查看购物车
  • Traditional Chinese
  • English
  • Japanese
封面
市场调查报告书
商品编码
1833599

2032 年人工智慧优化晶片市场预测：按晶片类型、处理类型、技术、应用、最终用户和地区进行的全球分析

Artificial Intelligence Optimized Chips Market Forecasts to 2032 - Global Analysis By Chip Type (GPU, ASIC, FPGA, and Other Chip Types), Processing Type, Technology, 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个工作天内

价格

根据 Stratistics MRC 的数据，全球人工智慧优化晶片市场预计在 2025 年达到 948 亿美元，到 2032 年将达到 5,759 亿美元，预测期内的复合年增长率为 29.4%。

人工智慧优化晶片专注于先进的半导体解决方案，专为加速深度学习、自然语言处理和电脑视觉等人工智慧工作负载而设计。与通用处理器不同，这些晶片整合了 GPU、TPU 和 NPU 等专用架构，以提高速度、效率和可扩展性。云端运算、自动驾驶汽车、机器人、智慧型装置等领域日益增长的需求正在推动这些晶片的快速普及。随着各行各业对人工智慧的采用日益广泛，市场正在见证重大创新和投资，使其成为全球数位转型的关键推动力。

据半导体行业协会称，受数据中心和边缘运算需求的推动，到 2027 年，人工智慧晶片的需求预计将以每年 30% 的速度成长。

深度学习的进展

现代神经网络，尤其是大型语言模型和复杂的电脑视觉系统，需要强大的平行处理能力，而通用 CPU 无法有效率地提供这种能力。这使得对 GPU 和 TPU 等专用硬体的需求变得至关重要，这些硬体的架构旨在加速矩阵运算和训练工作负载。因此，晶片製造商正在竞相开发更强大、更有效率的处理器，以处理下一代 AI 模型的运算负载，从而刺激市场大幅成长。

开发成本高

研发阶段需要对专业工程人才和先进设计软体进行巨额投资。此外，为了提高性能和能源效率而缩小奈米製程节点，会倍增製造成本，新建製造厂的成本高达数十亿美元。这些不断上升的成本可能会将市场力量集中在少数资金雄厚的科技巨头和老牌半导体公司手中，使规模较小的创新者和新兴企业难以竞争，并抑制市场上技术解决方案的多样性。

边缘运算的兴起

随着物联网设备、智慧摄影机和自动驾驶汽车等资料来源的爆炸性增长，人们越来越需要在本地而非远端云端资料中心处理这些资讯。这种转变需要一种新型低功耗、高效的AI晶片，能够直接在装置上执行推理任务，从而降低延迟、节省频宽并增强资料隐私。这一趋势正在激发创新，并催生出一个充满活力、快速成长的边缘AI处理器细分市场，涵盖从製造业到消费性电子的各个领域。

地缘政治紧张局势

不断升级的地缘政治衝突，尤其是美国之间的衝突，对全球人工智慧晶片供应链构成了重大威胁。这些紧张局势表现为贸易限制、出口管制以及对先进半导体技术的关税，可能扰乱关键零件和製造设备的流通。这种分散化导致了市场碎片化，迫使企业建立成本高昂的冗余供应链，并为长期规划带来了不确定性。这种环境不仅阻碍了全球合作与创新，还可能导致全球市场相关人员的成本膨胀和产品开发进度延迟。

COVID-19的影响：

疫情最初透过工厂关闭和供应链瓶颈扰乱了人工智慧晶片市场，导致生产延迟和零件短缺。然而，它也成为数位转型的强大催化剂。远距办公、电子商务的激增以及物流和医疗诊断领域对人工智慧主导解决方案的采用，增加了对运算能力的需求。这些双重影响凸显了人工智慧基础设施的关键作用，最终加速了对云端运算和资料中心的投资，并迅速催生了对先进高效能晶片的需求，以支援更加依赖数位化的全球经济。

