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市場調查報告書
商品編碼
2059118

人工智慧驅動的網路自動化市場預測至2034年：按組件、部署模型、組織規模、技術、應用、最終用戶和地區分類的全球分析

AI-Powered Network Automation Market Forecasts to 2034 - Global Analysis By Component (Solutions and Services), Deployment Model, Organization Size, Technology, Application, 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 的數據，全球人工智慧驅動的網路自動化市場預計將在 2026 年達到 193 億美元，並在預測期內以 10.1% 的複合年成長率成長，到 2034 年達到 420 億美元。

人工智慧驅動的網路自動化是指利用人工智慧 (AI) 和機器學習技術，對電腦網路進行自主管理、配置、最佳化和安全防護，從而最大限度地減少人為干預。這些系統分析網路遙測數據、流量模式和配置數據，以預測問題、執行策略並實施糾正措施。該技術涵蓋了意圖式網路、自癒能力和預測分析，將人工網路操作轉變為智慧自適應流程。人工智慧驅動的自動化能夠為尋求營運效率和可靠性的企業、通訊業者和雲端服務供應商帶來許多好處。

網路日益複雜

網路規模、設備多樣性和服務需求的指數級成長，正使傳統的人工管理方法不堪重負，並推動人工智慧驅動的自動化技術的應用。雲端原生架構、多重雲端部署以及物聯網的普及，帶來了超越人類能力範圍的管理複雜性。人工智慧系統處理大量遙測資料集，以識別異常情況並持續最佳化效能。在降低營運成本的同時保持服務品質的經濟壓力，正在加速對自動化的投資。網路可靠性的需求，需要人工智慧才能大規模提供的預測能力。

對可靠性和控制方面的擔憂

網路管理員和組織對將關鍵基礎設施管理的控制權委託給自動化系統表示嚴重擔憂。人工智慧決策流程缺乏透明度，導致自動化操作造成服務中斷時難以確定責任歸屬。人們擔心自動化修復措施會引發連鎖故障，這限制了完全自主運作的意願。某些行業對人工監督的監管要求也限制了自動化的應用範圍。這種信任缺失使得分階段部署並輔以廣泛的測試和檢驗成為必要。

零接觸配置

零接觸網路配置和管理技術的進步為完全自主的網路部署帶來了巨大機會。人工智慧驅動的系統無需人工干預即可自動發現設備、應用配置並制定策略。新的分店、資料中心和雲端資源可根據預先定義的運作參數進行實例化。部署時間從數週縮短至數小時，顯著提升了網路敏捷性。這些功能使得企業無需專業技術人員即可快速擴展業務並災害復原。

網路安全漏洞

人工智慧驅動的自動化系統本身就是網路攻擊的主要目標，攻擊者試圖大規模操縱網路行為。一旦自動化平台遭到入侵，惡意配置就能立即在整個網路中傳播。針對機器學習模型的對抗性攻擊可以欺騙異常檢測系統。對自動化平台的集中控制會造成單點故障。與傳統方法相比，人工智慧驅動網路的安全框架仍不成熟。

新冠疫情的影響：

新冠疫情暴露了人工管理分散員工的局限性，加速了人工智慧驅動的網路自動化技術的應用。遠距辦公的激增需要快速擴展網路並調整策略，而人工流程無法應對這些挑戰。維運負責人優先投資自動化，以在現場人員減少的情況下維持服務品質。此次危機凸顯了網路彈性中自癒和預測能力的重要性。疫情後的混合模式持續推動對自主網路管理的需求。

在預測期內，服務業預計將佔據最大的市場佔有率。

在預測期內，服務領域預計將佔據最大的市場佔有率。這主要歸功於市場對諮詢、整合和託管服務的廣泛需求，以支援人工智慧自動化技術的應用。企業需要專家指導來制定自動化策略並選擇合適的技術。部署服務可確保與現有網路管理工具和工作流程的正確整合。持續的託管服務提供模型監控、重新訓練和效能最佳化。多供應商人工智慧自動化生態系統的複雜性正在推動對專業服務的持續需求。

預計在預測期內，基於雲端的細分市場將呈現最高的複合年成長率。

在預測期內，受人工智慧自動化平台擴充性和基礎設施需求降低的推動，基於雲端的細分市場預計將呈現最高的成長率。雲端採用使得透過單一介面集中管理分散式網路環境成為可能。預訓練模型和跨客戶網路的智慧共用提高了自動化的效率。雲端資源的彈性能夠適應不斷變化的分析和處理需求。人們對雲端安全性和資料處理的信心不斷增強，正在加速雲端技術的普及應用。

市佔率最大的地區：

在預測期內，北美預計將佔據最大的市場佔有率，這得益於其對先進網路技術的早期應用以及強大的AI研發能力。美國之所以處於主導地位，是因為企業和通訊業者在智慧自動化領域進行了大量投資。主要技術供應商正將產品開發和行銷資源集中於該地區。創業投資的注入正在推動網路AI新創企業的創新。法律規範也支持數據驅動的網路管理方法。

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，這主要得益於大規模的網路擴張和政府主導的數位基礎設施發展舉措。中國處於主導地位，這得益於主要通訊業者將人工智慧廣泛整合到網路管理中。印度數位經濟的成長正在催生對自動化網路營運的需求。東南亞市場正在投資智慧城市和工業4.0基礎設施，對智慧管理提出了更高的要求。政府支持國內技術發展的項目正在增強該地區的能力。

