查看購物車
  • Simplified Chinese
  • English
  • Japanese
  • Korean
封面
市場調查報告書
商品編碼
1721381

AI晶片市場 (～2035年):晶片類型·處理類型·技術·功能·用途·終端用戶·企業類型·各地區的產業趨勢與全球預測

AI Chip Market, Till 2035: Distribution by Type of Chip, Type of Processing, Type of Technology, Type of Function, Type of Application, Type of End-User, Type of Enterprise and Geographical Regions : Industry Trends and Global Forecasts
出版日期: | 出版商: Roots Analysis | 英文 192 Pages | 商品交期: 2-10個工作天內

價格
簡介目錄

預計到 2035 年，全球 AI 晶片市場規模將從目前的 316 億美元增長至 8,468 億美元，預測期內的複合年增長率為 34.84%。

AI Chip Market-IMG1

在持續的技術進步和投資者興趣的推動下，預計全球 AI 晶片市場在預測期內將保持健康成長。

AI晶片的市場機會:各市場區隔

晶片類別

  • ASIC
  • CPU
  • FPGA
  • GPU
  • 其他

處理類別

  • 雲端
  • 邊緣

技術

  • 多晶片模組
  • 系統級封裝
  • 系統晶片
  • 其他

各功能

  • 推論
  • 訓練

各用途

  • computer vision
  • 自然語言處理
  • 網路安全
  • 機器人技術
  • 其他

各終端用戶

  • 農業
  • 汽車
  • 政府機關
  • 醫療保健
  • 人力資源
  • 製造
  • 零售
  • 其他

類別企業

  • 大企業
  • 中小企業

各地區

  • 北美
  • 美國
  • 加拿大
  • 墨西哥
  • 其他的北美各國
  • 歐洲
  • 奧地利
  • 比利時
  • 丹麥
  • 法國
  • 德國
  • 愛爾蘭
  • 義大利
  • 荷蘭
  • 挪威
  • 俄羅斯
  • 西班牙
  • 瑞典
  • 瑞士
  • 英國
  • 其他歐洲各國
  • 亞洲
  • 中國
  • 印度
  • 日本
  • 新加坡
  • 韓國
  • 其他亞洲各國
  • 南美
  • 巴西
  • 智利
  • 哥倫比亞
  • 委內瑞拉
  • 其他的南美各國
  • 中東·北非
  • 埃及
  • 伊朗
  • 伊拉克
  • 以色列
  • 科威特
  • 沙烏地阿拉伯
  • UAE
  • 其他的中東·北非各國
  • 全球其他地區
  • 澳洲
  • 紐西蘭
  • 其他的國家

AI晶片市場：成長與趨勢

根據 "富比士" 報道，64%的企業認為AI將提高其營運效率。此外，預計到2030年，道路上每十輛汽車中就有一輛是自動駕駛汽車。在此背景下，AI晶片正透過提高效率和創新來推動AI和機器人技術的未來發展。

在網路和數位科技的快速發展推動下，AI在關鍵產業的應用正在穩步推進。事實上，ChatGPT 上線僅五天就吸引了超過 100 萬用戶，這表明人工智慧的接受度正在迅速提升。

人工智慧晶片市場正成為全球創新和數位轉型的關鍵因素，旨在提高人工智慧的技術效率。自然語言處理和機器學習的進步對於充分發揮其潛力至關重要，並在提高能源效率和響應速度方面發揮重要作用。此外，NVIDIA 最新的 GPU、英特爾的 Gaudi 處理器、邊緣 AI 等對於促進現代即時決策至關重要。最近，Cerebras Systems 於 2024 年 9 月發布了其最新的人工智慧晶片 Cerebras Inference，其速度是 NVIDIA GPU 的 20 倍，單晶片上整合了超過 4 兆個電晶體。

本報告提供全球AI晶片的市場調查、彙整市場概要，背景，市場影響因素的分析，市場規模的轉變·預測，各種區分·各地區的詳細分析，競爭情形，主要企業簡介等資訊。

目錄

第1章 序文

第2章 調查手法

第3章 市場動態

第4章 宏觀經濟指標

章節II:定性的洞察

第5章 摘要整理

第6章 簡介

第7章 法規情勢

章節III:市場概要

第8章 主要企業的總括的資料庫

第9章 競爭情形

第10章 閒置頻段分析

第11章 競爭分析

第12章 AI晶片市場上Start-Ups生態系統

章節IV: 企業簡介

第13章 企業簡介

  • 章概要
  • Alibaba Group
  • Amazon Web Services
  • Apple
  • Avaamo
  • Baidu
  • Google
  • Hewlett Packard
  • IBM
  • IPsoft
  • Meta
  • Microsoft
  • NVIDIA
  • Nuance Communications
  • Oracle
  • Salesforce
  • SAP SE
  • SoundHound

