of the key industry drivers, restraints, opportunities, and challenges.

The major factors driving the growth of the AI chip market include the explosive expansion of generative AI applications, rapid deployment of intelligent systems across industries, and increasing need for specialized computational hardware. Additionally, the rapid expansion of edge computing initiatives, growing demand for autonomous vehicles, expansion of data center infrastructure, and digital transformation initiatives are expected to create significant growth opportunities for players operating in the AI chip market.

Market Segmentation

The AI chip market is segmented by chip type (GPU, CPU, ASIC, TPU, FPGA, NPU), function (training, inference), processing type (cloud/data center, edge), application (data centers, autonomous vehicles, consumer electronics, industrial IoT, healthcare), end-use (data centers & cloud, automotive, consumer electronics, industrial, healthcare, telecommunications), and geography. The study also evaluates industry competitors and analyzes the market at the country level.

Based on Chip Type

By chip type, the GPU segment holds the largest market share in 2026, primarily attributed to their versatile use in supporting large-scale training workloads, inference operations, and deep learning applications with modern data center environments. These processors offer the most comprehensive way to ensure high-performance AI processing across diverse applications. However, the ASIC and TPU segments are expected to grow at a rapid CAGR during the forecast period, driven by the growing need for specialized hardware optimization, reduced power consumption, and enhanced performance efficiency. The ability to provide application-specific acceleration makes these chips highly attractive for modern AI infrastructure. CPU, FPGA, and NPU represent significant segments for specialized applications.

Based on Function

By function, the inference segment holds the largest share of the overall market in 2026, primarily due to the widespread deployment of pre-trained models in production environments and the rigorous performance requirements for real-time decision-making. The training segment is expected to witness the fastest growth during the forecast period, driven by the shift toward large language models and the complexity of advanced AI algorithms. Both segments represent distinct requirements for computational architecture and power efficiency.

Based on Processing Type

By processing type, the cloud/data center segment holds the largest share of the overall market in 2026, driven by the need for centralized high-performance computing infrastructure and large-scale model training. Edge processing represents a growing segment as organizations increasingly implement distributed AI solutions to reduce latency and improve real-time responsiveness. Both segments require specialized chip architectures optimized for their respective deployment environments.

Geographic Analysis

An in-depth geographic analysis of the industry provides detailed qualitative and quantitative insights into the five major regions (North America, Europe, Asia-Pacific, Latin America, and the Middle East & Africa) and the coverage of major countries in each region. In 2026, North America dominates the global AI chip market with the largest market share, primarily attributed to massive investments in data center infrastructure and the presence of leading technology companies in the United States and Canada. Asia-Pacific is expected to witness the fastest growth during the forecast period, supported by advanced semiconductor manufacturing capabilities and rapid adoption of AI technologies in China, South Korea, and Taiwan. Europe, Latin America, and the Middle East & Africa represent emerging markets with growing AI infrastructure investments and increasing demand for specialized computing hardware.

Key Players

The key players operating in the global AI chip market are NVIDIA Corporation (U.S.), Intel Corporation (U.S.), Advanced Micro Devices Inc. (U.S.), Broadcom Inc. (U.S.), Qualcomm Incorporated (U.S.), Apple Inc. (U.S.), Google LLC (U.S.), Amazon.com Inc. (U.S.), Meta Platforms Inc. (U.S.), and various other regional and emerging manufacturers, among others.

Key Questions Answered in the Report-

  • What is the current revenue generated by the AI chip market globally?
  • At what rate is the global AI chip market demand projected to grow for the next 7-10 years?
  • What are the historical market sizes and growth rates of the global AI chip market?
  • What are the major factors impacting the growth of this market at the regional and country levels? What are the major opportunities for existing players and new entrants in the market?
  • Which segments in terms of chip type, function, and processing type are expected to create major traction for the service providers in this market?
  • What are the key geographical trends in this market? Which regions/countries are expected to offer significant growth opportunities for the companies operating in the global AI chip market?
  • Who are the major players in the global AI chip market? What are their specific service offerings in this market?
  • What are the recent strategic developments in the global AI chip market? What are the impacts of these strategic developments on the market?

Scope of the Report:

AI Chip Market Assessment -- by Chip Type

  • Graphics Processing Units (GPUs)
  • Central Processing Units (CPUs)
  • Application-Specific Integrated Circuits (ASICs)
  • Tensor Processing Units (TPUs)
  • Field-Programmable Gate Arrays (FPGAs)
  • Neural Processing Units (NPUs)

AI Chip Market Assessment -- by Function

  • Training
  • Inference

AI Chip Market Assessment -- by Processing Type

  • Cloud/Data Center
  • Edge

AI Chip Market Assessment -- by Application

  • Data Centers
  • Autonomous Vehicles
  • Consumer Electronics
  • Industrial IoT
  • Healthcare
  • Other Applications

AI Chip Market Assessment -- by End-use

  • Data Centers & Cloud
  • Automotive
  • Consumer Electronics
  • Industrial
  • Healthcare
  • Telecommunications
  • Other End-uses