GPU（图形处理单元）部分预计将成为预测期内最大的部分

预计在预测期内，GPU（图形处理器）领域将占据最大的市场份额。 GPU 最初设计用于渲染复杂的图形，其大规模平行架构非常适合训练深度学习模型所需的矩阵和向量运算。此外，其成熟的软体生态系统（包括 CUDA 等平台）为开发人员提供了有效利用其强大功能的重要工具。这种平行处理能力，加上广泛的开发人员支持，使 GPU 成为人工智慧研究和资料中心的预设选择，并巩固了其在市场上的主导地位。

边缘处理领域预计将在预测期内实现最高复合年增长率

边缘处理领域预计将在预测期内呈现最高成长率，这反映了产业向分散式智慧的决定性转变。随着连网物联网设备数量的快速增长，在边缘本地处理资料对于最大限度地降低延迟、节省频宽并确保即时应用的运作可靠性至关重要。这需要新一代人工智慧晶片，它不仅功能强大，而且节能高效、结构紧凑。因此，创新的重点是开发专门用于从自动驾驶汽车到智慧家电等各种应用的处理器，从而推动该领域的爆炸式增长。

占比最大的地区：

预计北美将在预测期内占据最大的市场份额。该地区汇聚了NVIDIA、英特尔和AMD等全球领先的科技巨头，以及Google和微软等超大规模资料中心业者，后者是AI晶片技术的主要消费者和创新者。此外，大量的创业投资资金筹措、政府对AI研究的大力支持以及金融、医疗保健和云端运算等关键领域对AI的早期广泛应用，共同打造了一个强大而成熟的生态系统，使其有望主导全球市场。

复合年增长率最高的地区：

预计亚太地区在预测期内的复合年增长率最高。这项成长主要得益于中国、日本和韩国等国家政府主导的大规模倡议旨在大力推动国内半导体製造和人工智慧发展。此外，庞大的电子製造基地、快速数位化的工业部门以及产生大量资料集的庞大人口，为人工智慧的应用提供了肥沃的土壤。这些动态，加上本土科技巨头不断增加的投资，使亚太地区成为成长最快的市场。

免费客製化服务

此报告的订阅者可以使用以下免费自订选项之一：

  • 公司简介
    • 对最多三家其他市场公司进行全面分析
    • 主要企业的SWOT分析（最多3家公司）
  • 区域细分
    • 根据客户兴趣对主要国家进行的市场估计、预测和复合年增长率（註：基于可行性检查）
  • 竞争基准化分析
    • 根据产品系列、地理分布和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 前言

  • 概述
  • 相关利益者
  • 调查范围
  • 调查方法
    • 资料探勘
    • 数据分析
    • 数据检验
    • 研究途径
  • 研究材料
    • 主要研究资料
    • 次级研究资讯来源
    • 先决条件

第三章市场走势分析

  • 驱动程式
  • 抑制因素
  • 机会
  • 威胁
  • 技术分析
  • 应用分析
  • 最终用户分析
  • 新兴市场
  • COVID-19的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方的议价能力
  • 替代品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

第五章全球人工智慧优化晶片市场（按晶片类型）

  • GPU（图形处理单元）
  • ASIC（专用积体电路）
    • TPU（张量处理单元）
    • 其他客製化 ASIC
  • FPGA（现场可程式化闸阵列）
  • 带有AI加速器的CPU（中央处理器）
  • NPU（神经处理单元）
  • 其他尖端类型

6. 全球人工智慧优化晶片市场（按处理类型）

  • 边缘处理
  • 云端处理

第七章全球人工智慧优化晶片市场（按技术）

  • 系统晶片(SoC)
  • 系统级封装(SiP)
  • 多晶片模组（MCM）
  • 其他技术

第八章全球人工智慧优化晶片市场（按应用）

  • 自然语言处理（NLP）
  • 电脑视觉
  • 机器人流程自动化（RPA）
  • 网路安全
  • 自动驾驶汽车和ADAS
  • 其他应用

第九章全球人工智慧优化晶片市场（按最终用户）

  • 医疗保健和生命科学
  • BFSI（银行、金融服务和保险）
  • 汽车和运输
  • 零售与电子商务
  • 资讯科技/通讯
  • 政府和国防
  • 製造业
  • 能源与公共产业
  • 媒体与娱乐
  • 其他最终用户

