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2032 年 AI 加速器市場預測：按類型、技術、應用、最終用戶和地區進行的全球分析

AI Accelerator Market Forecasts to 2032 - Global Analysis By 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個工作天內

價格

根據 Stratistics MRC 的數據，全球 AI 加速器市場規模預計在 2025 年達到 335.6 億美元，到 2032 年將達到 2,257.7 億美元，預測期內的複合年成長率為 31.3%。

AI加速器是專門設計的硬體單元，旨在提高人工智慧（包括機器學習和深度學習）運算的速度和效率。 GPU、TPU和NPU等設備增強了資料處理和運算能力，支援更快的AI模型訓練和推理。這些加速器廣泛應用於雲端服務、自動駕駛技術和邊緣運算等領域，能夠處理密集型演算法和大量數據，同時提升效能、能源效率和系統可擴展性。

業內專家預測，到 2025 年底，生成式人工智慧晶片市場規模將達到 500 億美元，到 2027 年將增加至約 7,000 億美元。

對高效能運算（HPC）的需求不斷成長

即時數據處理和複雜模擬的需求日益成長，推動著各行各業對高效能運算的採用。自動駕駛、基因組學和金融建模等領域需要龐大的運算吞吐量，這推動了人們對人工智慧加速器的興趣。企業擴大採用平行處理架構來高效​​處理大規模工作負載。隨著人工智慧模型日益複雜，對更快訓練和推理速度的需求也日益成長。雲端服務供應商和超大規模企業正在大力投資客製化晶片，以最佳化效能並降低延遲。運算需求的指數級成長使得人工智慧加速器成為下一代數位基礎設施的關鍵推動者。

整合複雜性

將 AI 加速器整合到現有 IT 生態系統中，將為企業帶來巨大的技術障礙。與舊系統、軟體堆疊和資料管道的相容性問題往往會延遲部署進度。開發人員必須駕馭各種框架、API 和硬體配置，才能確保無縫運​​作。缺乏標準化的介面和工具鏈會給整合帶來沉重的負擔，尤其對於中小型企業而言。為了充分利用加速器的功能，需要投入大量資金來培訓員工並重組工作流程。這些挑戰可能會減緩 AI 增強解決方案的採用速度，並限制其在整個組織中的可擴展性。

節能晶片設計的進步

低功耗架構和熱最佳化的突破為部署AI加速器開啟了新的可能性。晶片製造商正在利用先進的封裝、3D堆疊和新材料來降低消費量，同時又不犧牲性能。這些創新使邊緣設備和行動平台能夠持續運行複雜的AI工作負載。監管壓力和企業永續性目標正在進一步推動向更綠色的計算解決方案的轉變。新興企業和成熟企業都在探索神經形態和模擬運算範式，以突破效率的界限。隨著能源成本的上升，對高性能且環保的加速器的需求為市場擴張創造了肥沃的土壤。

與通用 CPU/GPU 的激烈競爭

通用處理器的普及和不斷發展對專用AI加速器構成了競爭威脅。 CPU和GPU日益針對AI工作負載進行最佳化，縮小了與專用晶片之間的效能差距。它們的多功能性和廣泛的開發者支援使其對成本敏感的應用具有吸引力。主流供應商正在將AI功能捆綁到主流處理器中，從而減少了某些用例對單獨加速器的需求。這種商品化可能會削弱利基加速器解決方案的差異化。如果在性能或效率方面沒有明顯的優勢，AI加速器可能難以維持市場發展動能。

COVID-19的影響：

疫情擾亂了全球供應鏈，減緩了人工智慧加速器組件的製造和交付。封鎖和遠端辦公要求將需求轉向雲端基礎的推理和邊緣運算解決方案。晶片短缺和物流瓶頸影響了生產和部署計劃。然而，這場危機加速了數位轉型，企業紛紛投資人工智慧以實現營運自動化和最佳化。醫療保健、物流和網路安全領域擴大採用人工智慧加速器來應對疫情相關的挑戰。後疫情時代策略如今強調供應鏈韌性、分散式運算模式和靈活的部署架構。

資料中心部分預計將成為預測期內最大的部分

資料中心領域預計將在預測期內佔據最大的市場佔有率，因為它在動力來源大規模人工智慧應用方面發揮核心作用。超大規模資料中心業者和雲端服務供應商正在整合客製化加速器，以提高吞吐量並降低能源成本。這些設施支援各種需要高效能運算的工作負載，從自然語言處理到推薦引擎。冷卻系統和工作負載編配的創新正在提高加速器的利用率和效率。人工智慧即服務平台的興起進一步推動了對可擴展、富含建議的基礎設施的需求。隨著企業轉向雲端原生架構，資料中心仍是人工智慧部署的支柱。

