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市場調查報告書
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1946022

全球資料中心人工智慧最佳化網路基礎設施市場：預測（至2034年）－按產品、網路、部署方式、資料中心類別、人工智慧應用、最終使用者和地區進行分析

AI-Optimized Network Infrastructure for Data Centers Market Forecasts to 2034 - Global Analysis By Offering (Hardware, Software and Services), Network, Deployment Model, Data Center Category, AI Usage, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3個工作天內

價格

根據 Stratistics MRC 的研究，全球資料中心 AI 最佳化網路基礎設施市場預計將在 2026 年達到 280.8 億美元，在預測期內以 14.3% 的複合年成長率成長，到 2034 年達到 818.2 億美元。

以資料中心為導向的AI最佳化網路基礎設施是指利用人工智慧（AI）提升效能、效率和可靠性的先進網路系統。透過整合AI驅動的分析、自動化和預測功能，​​這些基礎設施能夠動態管理資料流量、最佳化資源分配並降低伺服器、儲存和網路設備之間的延遲。它們支援即時監控、異常檢測和自癒功能，從而確保高可用性和能源效率。此類網路支援可擴展的工作負載，包括AI、機器學習和巨量資料應用，同時最大限度地降低運維複雜性。

即時分析處理的需求日益成長

企業在決策過程中越來越依賴人工智慧驅動的洞察，這需要低延遲、高頻寬的網路基礎設施。人工智慧最佳化的系統能夠實現更快的資料傳輸、預測性路由和動態工作負載平衡。供應商正在整合智慧編配工具來處理複雜的流量模式。銀行、金融和保險 (BFSI)、醫療保健和電信等行業主導這一趨勢，因為關鍵業務營運依賴於即時分析。對即時洞察日益成長的需求，正鞏固人工智慧最佳化網路作為現代資料中心基石的地位。

熟練的人工智慧網路工程師短缺

實施和維護人工智慧驅動的網路系統需要機器學習、自動化和網路安全的專業知識。中小企業在招募和留住人才方面面臨重重困難，而大型企業則面臨日益成長的專業技能成本。儘管培訓項目和認證正在不斷湧現，但人才短缺問題依然嚴峻。供應商正透過自動化和使用者友善介面簡化平台，但熟練專業人員的匱乏限制了系統的可擴展性，並持續延緩部署進度。

人工智慧驅動型網路解決方案的協作

協作努力正在推動將人工智慧演算法與先進網路硬體融合的解決方案的實現。供應商正在加強與雲端服務供應商、通訊業者和系統整合商的合作，以擴大市場佔有率。這些夥伴關係加速了創新，並降低了終端用戶的部署複雜性。各產業正在利用聯合解決方案，使其基礎設施與數位轉型目標保持一致。策略合作正在擴大市場覆蓋範圍，並將夥伴關係關係定位為成長的關鍵催化劑。

網路安全和資料外洩風險日益增加

隨著網路變得更加智慧和互聯，攻擊面也不斷擴大。資料外洩可能危及高度敏感的分析數據，並擾亂關鍵業務運作。為了降低風險，供應商正在投資加密、零信任框架和人工智慧驅動的威脅偵測技術。不斷演變的資料保護條例也增加了複雜性。對資料外洩和隱私的持續擔憂可能會阻礙企業採用這些技術，如果無法有效解決，還可能延緩技術的普及。

新冠疫情的感染疾病：

新冠疫情重塑了網路基礎設施的優先事項，凸顯了網路韌性和自動化的重要性。遠距辦公和線上活動的激增給資料中心帶來了前所未有的壓力，迫使營運商最佳化流量。支援預測路由和自適應頻寬分配的人工智慧驅動型網路解決方案因此備受關注。儘管一些計劃最初因預算限制而延期，但對即時分析的需求迅速推動了投資。供應商也看到了對可遠端管理、自動化平台日益成長的需求。