第 10 章全球人工智慧优化晶片市场（按地区）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲国家
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 其他亚太地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十一章 重大进展

  • 协议、伙伴关係、合作和合资企业
  • 收购与合併
  • 新产品发布
  • 业务扩展
  • 其他关键策略

第 12 章：公司概况

  • NVIDIA
  • AMD
  • Intel
  • Qualcomm
  • Apple
  • Google（Alphabet）
  • Amazon（AWS）
  • Huawei
  • Samsung
  • MediaTek
  • Broadcom
  • Arm
  • Graphcore
  • Cerebras Systems
  • SambaNova Systems
  • Groq
  • Tenstorrent
  • Cambricon
Product Code: SMRC31432

According to Stratistics MRC, the Global Artificial Intelligence Optimized Chips Market is accounted for $94.8 billion in 2025 and is expected to reach $575.9 billion by 2032 growing at a CAGR of 29.4% during the forecast period. Artificial Intelligence Optimized Chips focuses on advanced semiconductor solutions specifically designed to accelerate AI workloads, including deep learning, natural language processing, and computer vision. Unlike general-purpose processors, these chips integrate specialized architectures such as GPUs, TPUs, and NPUs for enhanced speed, efficiency, and scalability. Growing demand across cloud computing, autonomous vehicles, robotics, and smart devices is driving rapid adoption. With increasing AI deployment across industries, the market is witnessing significant innovation and investments, making it a critical enabler of digital transformation globally.

According to the Semiconductor Industry Association, AI chip demand is expected to grow 30% annually through 2027, driven by data center and edge computing needs.

Market Dynamics:

Driver:

Advancements in Deep Learning

Modern neural networks, particularly large language models and complex computer vision systems, demand immense parallel processing power that general-purpose CPUs cannot efficiently provide. This has created a critical need for specialized hardware like GPUs and TPUs that are architecturally designed to accelerate matrix operations and training workloads. Consequently, chipmakers are in a continuous race to develop more powerful and efficient processors specifically to keep up with the computational hunger of next-generation AI models, thereby fueling significant market growth.

Restraint:

High Development Costs

The research and development phase requires immense investment in specialized engineering talent and sophisticated design software. Moreover, moving to smaller nanometer process nodes for enhanced performance and power efficiency exponentially increases fabrication costs, with new fabrication plants costing billions of dollars. These soaring expenses concentrate market power among a few well-capitalized tech giants and established semiconductor players, making it exceptionally difficult for smaller innovators and startups to compete and potentially stifling the diversity of technological solutions in the market.

Opportunity:

Edge Computing Expansion

As data generation explodes from sources like IoT devices, smart cameras, and autonomous vehicles, there is a growing need to process this information locally rather than in distant cloud data centers. This shift demands a new class of low-power, high-efficiency AI chips that can perform inference tasks directly on-device, reducing latency, saving bandwidth, and enhancing data privacy. This trend is driving innovation and creating a vibrant, fast-growing segment for specialized edge-AI processors across industries from manufacturing to consumer electronics.

Threat:

Geopolitical Tensions

Escalating geopolitical disputes, particularly between the US and China, pose a significant threat to the global AI chip supply chain. These tensions have materialized as trade restrictions, export controls on advanced semiconductor technology, and tariffs, which can disrupt the flow of essential components and manufacturing equipment. Such fragmentation forces the bifurcation of the market, compels companies to build costly duplicate supply chains, and creates uncertainty in long-term planning. This environment not only hampers global collaboration and innovation but also risks inflating costs and delaying product development timelines for market players worldwide.

Covid-19 Impact:

The pandemic initially disrupted the AI chip market through factory closures and supply chain bottlenecks, causing production delays and component shortages. However, it simultaneously acted as a powerful accelerator for digital transformation. The surge in remote work, e-commerce, and the adoption of AI-driven solutions for logistics and healthcare diagnostics intensified the demand for computational power. This dual effect underscored the critical role of AI infrastructure, ultimately accelerating cloud and data center investments and fast-tracking the need for advanced, efficient chips to support a more digitally dependent global economy.

