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市場調查報告書

商品編碼

1995842

人工智慧晶片組市場：策略性洞察與預測（2026-2031 年）

AI Chipsets Market - Strategic Insights and Forecasts (2026-2031)

出版日期: 2026年02月25日 | 出版商:

Knowledge Sourcing Intelligence | 英文 149 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

全球人工智慧晶片組市場預計將從 2026 年的 864 億美元成長到 2031 年的 2,804 億美元，複合年成長率為 26.5%。

全球人工智慧晶片組市場是支撐數位經濟的關鍵基石。它為雲端運算、邊緣處理、自動化和連網型設備等領域人工智慧的普及提供了支撐。該市場策略性地佔據了半導體創新與大規模資料處理需求交會的有利位置。汽車、醫療、製造和家用電子電器等產業對人工智慧的日益普及，正在加速對能夠處理複雜運算工作負載的專用處理器的需求。企業優先考慮效能效率、可擴展性和即時分析，從而推動了對先進晶片結構和高效能運算基礎設施的持續投資。生成式人工智慧、機器學習應用和自主系統的普及，進一步強化了對人工智慧最佳化硬體平台的長期需求。

市場促進因素

人工智慧在各個領域的應用不斷擴展，仍然是推動成長要素。企業正將人工智慧融入營運，以提升自動化、預測分析和決策能力。這促使市場對能夠高效管理大規模資料集和神經網路工作負載的高效能處理器提出了更高的需求。消費性電子產品製造商正將人工智慧功能整合到智慧型手機、穿戴式裝置和智慧家居系統中，推動了對緊湊型、節能型晶片組的需求。

汽車產業也是一股重要的驅動力。自動駕駛系統和進階駕駛輔助技術需要強大的運算能力，這推動了專用人工智慧硬體的普及。醫療領域也正在成為一股強勁的需求來源，尤其是在依賴即時資料處理的醫學影像、診斷和藥物研發應用領域。

雲端基礎設施和超大規模資料中心的擴張正在加速人工智慧訓練和推理硬體的普及。企業正大力投資人工智慧驅動的數位轉型，這進一步推動了市場成長。

市場限制因素

儘管成長勢頭強勁，但一些結構性挑戰限制市場擴張。開發人工智慧晶片組需要大量的資本投入和專業的工程技術。高昂的研發成本和製造成本構成了進入壁壘，使得只有財力雄厚的半導體公司才能涉足這一領域。

設計複雜性是另一個阻礙因素。人工智慧晶片組需要先進的製造流程和複雜的架構，這增加了製造難度和生產前置作業時間。人工智慧系統相關的資料隱私和安全問題也造成了監管方面的不確定性。此外，全球半導體技術人才短缺也影響了創新週期，減緩了產品開發速度。

對技術和細分市場的洞察

市場區隔將組件分為GPU、FPGA、ASIC和其他專用處理器。 GPU憑藉其高效處理平行工作負載的能力，持續佔據市場主導地位。隨著企業對特定應用效能最佳化的需求日益成長，ASIC和專用AI加速器也越來越受到關注。

按最終用戶分類，主要細分市場包括家用電子電器、汽車、工業應用、醫療保健和企業計算。由於人工智慧功能已廣泛整合到日常設備中，家用電子電器仍然是一個主要細分市場。在機器人、預測性維護和智慧移動系統的推動下，汽車和工業自動化正在成為高成長細分市場。

處理工作負載大致可分為訓練和推理。訓練應用需要在資料中心進行高運算能力的運算，而推理工作負載則在互聯設備之間的邊緣迅速擴展。

競爭格局與策略展望

競爭格局的特點是快速創新和強大的垂直整合策略。領先的半導體公司正在擴展產品系列，以支援資料中心和邊緣運算環境。為了加快產品開發週期，晶片設計公司、晶圓代工廠和技術供應商之間的合作日益普遍。

產業相關人員正投資於先進的儲存技術、節能架構和專用加速器，以提升效能和可擴展性。在這個資本密集產業中，策略合作和持續的產品創新對於保持競爭優勢至關重要。

重點

隨著人工智慧與數位基礎設施和互聯系統整體融合，人工智慧晶片組市場預計將持續成長。儘管成本和複雜性仍然是結構性挑戰，但技術進步和行業內的廣泛應用將繼續推動長期成長。

本報告的主要益處

深入分析：獲得跨地區、客戶群、政策、社會經濟因素、消費者偏好和產業領域的詳細市場洞察。
競爭格局：了解主要企業的策略趨勢，並確定最佳的市場進入方式。
市場促進因素和未來趨勢：我們將評估影響市場的主要成長要素和新興趨勢。
實用建議：我們支援制定策略決策以開發新的收入來源。
適合各類讀者：非常適合Start-Ups、研究機構、顧問公司、中小企業和大型企業。