AI Chip Market Assessment -- by Geography

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Spain
    • Rest of Europe
  • Asia-Pacific
    • China
    • India
    • Japan
    • South Korea
    • Taiwan
    • Rest of Asia-Pacific
  • Latin America
    • Brazil
    • Mexico
    • Argentina
    • Rest of Latin America
  • Middle East & Africa
    • Saudi Arabia
    • UAE
    • South Africa
    • Rest of Middle East & Africa

TABLE OF CONTENTS

1. Introduction

  • 1.1. Market Definition
  • 1.2. Market Scope
  • 1.3. Research Methodology
  • 1.4. Assumptions & Limitations

2. Executive Summary

3. Market Overview

  • 3.1. Introduction
  • 3.2. Market Dynamics
    • 3.2.1. Drivers
    • 3.2.2. Restraints
    • 3.2.3. Opportunities
    • 3.2.4. Challenges
  • 3.3. Impact of Generative AI and Edge Computing on AI Chips
  • 3.4. Regulatory Landscape & Semiconductor Trade Policies
  • 3.5. Porter's Five Forces Analysis

4. Global AI Chip Market, by Chip Type

  • 4.1. Introduction
  • 4.2. Graphics Processing Units (GPU)
  • 4.3. Central Processing Units (CPU)
  • 4.4. Application-Specific Integrated Circuits (ASIC)
  • 4.5. Tensor Processing Units (TPU)
  • 4.6. Field-Programmable Gate Arrays (FPGA)
  • 4.7. Neural Processing Units (NPU)
  • 4.8. Others (Neuromorphic Chips, Photonic Processors)

5. Global AI Chip Market, by Function

  • 5.1. Introduction
  • 5.2. Training
  • 5.3. Inference

6. Global AI Chip Market, by Processing Type

  • 6.1. Introduction
  • 6.2. Cloud/Data Center
  • 6.3. Edge

7. Global AI Chip Market, by Application

  • 7.1. Introduction
  • 7.2. Data Centers & Cloud Computing
  • 7.3. Autonomous Vehicles & ADAS
  • 7.4. Consumer Electronics (Smartphones, PCs, Wearables)
  • 7.5. Industrial IoT & Robotics
  • 7.6. Healthcare & Medical Imaging
  • 7.7. Natural Language Processing & Generative AI
  • 7.8. Others (Smart Cities, Surveillance, Gaming)

8. Global AI Chip Market, by End-use

  • 8.1. Introduction
  • 8.2. Data Centers & Cloud
  • 8.3. Automotive
  • 8.4. Consumer Electronics
  • 8.5. Industrial
  • 8.6. Healthcare
  • 8.7. Telecommunications
  • 8.8. Others (Aerospace & Defense, Financial Services)

9. Global AI Chip Market, by Region

  • 9.1. Introduction
  • 9.2. North America
    • 9.2.1. U.S.
    • 9.2.2. Canada
  • 9.3. Europe
    • 9.3.1. Germany
    • 9.3.2. France
    • 9.3.3. U.K.
    • 9.3.4. Italy
    • 9.3.5. Spain
    • 9.3.6. Netherlands
    • 9.3.7. Rest of Europe
  • 9.4. Asia-Pacific
    • 9.4.1. China
    • 9.4.2. India
    • 9.4.3. Japan
    • 9.4.4. South Korea
    • 9.4.5. Taiwan
    • 9.4.6. Southeast Asia
    • 9.4.7. Australia
    • 9.4.8. Rest of Asia-Pacific
  • 9.5. Latin America
    • 9.5.1. Brazil
    • 9.5.2. Mexico
    • 9.5.3. Rest of Latin America
  • 9.6. Middle East & Africa
    • 9.6.1. Saudi Arabia
    • 9.6.2. UAE
    • 9.6.3. South Africa
    • 9.6.4. Rest of Middle East & Africa

10. Competitive Landscape

  • 10.1. Overview
  • 10.2. Key Growth Strategies
  • 10.3. Competitive Benchmarking
  • 10.4. Competitive Dashboard
    • 10.4.1. Industry Leaders
    • 10.4.2. Market Differentiators
    • 10.4.3. Vanguards
    • 10.4.4. Emerging Companies
  • 10.5. Market Ranking / Positioning Analysis of Key Players, 2025

11. Company Profiles (Manufacturers & Providers)

  • 11.1. NVIDIA Corporation
  • 11.2. Intel Corporation
  • 11.3. Advanced Micro Devices Inc. (AMD)
  • 11.4. Qualcomm Technologies Inc.
  • 11.5. Google LLC (Alphabet Inc.)
  • 11.6. Apple Inc.
  • 11.7. Microsoft Corporation
  • 11.8. Amazon Web Services Inc.
  • 11.9. Broadcom Inc.
  • 11.10. Samsung Electronics Co., Ltd.
  • 11.11. Taiwan Semiconductor Manufacturing Company (TSMC)
  • 11.12. Cerebras Systems
  • 11.13. Groq Inc.
  • 11.14. Tenstorrent
  • 11.15. SambaNova Systems
  • 11.16. Graphcore
  • 11.17. Hailo
  • 11.18. Habana Labs (Intel)
  • 11.19. Biren Technology
  • 11.20. Cambricon Technologies

12. Appendix

  • 12.1. Questionnaire
  • 12.2. Related Reports