The GPU (Graphics Processing Unit) segment is expected to be the largest during the forecast period

The GPU (Graphics Processing Unit) segment is expected to account for the largest market share during the forecast period. Originally designed for rendering complex graphics, the GPU's massively parallel architecture is exceptionally well-suited for the matrix and vector calculations fundamental to training deep learning models. Furthermore, its established, mature software ecosystem, including platforms like CUDA, provides developers with the essential tools to efficiently harness its power. This combination of parallel processing prowess and extensive developer support makes GPUs the default choice for AI research and data centers, securing their leading market position.

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

Over the forecast period, the edge processing segment is predicted to witness the highest growth rate, reflecting the industry's decisive shift towards decentralized intelligence. As the number of connected IoT devices skyrockets, processing data locally at the edge becomes critical to minimize latency, conserve bandwidth, and ensure operational reliability for real-time applications. This demands a new generation of AI chips that are not just powerful, but also highly power-efficient and compact. Consequently, intense innovation is focused on creating specialized processors for applications ranging from autonomous vehicles to smart appliances, driving explosive growth in this segment.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share. The region is home to the world's leading technology behemoths, such as NVIDIA, Intel, and AMD, and hyperscalers like Google and Microsoft, who are both major consumers and innovators of AI chip technology. Moreover, substantial venture capital funding, strong governmental support for AI research, and early, widespread adoption of AI across key sectors like finance, healthcare, and cloud computing create a robust and mature ecosystem that consolidates its dominant position in the global market.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR. his growth is primarily fueled by massive government-led initiatives in countries like China, Japan, and South Korea that aggressively promote domestic semiconductor manufacturing and AI development. Additionally, the presence of a massive electronics manufacturing base, a rapidly digitizing industrial sector, and an enormous population generating vast datasets provide a fertile ground for AI adoption. These dynamics, combined with rising investments from local tech giants, position Asia Pacific as the fastest-growing market.

Key players in the market

Some of the key players in Artificial Intelligence Optimized Chips Market include NVIDIA, AMD, Intel, Qualcomm, Apple, Google (Alphabet), Amazon (AWS), Huawei, Samsung, MediaTek, Broadcom, Arm, Graphcore, Cerebras Systems, SambaNova Systems, Groq, Tenstorrent, and Cambricon.

Key Developments:

In September 2025, NVIDIA and Intel announced a collaboration to develop AI infrastructure and personal computing products integrating NVIDIA RTX GPU chiplets with Intel x86 SoCs.

In September 2025, Qualcomm announced Snapdragon 8 Elite Gen 5 chip for smartphones in 2026, featuring in-house Oryon CPU, 3nm TSMC process, and enhanced AI agent capabilities for real-time personalized AI experiences.

In May 2025, AMD positioned itself as an AI powerhouse at Computex 2025 with new Radeon AI PRO R9700 workstation GPU for edge AI and Ryzen AI 300 series chips, claiming competitive AI performance including 15% lead over Apple's M4 Pro.

Chip Types Covered:

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

Processing Types Covered:

  • Edge Processing
  • Cloud Processing

Technologies Covered:

  • System-on-Chip (SoC)
  • System-in-Package (SiP)
  • Multi-Chip Module (MCM)
  • Other Technologies

Applications Covered:

  • Natural Language Processing (NLP)
  • Computer Vision
  • Robotic Process Automation (RPA)
  • Network Security
  • Autonomous Vehicles & ADAS
  • Other Applications

End Users Covered:

  • Healthcare & Life Sciences
  • BFSI (Banking, Financial Services, and Insurance)
  • Automotive & Transportation
  • Retail & E-commerce
  • IT & Telecommunications
  • Government & Defense
  • Manufacturing
  • Energy & Utilities
  • Media & Entertainment
  • 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 Artificial Intelligence Optimized Chips Market, By Chip Type