在預測期內，資料中心架構（脊葉式）細分市場預計將佔據最大的市場佔有率。

在預測期內，資料中心架構（脊葉式）細分市場預計將佔據最大的市場佔有率，這主要得益於超大規模資料中心對可擴展、低延遲架構的日益普及。脊葉式架構具有可預測的延遲和高吞吐量，因此非常適合人工智慧驅動的工作負載。營運商正依靠這種架構設計來簡化流量管理並實現高效的基礎設施擴展。供應商正在透過自動化和智慧監控來增強架構解決方案。超大規模資料中心和雲端服務供應商正在推動對高階架構部署的需求。該細分市場的主導地位反映了其為現代資料中心提供容錯和擴充性連接的能力。

預計在預測期內，網路自動化和最佳化領域將呈現最高的複合年成長率。

在預測期內，受智慧流量管理和預測路由需求不斷成長的推動，網路自動化和最佳化領域預計將呈現最高的成長率。企業正在採用自動化框架來減少人工干預並提高效率。人工智慧驅動的最佳化工具能夠實現預測路由、異常偵測和動態頻寬分配。供應商正在將機器學習整合到其平台中，以增強可擴展性。在電信和銀行、金融和保險 (BFSI) 等流量模式複雜的行業中，這些技術的應用正在迅速擴展。該領域的成長凸顯了其在實現自適應和智慧網路營運方面的重要作用。

市佔率最大的地區：

在整個預測期內，北美預計將保持最大的市場佔有率，這得益於其強大的超大規模資料中心網路和對人工智慧驅動型網路的早期應用。在成熟的資料中心生態系統和對人工智慧最佳化基礎設施的大力投資的支持下，北美預計將佔據最大的市場佔有率。美國在超大規模擴張、雲端原生應用程式和人工智慧驅動型工作負載方面處於主導地位。加拿大則透過專注於合規性和政府主導的數位化項目來補充其成長。主要技術提供商的存在鞏固了該地區的領先地位。對永續性和監管合規性日益成長的需求正在推動跨行業的應用。

複合年成長率最高的地區：

在預測期內，亞太地區預計將呈現最高的複合年成長率，這主要得益於快速的數位化和超大規模/邊緣運算設施的積極擴張。亞太地區預計將實現最高的複合年成長率，這主要得益於對容錯網路基礎設施的大規模投資。中國正在推動採用人工智慧賦能架構的超大規模設施的擴張，而印度則透過數位化專案和金融科技的擴張來推動成長。日本和韓國正在加速採用智慧網路平台，並專注於自動化和企業彈性。電信、銀行、金融和保險（BFSI）以及醫療產業正在推動全部區域的需求。除了這些促進因素外，亞太地區還受益於政府對本地網路設備製造的激勵措施以及對5G部署的大力區域投資，這些措施正在提高網路可近性並加速人工智慧最佳化網路解決方案的採用。

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訂閱本報告的用戶可享有以下免費自訂選項之一：

  • 公司簡介
    • 對其他公司（最多 3 家公司）進行全面分析
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  • 區域分類
    • 根據客戶興趣量身定做的主要國家/地區的市場估算、預測和複合年成長率（註：基於可行性檢查）
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    • 根據產品系列、地理覆蓋範圍和策略聯盟對主要企業進行基準分析。

目錄

第1章：執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
  • 分析材料

第3章 市場趨勢分析

  • 促進因素
  • 抑制因子
  • 機會
  • 威脅
  • 最終用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章：波特五力分析

  • 供應商議價能力
  • 買方的議價能力
  • 替代產品的威脅
  • 新進入者的威脅
  • 競爭公司之間的競爭

第5章：全球面向資料中心的AI最佳化網路基礎設施市場：按產品/服務分類

  • 硬體
    • AI最佳化型網路交換機
    • 高速路由器和互連設備
    • SmartNIC／DPU
  • 軟體
    • 人工智慧驅動的網路控制與編配
    • 交通最佳化與分析
  • 服務
    • 實施與整合
    • 託管服務和支援服務