我們的報告的使用範例

產業和市場洞察、機會評估、產品需求預測、打入市場策略、區域擴張、資本投資決策、監管分析、新產品開發和競爭情報。

報告範圍

2021年至2025年的歷史數據和2026年至2031年的預測數據
成長機會、挑戰、供應鏈前景、法律規範與趨勢分析
競爭定位、策略和市場佔有率評估
細分市場和區域銷售成長及預測評估
公司簡介，包括策略、產品、財務狀況和主要發展動態。

北美洲
- 按組件
- 最終用戶
- 國家
  - 美國
  - 加拿大
  - 其他
南美洲
- 按組件
- 最終用戶
- 國家
  - 巴西
  - 阿根廷
  - 其他
歐洲
- 按組件
- 最終用戶
- 國家
  - 英國
  - 德國
  - 法國
  - 義大利
  - 西班牙
  - 其他
中東和非洲
- 按組件
- 最終用戶
- 國家
  - 沙烏地阿拉伯
  - UAE
  - 其他
亞太地區
- 按組件
- 最終用戶
- 國家
  - 中國
  - 日本
  - 印度
  - 韓國
  - 台灣
  - 澳洲
  - 其他

第8章：競爭環境與分析

主要企業及策略分析
市佔率分析
合併、收購、協議和合作關係
競爭環境儀錶板

第9章：公司簡介

AMD Inc
Graphcore Ltd
Huawei Technologies Co Ltd
IBM Corporation
Intel Corporation
NVIDIA Corporation
Micron Technology Inc
Samsung Semiconductor
Synopsys, Inc.
Qualcomm Technologies, Inc.
MediaTek Inc.
Cerebras

簡介目錄

Product Code: KSI061614975

The Global AI Chipsets market is forecast to grow at a CAGR of 26.5%, reaching USD 280.4 billion in 2031 from USD 86.4 billion in 2026.

The global AI chipsets market represents a critical enabling layer for the digital economy. It underpins the expansion of artificial intelligence across cloud computing, edge processing, automation, and connected devices. The market is strategically positioned at the intersection of semiconductor innovation and large scale data processing requirements. Increasing adoption of AI across industries such as automotive, healthcare, manufacturing, and consumer electronics is accelerating demand for specialized processors capable of handling complex computational workloads. Organizations are prioritizing performance efficiency, scalability, and real time analytics, which is driving continuous investment in advanced chip architectures and high performance computing infrastructure. The proliferation of generative AI, machine learning applications, and autonomous systems is further strengthening long term demand for AI optimized hardware platforms.

Market Drivers

The expansion of AI applications across multiple sectors remains the primary growth driver. Businesses are integrating AI into operations to improve automation, predictive analytics, and decision making capabilities. This is increasing the need for high performance processors that can efficiently manage large datasets and neural network workloads. Consumer electronics manufacturers are embedding AI capabilities into smartphones, wearable devices, and smart home systems, which is boosting demand for compact and energy efficient chipsets.

The automotive industry is another key driver. Autonomous driving systems and advanced driver assistance technologies require significant computational power, increasing adoption of specialized AI hardware. Healthcare is also emerging as a strong demand center, particularly for medical imaging, diagnostics, and drug discovery applications that rely on real time data processing.

The expansion of cloud infrastructure and hyperscale data centers is accelerating deployment of AI training and inference hardware. Enterprises are investing heavily in AI enabled digital transformation, further supporting market growth.

Market Restraints

Despite strong growth momentum, several structural challenges constrain market expansion. Development of AI chipsets requires significant capital investment and specialized engineering expertise. High research and fabrication costs increase barriers to entry and limit participation to well funded semiconductor firms.

Design complexity is another constraint. AI chipsets require advanced fabrication processes and sophisticated architectures, which increase manufacturing difficulty and production timelines. Data privacy and security concerns related to AI systems also create regulatory uncertainty. In addition, the global shortage of skilled semiconductor professionals affects innovation cycles and slows product development.

Technology and Segment Insights

The market is segmented by component into GPU, FPGA, ASIC, and other specialized processors. GPUs continue to dominate due to their ability to process parallel workloads efficiently. ASICs and dedicated AI accelerators are gaining traction as organizations seek application specific performance optimization.

By end user, major segments include consumer electronics, automotive, industrial applications, healthcare, and enterprise computing. Consumer electronics remain a leading segment due to widespread integration of AI functionality in everyday devices. Automotive and industrial automation are emerging as high growth segments driven by robotics, predictive maintenance, and intelligent mobility systems.