章節V:市場趨勢

第14章 大趨勢分析

第15章 未滿足需求的分析

第16章 專利分析

第17章 最近的趨勢

章節VI:市場機會分析

第18章 全球AI晶片市場

第19章 代理商各系統的市場機會

第20章 應用各領域的市場機會

第21章 按代理商所扮演的角色的市場機會

第22章 各技術的市場機會

第23章 各產品類型的市場機會

第24章 北美AI晶片的市場機會

第25章 歐洲的AI晶片的市場機會

第26章 亞洲的AI晶片的市場機會

第27章 中東·北非的AI晶片的市場機會

第28章 南美的AI晶片的市場機會

第29章 全球其他地區的AI晶片的市場機會

第30章 市場集中分析:各主要企業分佈

第31章 鄰近市場分析

章節VII:策略工具

第32章 主要成功策略

第33章 波特的五力分析

第34章 SWOT分析

第35章 價值鏈分析

第36章 ROOTS的策略性建議

章節VIII:其他的壟斷的洞察

第37章 來自1次調查的洞察

第38章 報告書的結論

章節IX:附錄

第39章 表格形式資料

第40章 企業·團體一覽

第41章 客制化的機會

第42章 ROOTS訂閱服務

第43章 著者詳細內容

簡介目錄
Product Code: RAICT300149

GLOBAL AI CHIP MARKET: OVERVIEW

As per Roots Analysis, the global AI chip market size is estimated to grow from USD 31.6 billion in the current year to USD 846.8 billion by 2035, at a CAGR of 34.84% during the forecast period, till 2035.

AI Chip Market - IMG1

Driven by the ongoing technological advancements and increasing interest from investors, the global AI chip market is expected to grow at a healthy pace during the forecast period.

The opportunity for AI chip market has been distributed across the following segments:

Type of Chip

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

Type of Processing

  • Cloud
  • Edge

Type of Technology

  • Multi-Chip Module
  • System in Package
  • System on Chip
  • Others

Type of Function

  • Inference
  • Training

Type of Application

  • Computer Vision
  • Nature Language Processing
  • Network Security
  • Robotics
  • Others

End-Users

  • Agriculture
  • Automotive
  • Government
  • Healthcare
  • Human Resources
  • Manufacturing
  • Retail
  • Others

Type of Enterprise

  • Large
  • Small and Medium Enterprise

Geographical Regions

  • North America
  • US
  • Canada
  • Mexico
  • Other North American countries
  • Europe
  • Austria
  • Belgium
  • Denmark
  • France
  • Germany
  • Ireland
  • Italy
  • Netherlands
  • Norway
  • Russia
  • Spain
  • Sweden
  • Switzerland
  • UK
  • Other European countries
  • Asia
  • China
  • India
  • Japan
  • Singapore
  • South Korea
  • Other Asian countries
  • Latin America
  • Brazil
  • Chile
  • Colombia
  • Venezuela
  • Other Latin American countries
  • Middle East and North Africa
  • Egypt
  • Iran
  • Iraq
  • Israel
  • Kuwait
  • Saudi Arabia
  • UAE
  • Other MENA countries
  • Rest of the World
  • Australia
  • New Zealand
  • Other countries

AI CHIP MARKET: GROWTH AND TRENDS

According to Forbes, 64% of companies believe that artificial intelligence (AI) will enhance their business productivity. Additionally, projections suggest that by 2030, one in ten vehicles on the road will be self-driving. In this context, AI chips are driving the future of AI and robotics through increased efficiency and innovation. These AI chips are specialized integrated circuits designed to execute complex algorithmic tasks related to AI. It is important to note that there are a variety of applications for AI chips across different sectors, including healthcare, finance, automotive, and telecommunications. Some of the key benefits of utilizing these chips include improved operational efficiency, rapid real-time responses, and the ability to process vast amounts of data quickly and effectively. Moreover, the AI chips provide a range of advanced capabilities such as natural language processing, image recognition, and predictive analytics. Notably, the adoption of AI in major sectors is rising, driven by the fast expansion of the internet and digital technologies. Interestingly, ChatGPT managed to attract over 1 million users within just five days, highlighting the growing acceptance of AI.