預計醫療保健產業在預測期內將實現最高複合年成長率

預計醫療保健產業將在預測期內實現最高成長率，這得益於人工智慧診斷和個人化醫療的蓬勃發展。醫院和研究機構正在利用加速器進行影像分析、基因組學和藥物研發。人工智慧與臨床工作流程的整合正在增強決策能力和病患預後。對數位醫療和遠端醫療的監管支持正在推動基礎設施投資。加速器正在推動穿戴式裝置和遠端監控系統的即時數據處理。

比最大的地區

由於數位化進程的快速推進和基礎設施的擴張，預計亞太地區將在預測期內佔據最大的市場佔有率。中國、印度和韓國等國正大力投資半導體製造和人工智慧研究。政府支持的舉措正在推動國內晶片研發，減少對進口的依賴。該地區在金融、製造業和智慧城市領域的人工智慧應用正呈現強勁成長勢頭。全球科技公司與本地企業之間的策略合作夥伴關係正在加速技術創新和部署。憑藉龐大的用戶群和不斷成長的運算需求，亞太地區正逐漸成為加速器領域的主導力量。

複合年成長率最高的地區：

在預測期內，北美預計將呈現最高的複合年成長率，這得益於其在人工智慧創新和創業投資資金籌措的主導。美國擁有主要的晶片設計公司、雲端服務供應商和人工智慧新興企業，推動下一代加速器的發展。監管機構正在簡化新計算技術的核准途徑，以促進其更快的商業化。企業正在將加速器整合到混合雲和邊緣環境中，以提高效能和靈活性。該地區受益於由開發者、研究機構和企業採用者組成的成熟生態系統。隨著人工智慧應用的多樣化，北美將繼續引領全球加速器的應用。

免費客製化服務：

此報告的訂閱者可以使用以下免費自訂選項之一：

  • 公司簡介
    • 全面分析其他市場參與者（最多 3 家公司）
    • 主要企業的SWOT分析（最多3家公司）
  • 區域細分
    • 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進行基準化分析

目錄

第1章執行摘要

第2章 前言

  • 概述
  • 相關利益者
  • 調查範圍
  • 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
    • 二手研究資料
    • 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
  • 買方的議價能力
  • 替代品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

第5章全球人工智慧加速器市場類型

  • 圖形處理單元（GPU）
  • 現場可程式閘陣列（FPGA）
  • 專用積體電路（ASIC）
  • 張量處理單元（TPU）
  • 其他類型

第6章 全球人工智慧加速器市場（按技術）

  • 雲端基礎的AI加速器
  • 基於邊緣的AI加速器
  • 本地 AI 加速器

第7章全球人工智慧加速器市場（按應用）

  • 資料中心
  • 機器人技術
  • 雲端運算
  • 自動駕駛汽車
  • 消費性電子產品
  • 醫療保健和生命科學
  • 其他用途

第8章全球人工智慧加速器市場（按最終用戶）

  • 資訊科技/通訊
  • 製造業
  • 車
  • 航太/國防
  • 衛生保健
  • 零售
  • 其他最終用戶

第9章全球人工智慧加速器市場（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10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11章 公司概況

  • NVIDIA Corporation
  • Amazon Web Services
  • Advanced Micro Devices, Inc.（AMD）
  • Alphabet Inc.
  • Intel Corporation
  • Graphcore Limited
  • Google LLC
  • Axelera AI
  • Qualcomm Technologies, Inc.
  • Meta Platforms, Inc.
  • Apple Inc.
  • Samsung Electronics Co., Ltd.
  • Microsoft Corporation
  • IBM Corporation
  • Taiwan Semiconductor Manufacturing Company（TSMC）
Product Code: SMRC31636

According to Stratistics MRC, the Global AI Accelerator Market is accounted for $33.56 billion in 2025 and is expected to reach $225.77 billion by 2032 growing at a CAGR of 31.3% during the forecast period. An AI Accelerator is a dedicated hardware unit created to boost the speed and efficiency of artificial intelligence operations, including machine learning and deep learning. Devices like GPUs, TPUs, and NPUs enhance data handling and computational power, supporting faster AI model training and inference. Widely applied in areas such as cloud services, autonomous technologies, and edge computing, these accelerators handle intensive algorithms and vast data volumes while improving performance, energy efficiency, and system scalability.