Processing workloads are broadly divided into training and inference. Training applications require high computational capacity in data centers, while inference workloads are expanding rapidly at the edge across connected devices.

Competitive and Strategic Outlook

The competitive landscape is characterized by rapid innovation and strong vertical integration strategies. Leading semiconductor companies are expanding product portfolios to support both data center and edge computing environments. Partnerships between chip designers, foundries, and technology providers are becoming increasingly common to accelerate product development cycles.

Industry participants are investing in advanced memory technologies, power efficient architectures, and specialized accelerators to improve performance and scalability. Strategic collaborations and continuous product innovation are central to maintaining competitive advantage in this highly capital intensive industry.

Key Takeaways

The AI chipsets market is positioned for sustained expansion as artificial intelligence becomes embedded across digital infrastructure and connected systems. While cost and complexity remain structural challenges, technological advancement and broad industry adoption will continue to drive long term growth.

Key Benefits of this Report

Insightful Analysis: Gain detailed market insights across regions, customer segments, policies, socio-economic factors, consumer preferences, and industry verticals.
Competitive Landscape: Understand strategic moves by key players to identify optimal market entry approaches.
Market Drivers and Future Trends: Assess major growth forces and emerging developments shaping the market.
Actionable Recommendations: Support strategic decisions to unlock new revenue streams.
Caters to a Wide Audience: Suitable for startups, research institutions, consultants, SMEs, and large enterprises.

What businesses use our reports for

Industry and market insights, opportunity assessment, product demand forecasting, market entry strategy, geographical expansion, capital investment decisions, regulatory analysis, new product development, and competitive intelligence.

Report Coverage

Historical data from 2021 to 2025 and forecast data from 2026 to 2031
Growth opportunities, challenges, supply chain outlook, regulatory framework, and trend analysis
Competitive positioning, strategies, and market share evaluation
Revenue growth and forecast assessment across segments and regions
Company profiling including strategies, products, financials, and key developments

1. INTRODUCTION

1.1. Market Overview
1.2. Market Definition
1.3. Scope of the Study
1.4. Market Segmentation
1.5. Currency
1.6. Assumptions
1.7. Base and Forecast Years Timeline
1.8. Key Benefits for the Stakeholders

2. RESEARCH METHODOLOGY

2.1. Research Design
2.2. Research Process

3. EXECUTIVE SUMMARY

3.1. Key Findings

4. MARKET DYNAMICS

4.1. Market Drivers
4.2. Market Restraints
4.3. Porter's Five Forces Analysis
- 4.3.1. Bargaining Power of Suppliers
- 4.3.2. Bargaining Power of Buyers
- 4.3.3. The Threat of New Entrants
- 4.3.4. Threat of Substitutes
- 4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
4.5. Analyst View

5. AI CHIPSETS MARKET BY COMPONENT

5.1. Introduction
5.2. GPU (Graphic Processing Unit)
5.3. FGPA (Field-Programmable Gate Array)
5.4. ASIC (Application-Specific Integrated Circuit)
5.5. Others

6. AI CHIPSETS MARKET BY END-USER

6.1. Introduction
6.2. Automotives
6.3. Consumer Electronics
6.4. Industrial
6.5. Healthcare
6.6. Others

7. AI CHIPSETS MARKET BY GEOGRAPHY

7.1. Introduction
7.2. North America
- 7.2.1. By Component
- 7.2.2. By End-User
- 7.2.3. By Country
  - 7.2.3.1. United States
  - 7.2.3.2. Canada
  - 7.2.3.3. Others
7.3. South America
- 7.3.1. By Component
- 7.3.2. By End-User
- 7.3.3. By Country
  - 7.3.3.1. Brazil
  - 7.3.3.2. Argentina
  - 7.3.3.3. Others
7.4. Europe
- 7.4.1. By Component
- 7.4.2. By End-User
- 7.4.3. By Country
  - 7.4.3.1. United Kingdom
  - 7.4.3.2. Germany
  - 7.4.3.3. France
  - 7.4.3.4. Italy
  - 7.4.3.5. Spain
  - 7.4.3.6. Others
7.5. Middle East and Africa
- 7.5.1. By Component
- 7.5.2. By End-User
- 7.5.3. By Country
  - 7.5.3.1. Saudi Arabia
  - 7.5.3.2. UAE
  - 7.5.3.3. Others
7.6. Asia Pacific
- 7.6.1. By Component
- 7.6.2. By End-User
- 7.6.3. By Country
  - 7.6.3.1. China
  - 7.6.3.2. Japan
  - 7.6.3.3. India
  - 7.6.3.4. South Korea
  - 7.6.3.5. Taiwan
  - 7.6.3.6. Australia
  - 7.6.3.7. Others