The AI chip market is becoming an important element in the worldwide transition towards innovation and digital transformation, aiming for greater technological efficiency in AI. Natural language processing and machine learning have been crucial in realizing its full potential, enhancing power efficiency and response speed. Further, cutting-edge GPUs from NVIDIA and Intel's Gaudi processors, along with edge AI, are pivotal in facilitating real-time decision-making in this modern landscape. Recently, in September 2024, Cerebras Systems introduced its latest AI chip, the Cerebras Inference, which claims to be 20 times faster than NVIDIA's GPUs and features over 4 trillion transistors on a single chip.

AI CHIP MARKET: KEY SEGMENTS

Market Share by Type of Chip

Based on the type of chip, the global AI chip market is segmented into application-specific integrated circuit (ASIC), central processing unit (CPU), field programmable gate array (FPGA), graphics processing unit (GPU) and others. According to our estimates, currently, central processing unit (CPU) segment captures the majority share of the market. This can be attributed to extensive usage and the significant installed base of CPUs in data centers and edge devices. However, application-specific integrated circuit (ASIC) segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Processing

Based on the type of processing, the AI chip market is segmented into cloud and edge. According to our estimates, currently, cloud segment captures the majority share of the market. This can be attributed to its capability to satisfy high-performance needs, offer scalability and flexibility, facilitate data centralization, and ensure cost efficiency. However, edge segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Technology

Based on the type of technology, the AI chip market is segmented into multi-chip module, system in packaging, system on chip and others. According to our estimates, currently, system on chip segment captures the majority share of the market; further, this segment is anticipated to grow at a higher CAGR in the future. This can be attributed to its capability to combine multiple components into a single chip, which is especially beneficial for AI applications.

Market Share by Type of Function

Based on the type of function, the AI chip market is segmented into inference and training. According to our estimates, currently, inference segment captures the majority share of the market; further, this segment is anticipated to grow at a higher CAGR in the future. This can be attributed to the rising use of AI to improve operations and enhance customer experience. Data centers are expanding their AI capabilities, which is increasing the demand for high-performance inference chips.

Market Share by Type of Application

Based on the type of application, the AI chip market is segmented into computer vision, natural language processing, network security, robotics and others. According to our estimates, currently, computer vision segment captures the majority share of the market further, this segment is anticipated to grow at a higher CAGR in the future. This can be attributed to its essential function in enhancing automation and efficiency across numerous industries. The growing dependence on AI-driven systems for applications like quality control, surveillance, and real-time data analysis has resulted in increased demand for specialized chips capable of processing complex visual data.

Market Share by End-users

Based on the end-users, the AI chip market is segmented into agriculture, automotive, government, healthcare, human resources, manufacturing, retail and others. According to our estimates, currently, healthcare segment captures the majority share of the market. This can be attributed to the rising demand for patient data management, medical imaging analysis, and diagnostic applications that utilize AI chip technology, enhancing efficiency and accuracy in healthcare delivery. However, automotive segment is anticipated to grow at a higher CAGR during the forecast period.

Market Share by Type of Enterprise

Based on the type of enterprise, the AI chip market is segmented into large and small and medium enterprises. According to our estimates, currently, large enterprise segment captures the majority share of the market. This can be attributed to their considerable financial resources, extensive research and development capabilities, established presence in the market, and commitment to business growth. However, small and medium enterprise segment is anticipated to grow at a higher CAGR during the forecast period

Market Share by Geographical Regions

Based on the geographical regions, the AI chip market is segmented into North America, Europe, Asia, Latin America, Middle East and North Africa, and Rest of the World. According to our estimates, currently, North America captures the majority share of the market. This can be attributed to the concentration of major technology firms, significant investments in artificial general intelligence research and development, along with a well-established infrastructure. However, market share in Asia is anticipated to grow at a higher CAGR during the forecast period.

Example Players in AI Chip Market

  • Advanced Micro Devices
  • Amazon
  • General Vision
  • Google
  • Gyrfalcon Technology
  • Huawei Technologies
  • IBM
  • Infineon Technologies
  • Intel
  • Kneron
  • Microsoft
  • MYTHIC
  • Nvidia
  • NXP Semiconductors
  • Qualcomm Incorporated
  • Samsung Electronics
  • Toshiba
  • Wave Computing

AI CHIP MARKET: RESEARCH COVERAGE

The report on the AI chip market features insights on various sections, including:

  • Market Sizing and Opportunity Analysis: An in-depth analysis of the AI chip market, focusing on key market segments, including [A] type of chip, [B] type of processing, [C] type of technology, [D] type of function, [E] type of application, [F] end-users, [G] type of enterprise and [H] geographical regions.
  • Competitive Landscape: A comprehensive analysis of the companies engaged in the AI chip market, based on several relevant parameters, such as [A] year of establishment, [B] company size, [C] location of headquarters, [D] ownership structure.
  • Company Profiles: Elaborate profiles of prominent players engaged in the AI chip market, providing details on [A] location of headquarters, [B]company size, [C] company mission, [D] company footprint, [E] management team, [F] contact details, [G] financial information, [H] operating business segments, [I] AI chip portfolio, [J] moat analysis, [K] recent developments, and an informed future outlook.
  • Megatrends: An evaluation of ongoing megatrends in AI chip industry.
  • Patent Analysis: An insightful analysis of patents filed / granted in the AI chip domain, based on relevant parameters, including [A] type of patent, [B] patent publication year, [C] patent age and [D] leading players.
  • Recent Developments: An overview of the recent developments made in the AI chip market, along with analysis based on relevant parameters, including [A] year of initiative, [B] type of initiative, [C] geographical distribution and [D] most active players.
  • Porter's Five Forces Analysis: An analysis of five competitive forces prevailing in the AI chip market, including threats of new entrants, bargaining power of buyers, bargaining power of suppliers, threats of substitute products and rivalry among existing competitors.
  • SWOT Analysis: An insightful SWOT framework, highlighting the strengths, weaknesses, opportunities and threats in the domain. Additionally, it provides Harvey ball analysis, highlighting the relative impact of each SWOT parameter.

KEY QUESTIONS ANSWERED IN THIS REPORT

  • How many companies are currently engaged in this market?
  • Which are the leading companies in this market?
  • What is the significance of edge AI in the AI chip market?
  • What factors are likely to influence the evolution of this market?
  • What is the current and future market size?
  • What is the CAGR of this market?
  • How is the current and future market opportunity likely to be distributed across key market segments?
  • Which type of AI chip is expected to dominate the market?

REASONS TO BUY THIS REPORT

  • The report provides a comprehensive market analysis, offering detailed revenue projections of the overall market and its specific sub-segments. This information is valuable to both established market leaders and emerging entrants.
  • Stakeholders can leverage the report to gain a deeper understanding of the competitive dynamics within the market. By analyzing the competitive landscape, businesses can make informed decisions to optimize their market positioning and develop effective go-to-market strategies.
  • The report offers stakeholders a comprehensive overview of the market, including key drivers, barriers, opportunities, and challenges. This information empowers stakeholders to stay abreast of market trends and make data-driven decisions to capitalize on growth prospects.

ADDITIONAL BENEFITS

  • Complimentary Excel Data Packs for all Analytical Modules in the Report
  • 10% Free Content Customization
  • Detailed Report Walkthrough Session with Research Team
  • Free Updated report if the report is 6-12 months old or older

TABLE OF CONTENTS

SECTION I: REPORT OVERVIEW

1. PREFACE

  • 1.1. Introduction
  • 1.2. Market Share Insights
  • 1.3. Key Market Insights
  • 1.4. Report Coverage
  • 1.5. Key Questions Answered
  • 1.6. Chapter Outlines

2. RESEARCH METHODOLOGY

  • 2.1. Chapter Overview
  • 2.2. Research Assumptions
  • 2.3. Database Building
    • 2.3.1. Data Collection
    • 2.3.2. Data Validation
    • 2.3.3. Data Analysis
  • 2.4. Project Methodology
    • 2.4.1. Secondary Research
      • 2.4.1.1. Annual Reports
      • 2.4.1.2. Academic Research Papers
      • 2.4.1.3. Company Websites
      • 2.4.1.4. Investor Presentations
      • 2.4.1.5. Regulatory Filings
      • 2.4.1.6. White Papers
      • 2.4.1.7. Industry Publications
      • 2.4.1.8. Conferences and Seminars
      • 2.4.1.9. Government Portals
      • 2.4.1.10. Media and Press Releases
      • 2.4.1.11. Newsletters
      • 2.4.1.12. Industry Databases
      • 2.4.1.13. Roots Proprietary Databases
      • 2.4.1.14. Paid Databases and Sources
      • 2.4.1.15. Social Media Portals
      • 2.4.1.16. Other Secondary Sources
    • 2.4.2. Primary Research
      • 2.4.2.1. Introduction
      • 2.4.2.2. Types
        • 2.4.2.2.1. Qualitative
        • 2.4.2.2.2. Quantitative
      • 2.4.2.3. Advantages
      • 2.4.2.4. Techniques
        • 2.4.2.4.1. Interviews
        • 2.4.2.4.2. Surveys
        • 2.4.2.4.3. Focus Groups
        • 2.4.2.4.4. Observational Research
        • 2.4.2.4.5. Social Media Interactions
      • 2.4.2.5. Stakeholders
        • 2.4.2.5.1. Company Executives (CXOs)
        • 2.4.2.5.2. Board of Directors
        • 2.4.2.5.3. Company Presidents and Vice Presidents
        • 2.4.2.5.4. Key Opinion Leaders
        • 2.4.2.5.5. Research and Development Heads
        • 2.4.2.5.6. Technical Experts
        • 2.4.2.5.7. Subject Matter Experts
        • 2.4.2.5.8. Scientists
        • 2.4.2.5.9. Doctors and Other Healthcare Providers
      • 2.4.2.6. Ethics and Integrity
        • 2.4.2.6.1. Research Ethics
        • 2.4.2.6.2. Data Integrity
    • 2.4.3. Analytical Tools and Databases