第6章：全球面向資料中心的AI最佳化網路基礎設施市場結構：按網路架構分類

  • 軟體定義網路 (SDN)
  • 資料中心架構（脊葉式架構）
  • 高效能互連網路
  • 自主/意圖驅動型網路
  • 其他網路架構

第7章：全球資料中心人工智慧最佳化網路基礎設施市場：按部署方式分類

  • 現場
  • 雲
  • 混合

第8章：全球資料中心人工智慧最佳化網路基礎設施市場：按資料中心類別分類

  • 超大規模
  • 企業
  • 搭配
  • 邊緣
  • 其他資料中心類別

第9章：全球資料中心人工智慧最佳化網路基礎設施市場：按人工智慧應用分類

  • 加速人工智慧工作負載
  • 網路自動化和最佳化
  • 預測性運作和維護
  • 人工智慧的其他用途

第10章：全球面向資料中心的AI最佳化網路基礎設施市場：按最終用戶分類

  • 資訊科技/通訊
  • 銀行、金融服務和保險業 (BFSI)
  • 醫療保健
  • 零售與電子商務
  • 製造業
  • 政府/國防
  • 其他最終用戶

第11章：全球資料中心人工智慧最佳化網路基礎設施市場：按地區分類

  • 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
    • 其他南美國家
  • 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12章 主要趨勢

  • 合約、商業夥伴關係與合作、合資企業
  • 企業合併（M&A）
  • 新產品發布
  • 業務拓展
  • 其他關鍵策略

第13章：公司簡介

  • Cisco Systems, Inc.
  • Dell Technologies Inc.
  • Hewlett Packard Enterprise（HPE）
  • Lenovo Group Ltd.
  • IBM Corporation
  • Intel Corporation
  • NVIDIA Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services
  • Huawei Technologies Co., Ltd.
  • Juniper Networks, Inc.
  • Arista Networks, Inc.
  • Broadcom Inc.
  • Oracle Corporation
Product Code: SMRC33717

According to Stratistics MRC, the Global AI-Optimized Network Infrastructure for Data Centers Market is accounted for $28.08 billion in 2026 and is expected to reach $81.82 billion by 2034 growing at a CAGR of 14.3% during the forecast period. AI-Optimized Network Infrastructure for Data Centers refers to advanced networking systems designed to leverage artificial intelligence (AI) for enhanced performance, efficiency, and reliability. By integrating AI-driven analytics, automation, and predictive capabilities, these infrastructures dynamically manage data traffic, optimize resource allocation, and reduce latency across servers, storage, and network devices. They enable real-time monitoring, anomaly detection, and self-healing operations, ensuring high availability and energy efficiency. Such networks support scalable workloads, including AI, machine learning, and big data applications, while minimizing operational complexity.

Market Dynamics:

Driver:

Rising demand for real time analytics processing

Enterprises are increasingly dependent on AI driven insights for decision making, which requires low latency, high bandwidth network infrastructure. AI optimized systems enable faster data flows, predictive routing, and dynamic workload balancing. Vendors are embedding intelligent orchestration tools to handle complex traffic patterns. Sectors such as BFSI, healthcare, and telecom are leading adoption as they rely on real time analytics for mission critical operations. Rising demand for immediate insights is firmly positioning AI optimized networks as a cornerstone of modern data centers.

Restraint:

Shortage of skilled AI network engineers

Deploying and maintaining AI driven network systems requires expertise in machine learning, automation, and cybersecurity. Smaller enterprises struggle to recruit and retain talent, while larger operators face rising costs for specialized skills. Training programs and certifications are being introduced, but the gap remains significant. Vendors are attempting to simplify platforms with automation and user friendly interfaces. Even so, the lack of skilled professionals continues to restrain scalability and slows deployment timelines.

Opportunity:

Partnerships for AI driven network solutions

Collaborative initiatives are enabling integrated solutions that combine AI algorithms with advanced networking hardware. Vendors are forming alliances with cloud providers, telecom operators, and system integrators to broaden reach. These partnerships accelerate innovation and reduce deployment complexity for end users. Industries are leveraging joint solutions to align infrastructure with digital transformation goals. Strategic collaborations are expanding the market scope and positioning partnerships as a key growth catalyst.