According to Industry Experts, the market for chips powering generative AI will hit USD 50 billion by the end of 2025, with projections to rise to approximately USD 700 billion by 2027.

Market Dynamics:

Driver:

Growing need for high-performance computing (HPC)

The escalating demand for real-time data processing and complex simulations is propelling the adoption of high-performance computing across industries. Sectors such as autonomous driving, genomics, and financial modeling require immense computational throughput, driving interest in AI accelerators. Enterprises are increasingly deploying parallel processing architectures to handle large-scale workloads efficiently. As AI models become more sophisticated, the need for faster training and inference speeds is intensifying. Cloud providers and hyperscalers are investing heavily in custom silicon to optimize performance and reduce latency. This surge in computational requirements is positioning AI accelerators as critical enablers of next-gen digital infrastructure.

Restraint:

Complexity of integration

Integrating AI accelerators into existing IT ecosystems presents significant technical hurdles for enterprises. Compatibility issues with legacy systems, software stacks, and data pipelines often slow deployment timelines. Developers must navigate diverse frameworks, APIs, and hardware configurations to ensure seamless operation. The lack of standardized interfaces and toolchains adds to the integration burden, especially for smaller firms. Training personnel and rearchitecting workflows to leverage accelerator capabilities requires substantial investment. These challenges can delay adoption and limit the scalability of AI-enhanced solutions across organizations.

Opportunity:

Advancements in energy-efficient chip designs

Breakthroughs in low-power architecture and thermal optimization are unlocking new possibilities for AI accelerator deployment. Chipmakers are leveraging advanced packaging, 3D stacking, and novel materials to reduce energy consumption without compromising performance. These innovations are enabling edge devices and mobile platforms to run complex AI workloads sustainably. Regulatory pressure and corporate sustainability goals are further incentivizing the shift toward greener compute solutions. Startups and incumbents alike are exploring neuromorphic and analog computing paradigms to push efficiency boundaries. As energy costs rise, demand for high-performance yet eco-friendly accelerators is creating fertile ground for market expansion.

Threat:

Intense competition from general-purpose CPUs/GPUs

The widespread availability and continual evolution of general-purpose processors pose a competitive threat to specialized AI accelerators. CPUs and GPUs are increasingly optimized for AI workloads, narrowing the performance gap with dedicated chips. Their versatility and broad developer support make them attractive for cost-sensitive applications. Major vendors are bundling AI capabilities into mainstream processors, reducing the need for discrete accelerators in some use cases. This commoditization risks eroding the differentiation of niche accelerator solutions. Without clear performance or efficiency advantages, AI accelerators may struggle to maintain market momentum.

Covid-19 Impact:

The pandemic disrupted global supply chains, delaying fabrication and delivery of AI accelerator components. Lockdowns and remote work mandates shifted demand toward cloud-based inference and edge computing solutions. Chip shortages and logistics bottlenecks impacted production schedules and deployment timelines. However, the crisis accelerated digital transformation, with enterprises investing in AI to automate and optimize operations. Healthcare, logistics, and cybersecurity sectors saw increased adoption of AI accelerators to manage pandemic-related challenges. Post-Covid strategies now emphasize supply chain resilience, distributed compute models, and flexible deployment architectures.

The data centers segment is expected to be the largest during the forecast period

The data centers segment is expected to account for the largest market share during the forecast period, due to its central role in powering large-scale AI applications. Hyperscalers and cloud providers are integrating custom accelerators to enhance throughput and reduce energy costs. These facilities support diverse workloads, from natural language processing to recommendation engines, requiring high-performance compute. Innovations in cooling systems and workload orchestration are improving accelerator utilization and efficiency. The rise of AI-as-a-service platforms is further driving demand for scalable, accelerator-rich infrastructure. As enterprises migrate to cloud-native architectures, data centers remain the backbone of AI deployment.

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

Over the forecast period, the healthcare segment is predicted to witness the highest growth rate, due to driven by the surge in AI-powered diagnostics and personalized medicine. Hospitals and research institutions are leveraging accelerators for imaging analysis, genomics, and drug discovery. The integration of AI into clinical workflows is enhancing decision-making and patient outcomes. Regulatory support for digital health and telemedicine is boosting infrastructure investments. Accelerators are enabling real-time data processing in wearable devices and remote monitoring systems.