3. MARKET DYNAMICS

  • 3.1. Forecast Methodology
    • 3.1.1. Top-Down Approach
    • 3.1.2. Bottom-Up Approach
    • 3.1.3. Hybrid Approach
  • 3.2. Market Assessment Framework
    • 3.2.1. Total Addressable Market (TAM)
    • 3.2.2. Serviceable Addressable Market (SAM)
    • 3.2.3. Serviceable Obtainable Market (SOM)
    • 3.2.4. Currently Acquired Market (CAM)
  • 3.3. Forecasting Tools and Techniques
    • 3.3.1. Qualitative Forecasting
    • 3.3.2. Correlation
    • 3.3.3. Regression
    • 3.3.4. Time Series Analysis
    • 3.3.5. Extrapolation
    • 3.3.6. Convergence
    • 3.3.7. Forecast Error Analysis
    • 3.3.8. Data Visualization
    • 3.3.9. Scenario Planning
    • 3.3.10. Sensitivity Analysis
  • 3.4. Key Considerations
    • 3.4.1. Demographics
    • 3.4.2. Market Access
    • 3.4.3. Reimbursement Scenarios
    • 3.4.4. Industry Consolidation
  • 3.5. Robust Quality Control
  • 3.6. Key Market Segmentations
  • 3.7. Limitations

4. MACRO-ECONOMIC INDICATORS

  • 4.1. Chapter Overview
  • 4.2. Market Dynamics
    • 4.2.1. Time Period
      • 4.2.1.1. Historical Trends
      • 4.2.1.2. Current and Forecasted Estimates
    • 4.2.2. Currency Coverage
      • 4.2.2.1. Overview of Major Currencies Affecting the Market
      • 4.2.2.2. Impact of Currency Fluctuations on the Industry
    • 4.2.3. Foreign Exchange Impact
      • 4.2.3.1. Evaluation of Foreign Exchange Rates and Their Impact on Market
      • 4.2.3.2. Strategies for Mitigating Foreign Exchange Risk
    • 4.2.4. Recession
      • 4.2.4.1. Historical Analysis of Past Recessions and Lessons Learnt
      • 4.2.4.2. Assessment of Current Economic Conditions and Potential Impact on the Market
    • 4.2.5. Inflation
      • 4.2.5.1. Measurement and Analysis of Inflationary Pressures in the Economy
      • 4.2.5.2. Potential Impact of Inflation on the Market Evolution
    • 4.2.6. Interest Rates
      • 4.2.6.1. Overview of Interest Rates and Their Impact on the Market
      • 4.2.6.2. Strategies for Managing Interest Rate Risk
    • 4.2.7. Commodity Flow Analysis
      • 4.2.7.1. Type of Commodity
      • 4.2.7.2. Origins and Destinations
      • 4.2.7.3. Values and Weights
      • 4.2.7.4. Modes of Transportation
    • 4.2.8. Global Trade Dynamics
      • 4.2.8.1. Import Scenario
      • 4.2.8.2. Export Scenario
    • 4.2.9. War Impact Analysis
      • 4.2.9.1. Russian-Ukraine War
      • 4.2.9.2. Israel-Hamas War
    • 4.2.10. COVID Impact / Related Factors
      • 4.2.10.1. Global Economic Impact
      • 4.2.10.2. Industry-specific Impact
      • 4.2.10.3. Government Response and Stimulus Measures
      • 4.2.10.4. Future Outlook and Adaptation Strategies
    • 4.2.11. Other Indicators
      • 4.2.11.1. Fiscal Policy
      • 4.2.11.2. Consumer Spending
      • 4.2.11.3. Gross Domestic Product (GDP)
      • 4.2.11.4. Employment
      • 4.2.11.5. Taxes
      • 4.2.11.6. R&D Innovation
      • 4.2.11.7. Stock Market Performance
      • 4.2.11.8. Supply Chain
      • 4.2.11.9. Cross-Border Dynamics