Threat:

Increasing cybersecurity and data breach risks

Networks become more intelligent and interconnected, they present larger attack surfaces. Breaches can compromise sensitive analytics data and disrupt mission critical operations. Vendors are investing in encryption, zero trust frameworks, and AI driven threat detection to mitigate risks. Compliance with evolving data protection regulations adds further complexity. Persistent concerns around breaches and privacy are creating hesitation among operators and could slow adoption if not addressed effectively.

Covid-19 Impact:

The Covid 19 pandemic reshaped priorities in network infrastructure, highlighting the need for resilience and automation. Remote work and surging online activity placed unprecedented strain on data centers, forcing operators to optimize traffic flows. AI driven network solutions gained traction as they enabled predictive routing and adaptive bandwidth allocation. Budget constraints initially delayed some projects, but the need for real time analytics quickly accelerated investments. Vendors saw heightened demand for automation enabled platforms that could be managed remotely.

The data center fabric (Spine-Leaf) segment is expected to be the largest during the forecast period

The data center fabric (Spine-Leaf) segment is expected to account for the largest market share during the forecast period due to rising adoption of scalable and low latency architectures in hyperscale facilities. Spine Leaf architectures provide predictable latency and high throughput, making them ideal for AI driven workloads. Operators rely on fabric designs to simplify traffic management and scale infrastructure efficiently. Vendors are enhancing fabric solutions with automation and intelligent monitoring. Hyperscale and cloud providers are driving demand for advanced fabric deployments. This segment's leadership reflects its ability to deliver resilient and scalable connectivity for modern data centers.

The network automation & optimization segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the network automation & optimization segment is predicted to witness the highest growth rate as the expanding need for intelligent traffic management predictive routing. Enterprises are deploying automation frameworks to reduce manual intervention and improve efficiency. AI driven optimization tools enable predictive routing, anomaly detection, and dynamic bandwidth allocation. Vendors are embedding machine learning into platforms to enhance scalability. Adoption is expanding rapidly across industries with complex traffic patterns, such as telecom and BFSI. The segment's growth underscores its role in enabling adaptive and intelligent network operations.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share due to strong hyperscale presence and early adoption of AI driven networking. North America is forecast to hold the largest market share, supported by its mature data center ecosystem and proactive investment in AI optimized infrastructure. The United States leads with hyperscale expansions, cloud native deployments, and AI driven workloads. Canada complements growth with compliance focused initiatives and government backed digital programs. Presence of major technology providers consolidates regional leadership. Rising demand for sustainability and regulatory compliance is shaping adoption across industries.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR owing to rapid digitalization and aggressive expansion of hyperscale and edge facilities. Asia Pacific is anticipated to post the highest CAGR, driven by large scale investments in resilient network infrastructure. China is scaling hyperscale facilities with AI enabled fabrics, while India is fostering growth through digitization programs and fintech expansion. Japan and South Korea emphasize automation and enterprise resilience, accelerating adoption of intelligent networking platforms. Telecom, BFSI, and healthcare industries are fueling demand across the region. Beyond these drivers, Asia Pacific is also benefiting from government incentives for local manufacturing of networking equipment and strong regional investment in 5G rollouts, which are boosting accessibility and accelerating adoption of AI optimized network solutions.

Key players in the market

Some of the key players in AI-Optimized Network Infrastructure for Data Centers Market include Cisco Systems, Inc., Dell Technologies Inc., Hewlett Packard Enterprise (HPE), Lenovo Group Ltd., IBM Corporation, Intel Corporation, NVIDIA Corporation, Microsoft Corporation, Google LLC, Amazon Web Services, Huawei Technologies Co., Ltd., Juniper Networks, Inc., Arista Networks, Inc., Broadcom Inc. and Oracle Corporation.

Key Developments:

In November 2024, Cisco and NVIDIA announced an expanded partnership to integrate NVIDIA's Grace Blackwell GB200 AI systems with Cisco's Ethernet-based networking, creating a unified AI infrastructure solution for data centers. This collaboration aims to simplify deployment and management of massive-scale AI clusters using Cisco's validated designs and NVIDIA's computing platforms.

In September 2024, Dell partnered with Meta to offer a validated design for Meta's Llama 3 models on Dell's AI infrastructure, optimizing the network and compute stack for efficient large-scale model training and inference within customer data centers.