Region with largest share:

During the forecast period, the Asia Pacific region is expected to hold the largest market share, fueled by rapid digitization and infrastructure expansion. Countries like China, India, and South Korea are investing heavily in semiconductor manufacturing and AI research. Government-backed initiatives are promoting domestic chip development and reducing reliance on imports. The region is witnessing strong growth in AI adoption across finance, manufacturing, and smart cities. Strategic collaborations between global tech firms and local players are accelerating innovation and deployment. With a vast user base and rising compute needs, Asia Pacific is emerging as a dominant force in the accelerator landscape.

Region with highest CAGR:

Over the forecast period, the North America region is anticipated to exhibit the highest CAGR, owing to its leadership in AI innovation and venture capital funding. The U.S. is home to major chip designers, cloud providers, and AI startups driving next-gen accelerator development. Regulatory bodies are streamlining approval pathways for emerging compute technologies, fostering rapid commercialization. Enterprises are integrating accelerators into hybrid cloud and edge environments to boost performance and agility. The region benefits from a mature ecosystem of developers, research institutions, and enterprise adopters. As AI applications diversify, North America continues to set the pace for global accelerator adoption.

Key players in the market

Some of the key players in AI Accelerator Market include NVIDIA Corporation, Amazon Web Services, Advanced Micro Devices, Inc. (AMD), Alphabet Inc., Intel Corporation, Graphcore Limited, Google LLC, Axelera AI, Qualcomm Technologies, Inc., Meta Platforms, Inc., Apple Inc., Samsung Electronics Co., Ltd., Microsoft Corporation, IBM Corporation, and Taiwan Semiconductor Manufacturing Company (TSMC).

Key Developments:

In September 2025, NVIDIA and OpenAI announced a letter of intent for a landmark strategic partnership to deploy at least 10 gigawatts of NVIDIA systems for OpenAI's next-generation AI infrastructure to train and run its next generation of models on the path to deploying superintelligence. To support this deployment including data center and power capacity, NVIDIA intends to invest up to $100 billion in OpenAI as the new NVIDIA systems are deployed.

In September 2025, Intel Corporation and NVIDIA announced a collaboration to jointly develop multiple generations of custom datacenter and PC products that accelerate applications and workloads across hyperscale, enterprise and consumer markets. The companies will focus on seamlessly connecting NVIDIA and Intel architectures using NVIDIA NVLink - integrating the strengths of NVIDIA's AI and accelerated computing with Intel's leading CPU technologies and x86 ecosystem to deliver cutting-edge solutions for customers.

Types Covered:

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

Technologies Covered:

  • Cloud-Based AI Accelerators
  • Edge-Based AI Accelerators
  • On-Premise AI Accelerators

Applications Covered:

  • Data Centers
  • Robotics
  • Cloud Computing
  • Autonomous Vehicles
  • Consumer Electronics
  • Healthcare & Life Sciences
  • Other Applications

End Users Covered:

  • IT & Telecom
  • Manufacturing
  • Automotive
  • Aerospace & Defense
  • Healthcare
  • Retail
  • 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 Accelerator Market, By Type

  • 5.1 Introduction
  • 5.2 Graphics Processing Unit (GPU)
  • 5.3 Field-Programmable Gate Array (FPGA)
  • 5.4 Application-Specific Integrated Circuit (ASIC)
  • 5.5 Tensor Processing Unit (TPU)
  • 5.6 Other Types

6 Global AI Accelerator Market, By Technology

  • 6.1 Introduction
  • 6.2 Cloud-Based AI Accelerators
  • 6.3 Edge-Based AI Accelerators
  • 6.4 On-Premise AI Accelerators

7 Global AI Accelerator Market, By Application

  • 7.1 Introduction
  • 7.2 Data Centers
  • 7.3 Robotics
  • 7.4 Cloud Computing
  • 7.5 Autonomous Vehicles
  • 7.6 Consumer Electronics
  • 7.7 Healthcare & Life Sciences
  • 7.8 Other Applications

8 Global AI Accelerator Market, By End User

  • 8.1 Introduction
  • 8.2 IT & Telecom
  • 8.3 Manufacturing
  • 8.4 Automotive
  • 8.5 Aerospace & Defense
  • 8.6 Healthcare
  • 8.7 Retail
  • 8.8 Other End Users