SECTION II: QUALITATIVE INSIGHTS

5. EXECUTIVE SUMMARY

6. INTRODUCTION

  • 6.1. Chapter Overview
  • 6.2. Overview of AI chip Market
    • 6.2.1. Type of Agent System
    • 6.2.2. Areas of Application
    • 6.2.3. Type of Agent Role
    • 6.2.4. Type of Product
  • 6.3. Future Perspective

7. REGULATORY SCENARIO

SECTION III: MARKET OVERVIEW

8. COMPREHENSIVE DATABASE OF LEADING PLAYERS

9. COMPETITIVE LANDSCAPE

  • 9.1. Chapter Overview
  • 9.2. AI chip: Overall Market Landscape
    • 9.2.1. Analysis by Year of Establishment
    • 9.2.2. Analysis by Company Size
    • 9.2.3. Analysis by Location of Headquarters
    • 9.2.4. Analysis by Ownership Structure

10. WHITE SPACE ANALYSIS

11. COMPETITIVE COMPETITIVENESS ANALYSIS

12. STARTUP ECOSYSTEM IN THE AI CHIP MARKET

  • 12.1. AI chip Market: Market Landscape of Startups
    • 12.1.1. Analysis by Year of Establishment
    • 12.1.2. Analysis by Company Size
    • 12.1.3. Analysis by Company Size and Year of Establishment
    • 12.1.4. Analysis by Location of Headquarters
    • 12.1.5. Analysis by Company Size and Location of Headquarters
    • 12.1.6. Analysis by Ownership Structure
  • 12.2. Key Findings

SECTION IV: COMPANY PROFILES

13. COMPANY PROFILES

  • 13.1. Chapter Overview
  • 13.2. Alibaba Group
    • 13.2.1. Company Overview
    • 13.2.2. Company Mission
    • 13.2.3. Company Footprint
    • 13.2.4. Management Team
    • 13.2.5. Contact Details
    • 13.2.6. Financial Performance
    • 13.2.7. Operating Business Segments
    • 13.2.8. Service / Product Portfolio (project specific)
    • 13.2.9. MOAT Analysis
    • 13.2.10. Recent Developments and Future Outlook
  • 13.3. Amazon Web Services
  • 13.4. Apple
  • 13.5. Avaamo
  • 13.6. Baidu
  • 13.7. Google
  • 13.8. Hewlett Packard
  • 13.9. IBM
  • 13.10. IPsoft
  • 13.11. Meta
  • 13.12. Microsoft
  • 13.13. NVIDIA
  • 13.14. Nuance Communications
  • 13.15. Oracle
  • 13.16. Salesforce
  • 13.17. SAP SE
  • 13.18. SoundHound

SECTION V: MARKET TRENDS

14. MEGA TRENDS ANALYSIS

15. UNMEET NEED ANALYSIS

16. PATENT ANALYSIS

17. RECENT DEVELOPMENTS

  • 17.1. Chapter Overview
  • 17.2. Recent Funding
  • 17.3. Recent Partnerships
  • 17.4. Other Recent Initiatives

SECTION VI: MARKET OPPORTUNITY ANALYSIS

18. GLOBAL AI CHIP MARKET

  • 18.1. Chapter Overview
  • 18.2. Key Assumptions and Methodology
  • 18.3. Trends Disruption Impacting Market
  • 18.4. Demand Side Trends
  • 18.5. Supply Side Trends
  • 18.6. Global AI chip Market, Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 18.7. Multivariate Scenario Analysis
    • 18.7.1. Conservative Scenario
    • 18.7.2. Optimistic Scenario
  • 18.8. Investment Feasibility Index
  • 18.9. Key Market Segmentations

19. MARKET OPPORTUNITIES BASED ON TYPE OF AGENT SYSTEM

  • 19.1. Chapter Overview
  • 19.2. Key Assumptions and Methodology
  • 19.3. Revenue Shift Analysis
  • 19.4. Market Movement Analysis
  • 19.5. Penetration-Growth (P-G) Matrix
  • 19.6. AI chip Market for Multi-agent: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.7. AI chip Market for Single agent: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 19.8. Data Triangulation and Validation
    • 19.8.1. Secondary Sources
    • 19.8.2. Primary Sources
    • 19.8.3. Statistical Modeling