Offerings Covered:

  • Hardware
  • Software
  • Services

Network Architectures Covered:

  • Software-Defined Networking (SDN)
  • Data Center Fabric (Spine-Leaf)
  • High-Performance Interconnect Networks
  • Autonomous / Intent-Based Networks
  • Other Network Architectures

Deployment Models Covered:

  • On-Premises
  • Cloud
  • Hybrid

Data Center Categories Covered:

  • Hyperscale
  • Enterprise
  • Colocation
  • Edge
  • Other Data Center Categories

AI Usages Covered:

  • AI Workload Acceleration
  • Network Automation & Optimization
  • Predictive Operations & Maintenance
  • Other AI Usages

End Users Covered:

  • IT & Telecommunications
  • BFSI
  • Healthcare
  • Retail & E-Commerce
  • Manufacturing
  • Government & Defense
  • 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 2023, 2024, 2025, 2026, 2028, 2032 and 2034
  • 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 End User Analysis
  • 3.7 Emerging Markets
  • 3.8 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-Optimized Network Infrastructure for Data Centers Market, By Offering

  • 5.1 Introduction
  • 5.2 Hardware
    • 5.2.1 AI-Optimized Network Switches
    • 5.2.2 High-Speed Routers & Interconnects
    • 5.2.3 SmartNICs / DPUs
  • 5.3 Software
    • 5.3.1 AI-Driven Network Control & Orchestration
    • 5.3.2 Traffic Optimization & Analytics
  • 5.4 Services
    • 5.4.1 Deployment & Integration
    • 5.4.2 Managed & Support Services

6 Global AI-Optimized Network Infrastructure for Data Centers Market, By Network Architecture

  • 6.1 Introduction
  • 6.2 Software-Defined Networking (SDN)
  • 6.3 Data Center Fabric (Spine-Leaf)
  • 6.4 High-Performance Interconnect Networks
  • 6.5 Autonomous / Intent-Based Networks
  • 6.6 Other Network Architectures

7 Global AI-Optimized Network Infrastructure for Data Centers Market, By Deployment Model

  • 7.1 Introduction
  • 7.2 On-Premises
  • 7.3 Cloud
  • 7.4 Hybrid

8 Global AI-Optimized Network Infrastructure for Data Centers Market, By Data Center Category

  • 8.1 Introduction
  • 8.2 Hyperscale
  • 8.3 Enterprise
  • 8.4 Colocation
  • 8.5 Edge
  • 8.6 Other Data Center Categories

9 Global AI-Optimized Network Infrastructure for Data Centers Market, By AI Usage

  • 9.1 Introduction
  • 9.2 AI Workload Acceleration
  • 9.3 Network Automation & Optimization
  • 9.4 Predictive Operations & Maintenance
  • 9.5 Other AI Usages

10 Global AI-Optimized Network Infrastructure for Data Centers Market, By End User

  • 10.1 Introduction
  • 10.2 IT & Telecommunications
  • 10.3 BFSI
  • 10.4 Healthcare
  • 10.5 Retail & E-Commerce
  • 10.6 Manufacturing
  • 10.7 Government & Defense
  • 10.8 Other End Users

11 Global AI-Optimized Network Infrastructure for Data Centers Market, By Geography

  • 11.1 Introduction
  • 11.2 North America
    • 11.2.1 US
    • 11.2.2 Canada
    • 11.2.3 Mexico
  • 11.3 Europe
    • 11.3.1 Germany
    • 11.3.2 UK
    • 11.3.3 Italy
    • 11.3.4 France
    • 11.3.5 Spain
    • 11.3.6 Rest of Europe
  • 11.4 Asia Pacific
    • 11.4.1 Japan
    • 11.4.2 China
    • 11.4.3 India
    • 11.4.4 Australia
    • 11.4.5 New Zealand
    • 11.4.6 South Korea
    • 11.4.7 Rest of Asia Pacific
  • 11.5 South America
    • 11.5.1 Argentina
    • 11.5.2 Brazil
    • 11.5.3 Chile
    • 11.5.4 Rest of South America
  • 11.6 Middle East & Africa
    • 11.6.1 Saudi Arabia
    • 11.6.2 UAE
    • 11.6.3 Qatar
    • 11.6.4 South Africa
    • 11.6.5 Rest of Middle East & Africa