  • 5.1 Introduction
  • 5.2 GPU (Graphics Processing Unit)
  • 5.3 ASIC (Application-Specific Integrated Circuit)
    • 5.3.1 TPU (Tensor Processing Unit)
    • 5.3.2 Other Custom ASICs
  • 5.4 FPGA (Field-Programmable Gate Array)
  • 5.5 CPU (Central Processing Unit) with AI Accelerators
  • 5.6 NPU (Neural Processing Unit)
  • 5.7 Other Chip Types

6 Global Artificial Intelligence Optimized Chips Market, By Processing Type

  • 6.1 Introduction
  • 6.2 Edge Processing
  • 6.3 Cloud Processing

7 Global Artificial Intelligence Optimized Chips Market, By Technology

  • 7.1 Introduction
  • 7.2 System-on-Chip (SoC)
  • 7.3 System-in-Package (SiP)
  • 7.4 Multi-Chip Module (MCM)
  • 7.5 Other Technologies

8 Global Artificial Intelligence Optimized Chips Market, By Application

  • 8.1 Introduction
  • 8.2 Natural Language Processing (NLP)
  • 8.3 Computer Vision
  • 8.4 Robotic Process Automation (RPA)
  • 8.5 Network Security
  • 8.6 Autonomous Vehicles & ADAS
  • 8.7 Other Applications

9 Global Artificial Intelligence Optimized Chips Market, By End User

  • 9.1 Introduction
  • 9.2 Healthcare & Life Sciences
  • 9.3 BFSI (Banking, Financial Services, and Insurance)
  • 9.4 Automotive & Transportation
  • 9.5 Retail & E-commerce
  • 9.6 IT & Telecommunications
  • 9.7 Government & Defense
  • 9.8 Manufacturing
  • 9.9 Energy & Utilities
  • 9.10 Media & Entertainment
  • 9.11 Other End Users

10 Global Artificial Intelligence Optimized Chips Market, By Geography

  • 10.1 Introduction
  • 10.2 North America
    • 10.2.1 US
    • 10.2.2 Canada
    • 10.2.3 Mexico
  • 10.3 Europe
    • 10.3.1 Germany
    • 10.3.2 UK
    • 10.3.3 Italy
    • 10.3.4 France
    • 10.3.5 Spain
    • 10.3.6 Rest of Europe
  • 10.4 Asia Pacific
    • 10.4.1 Japan
    • 10.4.2 China
    • 10.4.3 India
    • 10.4.4 Australia
    • 10.4.5 New Zealand
    • 10.4.6 South Korea
    • 10.4.7 Rest of Asia Pacific
  • 10.5 South America
    • 10.5.1 Argentina
    • 10.5.2 Brazil
    • 10.5.3 Chile
    • 10.5.4 Rest of South America
  • 10.6 Middle East & Africa
    • 10.6.1 Saudi Arabia
    • 10.6.2 UAE
    • 10.6.3 Qatar
    • 10.6.4 South Africa
    • 10.6.5 Rest of Middle East & Africa

11 Key Developments

  • 11.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 11.2 Acquisitions & Mergers
  • 11.3 New Product Launch
  • 11.4 Expansions
  • 11.5 Other Key Strategies

12 Company Profiling

  • 12.1 NVIDIA
  • 12.2 AMD
  • 12.3 Intel
  • 12.4 Qualcomm
  • 12.5 Apple
  • 12.6 Google (Alphabet)
  • 12.7 Amazon (AWS)
  • 12.8 Huawei
  • 12.9 Samsung
  • 12.10 MediaTek
  • 12.11 Broadcom
  • 12.12 Arm
  • 12.13 Graphcore
  • 12.14 Cerebras Systems
  • 12.15 SambaNova Systems
  • 12.16 Groq
  • 12.17 Tenstorrent
  • 12.18 Cambricon