9 Global AI Accelerator Market, By Geography

  • 9.1 Introduction
  • 9.2 North America
    • 9.2.1 US
    • 9.2.2 Canada
    • 9.2.3 Mexico
  • 9.3 Europe
    • 9.3.1 Germany
    • 9.3.2 UK
    • 9.3.3 Italy
    • 9.3.4 France
    • 9.3.5 Spain
    • 9.3.6 Rest of Europe
  • 9.4 Asia Pacific
    • 9.4.1 Japan
    • 9.4.2 China
    • 9.4.3 India
    • 9.4.4 Australia
    • 9.4.5 New Zealand
    • 9.4.6 South Korea
    • 9.4.7 Rest of Asia Pacific
  • 9.5 South America
    • 9.5.1 Argentina
    • 9.5.2 Brazil
    • 9.5.3 Chile
    • 9.5.4 Rest of South America
  • 9.6 Middle East & Africa
    • 9.6.1 Saudi Arabia
    • 9.6.2 UAE
    • 9.6.3 Qatar
    • 9.6.4 South Africa
    • 9.6.5 Rest of Middle East & Africa

10 Key Developments

  • 10.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 10.2 Acquisitions & Mergers
  • 10.3 New Product Launch
  • 10.4 Expansions
  • 10.5 Other Key Strategies

11 Company Profiling

  • 11.1 NVIDIA Corporation
  • 11.2 Amazon Web Services
  • 11.3 Advanced Micro Devices, Inc. (AMD)
  • 11.4 Alphabet Inc.
  • 11.5 Intel Corporation
  • 11.6 Graphcore Limited
  • 11.7 Google LLC
  • 11.8 Axelera AI
  • 11.9 Qualcomm Technologies, Inc.
  • 11.10 Meta Platforms, Inc.
  • 11.11 Apple Inc.
  • 11.12 Samsung Electronics Co., Ltd.
  • 11.13 Microsoft Corporation
  • 11.14 IBM Corporation
  • 11.15 Taiwan Semiconductor Manufacturing Company (TSMC)

List of Tables

  • Table 1 Global AI Accelerator Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global AI Accelerator Market Outlook, By Type (2024-2032) ($MN)
  • Table 3 Global AI Accelerator Market Outlook, By Graphics Processing Unit (GPU) (2024-2032) ($MN)
  • Table 4 Global AI Accelerator Market Outlook, By Field-Programmable Gate Array (FPGA) (2024-2032) ($MN)
  • Table 5 Global AI Accelerator Market Outlook, By Application-Specific Integrated Circuit (ASIC) (2024-2032) ($MN)
  • Table 6 Global AI Accelerator Market Outlook, By Tensor Processing Unit (TPU) (2024-2032) ($MN)
  • Table 7 Global AI Accelerator Market Outlook, By Other Types (2024-2032) ($MN)
  • Table 8 Global AI Accelerator Market Outlook, By Technology (2024-2032) ($MN)
  • Table 9 Global AI Accelerator Market Outlook, By Cloud-Based AI Accelerators (2024-2032) ($MN)
  • Table 10 Global AI Accelerator Market Outlook, By Edge-Based AI Accelerators (2024-2032) ($MN)
  • Table 11 Global AI Accelerator Market Outlook, By On-Premise AI Accelerators (2024-2032) ($MN)
  • Table 12 Global AI Accelerator Market Outlook, By Application (2024-2032) ($MN)
  • Table 13 Global AI Accelerator Market Outlook, By Data Centers (2024-2032) ($MN)
  • Table 14 Global AI Accelerator Market Outlook, By Robotics (2024-2032) ($MN)
  • Table 15 Global AI Accelerator Market Outlook, By Cloud Computing (2024-2032) ($MN)
  • Table 16 Global AI Accelerator Market Outlook, By Autonomous Vehicles (2024-2032) ($MN)
  • Table 17 Global AI Accelerator Market Outlook, By Consumer Electronics (2024-2032) ($MN)
  • Table 18 Global AI Accelerator Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 19 Global AI Accelerator Market Outlook, By Other Applications (2024-2032) ($MN)
  • Table 20 Global AI Accelerator Market Outlook, By End User (2024-2032) ($MN)
  • Table 21 Global AI Accelerator Market Outlook, By IT & Telecom (2024-2032) ($MN)
  • Table 22 Global AI Accelerator Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 23 Global AI Accelerator Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 24 Global AI Accelerator Market Outlook, By Aerospace & Defense (2024-2032) ($MN)
  • Table 25 Global AI Accelerator Market Outlook, By Healthcare (2024-2032) ($MN)
  • Table 26 Global AI Accelerator Market Outlook, By Retail (2024-2032) ($MN)
  • Table 27 Global AI Accelerator 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.