12 Key Developments

  • 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
  • 12.2 Acquisitions & Mergers
  • 12.3 New Product Launch
  • 12.4 Expansions
  • 12.5 Other Key Strategies

13 Company Profiling

  • 13.1 Cisco Systems, Inc.
  • 13.2 Dell Technologies Inc.
  • 13.3 Hewlett Packard Enterprise (HPE)
  • 13.4 Lenovo Group Ltd.
  • 13.5 IBM Corporation
  • 13.6 Intel Corporation
  • 13.7 NVIDIA Corporation
  • 13.8 Microsoft Corporation
  • 13.9 Google LLC
  • 13.10 Amazon Web Services
  • 13.11 Huawei Technologies Co., Ltd.
  • 13.12 Juniper Networks, Inc.
  • 13.13 Arista Networks, Inc.
  • 13.14 Broadcom Inc.
  • 13.15 Oracle Corporation

List of Tables

  • Table 1 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Offering (2023-2034) ($MN)
  • Table 3 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Hardware (2023-2034) ($MN)
  • Table 4 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By AI-Optimized Network Switches (2023-2034) ($MN)
  • Table 5 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By High-Speed Routers & Interconnects (2023-2034) ($MN)
  • Table 6 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By SmartNICs / DPUs (2023-2034) ($MN)
  • Table 7 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Software (2023-2034) ($MN)
  • Table 8 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By AI-Driven Network Control & Orchestration (2023-2034) ($MN)
  • Table 9 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Traffic Optimization & Analytics (2023-2034) ($MN)
  • Table 10 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Services (2023-2034) ($MN)
  • Table 11 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Deployment & Integration (2023-2034) ($MN)
  • Table 12 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Managed & Support Services (2023-2034) ($MN)
  • Table 13 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Network Architecture (2023-2034) ($MN)
  • Table 14 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Software-Defined Networking (SDN) (2023-2034) ($MN)
  • Table 15 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Data Center Fabric (Spine-Leaf) (2023-2034) ($MN)
  • Table 16 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By High-Performance Interconnect Networks (2023-2034) ($MN)
  • Table 17 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Autonomous / Intent-Based Networks (2023-2034) ($MN)
  • Table 18 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Other Network Architectures (2023-2034) ($MN)
  • Table 19 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Deployment Model (2023-2034) ($MN)
  • Table 20 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 21 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Cloud (2023-2034) ($MN)
  • Table 22 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Hybrid (2023-2034) ($MN)
  • Table 23 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Data Center Category (2023-2034) ($MN)
  • Table 24 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Hyperscale (2023-2034) ($MN)
  • Table 25 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Enterprise (2023-2034) ($MN)
  • Table 26 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Colocation (2023-2034) ($MN)
  • Table 27 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Edge (2023-2034) ($MN)
  • Table 28 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Other Data Center Categories (2023-2034) ($MN)
  • Table 29 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By AI Usage (2023-2034) ($MN)
  • Table 30 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By AI Workload Acceleration (2023-2034) ($MN)
  • Table 31 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Network Automation & Optimization (2023-2034) ($MN)
  • Table 32 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Predictive Operations & Maintenance (2023-2034) ($MN)
  • Table 33 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Other AI Usages (2023-2034) ($MN)
  • Table 34 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By End User (2023-2034) ($MN)
  • Table 35 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By IT & Telecommunications (2023-2034) ($MN)
  • Table 36 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By BFSI (2023-2034) ($MN)
  • Table 37 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Healthcare (2023-2034) ($MN)
  • Table 38 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Retail & E-Commerce (2023-2034) ($MN)
  • Table 39 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Manufacturing (2023-2034) ($MN)
  • Table 40 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Government & Defense (2023-2034) ($MN)
  • Table 41 Global AI-Optimized Network Infrastructure for Data Centers Market Outlook, By Other End Users (2023-2034) ($MN)

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