List of Tables

  • Table 1 Global Artificial Intelligence Optimized Chips Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global Artificial Intelligence Optimized Chips Market Outlook, By Chip Type (2024-2032) ($MN)
  • Table 3 Global Artificial Intelligence Optimized Chips Market Outlook, By GPU (Graphics Processing Unit) (2024-2032) ($MN)
  • Table 4 Global Artificial Intelligence Optimized Chips Market Outlook, By ASIC (Application-Specific Integrated Circuit) (2024-2032) ($MN)
  • Table 5 Global Artificial Intelligence Optimized Chips Market Outlook, By TPU (Tensor Processing Unit) (2024-2032) ($MN)
  • Table 6 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Custom ASICs (2024-2032) ($MN)
  • Table 7 Global Artificial Intelligence Optimized Chips Market Outlook, By FPGA (Field-Programmable Gate Array) (2024-2032) ($MN)
  • Table 8 Global Artificial Intelligence Optimized Chips Market Outlook, By CPU (Central Processing Unit) with AI Accelerators (2024-2032) ($MN)
  • Table 9 Global Artificial Intelligence Optimized Chips Market Outlook, By NPU (Neural Processing Unit) (2024-2032) ($MN)
  • Table 10 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Chip Types (2024-2032) ($MN)
  • Table 11 Global Artificial Intelligence Optimized Chips Market Outlook, By Processing Type (2024-2032) ($MN)
  • Table 12 Global Artificial Intelligence Optimized Chips Market Outlook, By Edge Processing (2024-2032) ($MN)
  • Table 13 Global Artificial Intelligence Optimized Chips Market Outlook, By Cloud Processing (2024-2032) ($MN)
  • Table 14 Global Artificial Intelligence Optimized Chips Market Outlook, By Technology (2024-2032) ($MN)
  • Table 15 Global Artificial Intelligence Optimized Chips Market Outlook, By System-on-Chip (SoC) (2024-2032) ($MN)
  • Table 16 Global Artificial Intelligence Optimized Chips Market Outlook, By System-in-Package (SiP) (2024-2032) ($MN)
  • Table 17 Global Artificial Intelligence Optimized Chips Market Outlook, By Multi-Chip Module (MCM) (2024-2032) ($MN)
  • Table 18 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Technologies (2024-2032) ($MN)
  • Table 19 Global Artificial Intelligence Optimized Chips Market Outlook, By Application (2024-2032) ($MN)
  • Table 20 Global Artificial Intelligence Optimized Chips Market Outlook, By Natural Language Processing (NLP) (2024-2032) ($MN)
  • Table 21 Global Artificial Intelligence Optimized Chips Market Outlook, By Computer Vision (2024-2032) ($MN)
  • Table 22 Global Artificial Intelligence Optimized Chips Market Outlook, By Robotic Process Automation (RPA) (2024-2032) ($MN)
  • Table 23 Global Artificial Intelligence Optimized Chips Market Outlook, By Network Security (2024-2032) ($MN)
  • Table 24 Global Artificial Intelligence Optimized Chips Market Outlook, By Autonomous Vehicles & ADAS (2024-2032) ($MN)
  • Table 25 Global Artificial Intelligence Optimized Chips Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 26 Global Artificial Intelligence Optimized Chips Market Outlook, By End User (2024-2032) ($MN)
  • Table 27 Global Artificial Intelligence Optimized Chips Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 28 Global Artificial Intelligence Optimized Chips Market Outlook, By BFSI (Banking, Financial Services, and Insurance) (2024-2032) ($MN)
  • Table 29 Global Artificial Intelligence Optimized Chips Market Outlook, By Automotive & Transportation (2024-2032) ($MN)
  • Table 30 Global Artificial Intelligence Optimized Chips Market Outlook, By Retail & E-commerce (2024-2032) ($MN)
  • Table 31 Global Artificial Intelligence Optimized Chips Market Outlook, By IT & Telecommunications (2024-2032) ($MN)
  • Table 32 Global Artificial Intelligence Optimized Chips Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 33 Global Artificial Intelligence Optimized Chips Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 34 Global Artificial Intelligence Optimized Chips Market Outlook, By Energy & Utilities (2024-2032) ($MN)
  • Table 35 Global Artificial Intelligence Optimized Chips Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 36 Global Artificial Intelligence Optimized Chips Market Outlook, By Other End Users (2024-2032) ($MN)

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