20. MARKET OPPORTUNITIES BASED ON AREAS OF APPLICATION

  • 20.1. Chapter Overview
  • 20.2. Key Assumptions and Methodology
  • 20.3. Revenue Shift Analysis
  • 20.4. Market Movement Analysis
  • 20.5. Penetration-Growth (P-G) Matrix
  • 20.6. AI chip Market for Customer Service & Virtual Assistants: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.7. AI chip Market for Healthcare: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 20.8. Data Triangulation and Validation
    • 20.8.1. Secondary Sources
    • 20.8.2. Primary Sources
    • 20.8.3. Statistical Modeling

21. MARKET OPPORTUNITIES BASED ON TYPES OF AGENT ROLE

  • 21.1. Chapter Overview
  • 21.2. Key Assumptions and Methodology
  • 21.3. Revenue Shift Analysis
  • 21.4. Market Movement Analysis
  • 21.5. Penetration-Growth (P-G) Matrix
  • 21.6. AI chip Market for Code Generation: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.7. AI chip Market for Customer Service: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.8. AI chip Market for Marketing: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.9. AI chip Market for Productivity & Personal Assistants: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.10. AI chip Market for Sales: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 21.11. Data Triangulation and Validation
    • 21.11.1. Secondary Sources
    • 21.11.2. Primary Sources
    • 21.11.3. Statistical Modeling

22. MARKET OPPORTUNITIES BASED ON TYPE OF TECHNOLOGY

  • 22.1. Chapter Overview
  • 22.2. Key Assumptions and Methodology
  • 22.3. Revenue Shift Analysis
  • 22.4. Market Movement Analysis
  • 22.5. Penetration-Growth (P-G) Matrix
  • 22.6. AI chip Market for Deep Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.7. AI chip Market for Machine Learning: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 22.8. Data Triangulation and Validation
    • 22.8.1. Secondary Sources
    • 22.8.2. Primary Sources
    • 22.8.3. Statistical Modeling

23. MARKET OPPORTUNITIES BASED ON TYPE OF PRODUCT

  • 23.1. Chapter Overview
  • 23.2. Key Assumptions and Methodology
  • 23.3. Revenue Shift Analysis
  • 23.4. Market Movement Analysis
  • 23.5. Penetration-Growth (P-G) Matrix
  • 23.6. AI chip Market for Build Your Own Agents: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.7. AI chip Market for Ready to Deploy Agents: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 23.8. Data Triangulation and Validation
    • 23.8.1. Secondary Sources
    • 23.8.2. Primary Sources
    • 23.8.3. Statistical Modeling

24. MARKET OPPORTUNITIES FOR AI CHIP IN NORTH AMERICA

  • 24.1. Chapter Overview
  • 24.2. Key Assumptions and Methodology
  • 24.3. Revenue Shift Analysis
  • 24.4. Market Movement Analysis
  • 24.5. Penetration-Growth (P-G) Matrix
  • 24.6. AI chip Market in North America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.1. AI chip Market in the US: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.2. AI chip Market in Canada: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.3. AI chip Market in Mexico: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 24.6.4. AI chip Market in Other North American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 24.7. Data Triangulation and Validation

25. MARKET OPPORTUNITIES FOR AI CHIP IN EUROPE

  • 25.1. Chapter Overview
  • 25.2. Key Assumptions and Methodology
  • 25.3. Revenue Shift Analysis
  • 25.4. Market Movement Analysis
  • 25.5. Penetration-Growth (P-G) Matrix
  • 25.6. AI chip Market in Europe: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.1. AI chip Market in Austria: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.2. AI chip Market in Belgium: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.3. AI chip Market in Denmark: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.4. AI chip Market in France: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.5. AI chip Market in Germany: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.6. AI chip Market in Ireland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.7. AI chip Market in Italy: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.8. AI chip Market in Netherlands: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.9. AI chip Market in Norway: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.10. AI chip Market in Russia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.11. AI chip Market in Spain: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.12. AI chip Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.13. AI chip Market in Sweden: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.14. AI chip Market in Switzerland: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.15. AI chip Market in the UK: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 25.6.16. AI chip Market in Other European Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 25.7. Data Triangulation and Validation

26. MARKET OPPORTUNITIES FOR AI CHIP IN ASIA

  • 26.1. Chapter Overview
  • 26.2. Key Assumptions and Methodology
  • 26.3. Revenue Shift Analysis
  • 26.4. Market Movement Analysis
  • 26.5. Penetration-Growth (P-G) Matrix
  • 26.6. AI chip Market in Asia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.1. AI chip Market in China: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.2. AI chip Market in India: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.3. AI chip Market in Japan: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.4. AI chip Market in Singapore: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.5. AI chip Market in South Korea: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 26.6.6. AI chip Market in Other Asian Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 26.7. Data Triangulation and Validation

27. MARKET OPPORTUNITIES FOR AI CHIP IN MIDDLE EAST AND NORTH AFRICA (MENA)

  • 27.1. Chapter Overview
  • 27.2. Key Assumptions and Methodology
  • 27.3. Revenue Shift Analysis
  • 27.4. Market Movement Analysis
  • 27.5. Penetration-Growth (P-G) Matrix
  • 27.6. AI chip Market in Middle East and North Africa (MENA): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.1. AI chip Market in Egypt: Historical Trends (Since 2019) and Forecasted Estimates (Till 205)
    • 27.6.2. AI chip Market in Iran: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.3. AI chip Market in Iraq: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.4. AI chip Market in Israel: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.5. AI chip Market in Kuwait: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.6. AI chip Market in Saudi Arabia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.7. AI chip Market in United Arab Emirates (UAE): Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 27.6.8. AI chip Market in Other MENA Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 27.7. Data Triangulation and Validation

28. MARKET OPPORTUNITIES FOR AI CHIP IN LATIN AMERICA

  • 28.1. Chapter Overview
  • 28.2. Key Assumptions and Methodology
  • 28.3. Revenue Shift Analysis
  • 28.4. Market Movement Analysis
  • 28.5. Penetration-Growth (P-G) Matrix
  • 28.6. AI chip Market in Latin America: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.1. AI chip Market in Argentina: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.2. AI chip Market in Brazil: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.3. AI chip Market in Chile: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.4. AI chip Market in Colombia Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.5. AI chip Market in Venezuela: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 28.6.6. AI chip Market in Other Latin American Countries: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
  • 28.7. Data Triangulation and Validation

29. MARKET OPPORTUNITIES FOR AI CHIP IN REST OF THE WORLD

  • 29.1. Chapter Overview
  • 29.2. Key Assumptions and Methodology
  • 29.3. Revenue Shift Analysis
  • 29.4. Market Movement Analysis
  • 29.5. Penetration-Growth (P-G) Matrix
  • 29.6. AI chip Market in Rest of the World: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.1. AI chip Market in Australia: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.2. AI chip Market in New Zealand: Historical Trends (Since 2019) and Forecasted Estimates (Till 2035)
    • 29.6.3. AI chip Market in Other Countries
  • 29.7. Data Triangulation and Validation

30. MARKET CONCENTRATION ANALYSIS: DISTRIBUTION BY LEADING PLAYERS

  • 30.1. Leading Player 1
  • 30.2. Leading Player 2
  • 30.3. Leading Player 3
  • 30.4. Leading Player 4
  • 30.5. Leading Player 5
  • 30.6. Leading Player 6
  • 30.7. Leading Player 7
  • 30.8. Leading Player 8

31. ADJACENT MARKET ANALYSIS

SECTION VII: STRATEGIC TOOLS

32. KEY WINNING STRATEGIES

33. PORTER FIVE FORCES ANALYSIS

34. SWOT ANALYSIS

35. VALUE CHAIN ANALYSIS

36. ROOTS STRATEGIC RECOMMENDATIONS

  • 36.1. Chapter Overview
  • 36.2. Key Business-related Strategies
    • 36.2.1. Research & Development
    • 36.2.2. Product Manufacturing
    • 36.2.3. Commercialization / Go-to-Market
    • 36.2.4. Sales and Marketing
  • 36.3. Key Operations-related Strategies
    • 36.3.1. Risk Management
    • 36.3.2. Workforce
    • 36.3.3. Finance
    • 36.3.4. Others

SECTION VIII: OTHER EXCLUSIVE INSIGHTS

37. INSIGHTS FROM PRIMARY RESEARCH

38. REPORT CONCLUSION

SECTION IX: APPENDIX

39. TABULATED DATA

40. LIST OF COMPANIES AND ORGANIZATIONS

41. CUSTOMIZATION OPPORTUNITIES

42. ROOTS SUBSCRIPTION SERVICES

43. AUTHOR DETAILS