免費客製化服務：

所有購買此報告的客戶均可享受以下免費自訂選項之一：

  • 企業概況
    • 對其他市場參與者（最多 3 家公司）進行全面分析
    • 對主要公司進行SWOT分析（最多3家公司）
  • 區域細分
    • 應客戶要求，我們提供主要國家和地區的市場估算和預測，以及複合年成長率（註：需進行可行性檢查）。
  • 競爭性標竿分析
    • 根據產品系列、地理覆蓋範圍和策略聯盟對領先公司進行基準分析。

目錄

第1章執行摘要

  • 市場概覽及主要亮點
  • 促進因素、挑戰與機遇
  • 競爭格局概述
  • 戰略洞察與建議

第2章：研究框架

  • 研究目標和範圍
  • 相關人員分析
  • 研究假設和限制
  • 調查方法

第3章 市場動態與趨勢分析

  • 市場定義與結構
  • 主要市場促進因素
  • 市場限制與挑戰
  • 投資成長機會和重點領域
  • 產業威脅與風險評估
  • 技術與創新展望
  • 新興市場/高成長市場
  • 監管和政策環境
  • 新冠疫情的影響及復甦前景

第4章：競爭環境與策略評估

  • 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
    • 競爭公司之間的競爭
  • 主要公司市佔率分析
  • 產品基準評效和效能比較

第5章：全球人工智慧驅動的網路自動化市場：按組件分類

  • 解決方案
  • 服務

第6章：全球人工智慧驅動的網路自動化市場：依部署模式分類

  • 基於雲端的
  • 現場
  • 混合實現

第7章 全球人工智慧驅動的網路自動化市場：依組織規模分類

  • 大公司
  • 小型企業
  • 通訊業者

第8章：全球人工智慧驅動的網路自動化市場：按技術分類

  • 機器學習
  • 深度學習
  • 自然語言處理
  • 電腦視覺
  • 強化學習
  • 預測分析
  • 基於意圖的網路

第9章：全球人工智慧驅動的網路自動化市場：按應用領域分類

  • 網路流量管理
  • 網路安全自動化
  • 自癒網路
  • 雲端網路管理
  • 5G網路自動化
  • 物聯網網路最佳化
  • 資料中心自動化

第10章：全球人工智慧驅動的網路自動化市場：按最終用戶分類

  • 通訊業者
  • 雲端服務供應商
  • 公司
  • 政府/國防
  • 金融服務機構
  • 醫療機構
  • 製造公司

第11章 全球人工智慧驅動的網路自動化市場：按地區分類

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 英國
    • 德國
    • 法國
    • 義大利
    • 西班牙
    • 荷蘭
    • 比利時
    • 瑞典
    • 瑞士
    • 波蘭
    • 其他歐洲國家
  • 亞太地區
    • 中國
    • 日本
    • 印度
    • 韓國
    • 澳洲
    • 印尼
    • 泰國
    • 馬來西亞
    • 新加坡
    • 越南
    • 其他亞太國家
  • 南美洲
    • 巴西
    • 阿根廷
    • 哥倫比亞
    • 智利
    • 秘魯
    • 其他南美國家
  • 世界其他地區（RoW）
    • 中東
      • 沙烏地阿拉伯
      • 阿拉伯聯合大公國
      • 卡達
      • 以色列
      • 其他中東國家
    • 非洲
      • 南非
      • 埃及
      • 摩洛哥
      • 其他非洲國家

第12章 策略市場資訊

  • 工業價值網路和供應鏈評估
  • 空白區域和機會地圖
  • 產品演進與市場生命週期分析
  • 通路、經銷商和打入市場策略的評估

第13章 產業趨勢與策略舉措

  • 併購
  • 夥伴關係、聯盟和合資企業
  • 新產品發布和認證
  • 擴大生產能力和投資
  • 其他策略舉措

第14章：公司簡介

  • Cisco Systems Inc.
  • International Business Machines Corporation
  • Hewlett Packard Enterprise Company
  • Juniper Networks Inc.
  • Nokia Corporation
  • Telefonaktiebolaget LM Ericsson
  • Huawei Technologies Co., Ltd.
  • VMware Inc.
  • Oracle Corporation
  • Microsoft Corporation
  • Google LLC
  • Amazon Web Services Inc.
  • Extreme Networks Inc.
  • Fujitsu Limited
  • NEC Corporation
  • Amdocs Limited
  • Infosys Limited
  • Capgemini SE
Product Code: SMRC36658

According to Stratistics MRC, the Global AI-Powered Network Automation Market is accounted for $19.3 billion in 2026 and is expected to reach $42.0 billion by 2034 growing at a CAGR of 10.1% during the forecast period. AI-powered network automation refers to the use of artificial intelligence and machine learning technologies to autonomously manage, configure, optimize, and secure computer networks with minimal human intervention. These systems analyze network telemetry, traffic patterns, and configuration data to predict issues, enforce policies, and execute remediation actions. The technology encompasses intent-based networking, self-healing capabilities, and predictive analytics that transform manual network operations into intelligent, adaptive processes. AI-powered automation serves enterprise, telecom, and cloud provider networks seeking operational efficiency and reliability.

Market Dynamics:

Driver:

Network complexity growth

The exponential growth in network scale, device diversity, and service requirements is overwhelming traditional manual management approaches, driving AI automation adoption. Cloud-native architectures, multi-cloud deployments, and IoT proliferation create management complexity beyond human capacity. AI systems process vast telemetry datasets to identify anomalies and optimize performance continuously. The economic pressure to reduce operational expenditures while maintaining service quality accelerates automation investments. Network reliability demands require predictive capabilities that only AI can provide at scale.

Restraint:

Trust and control concerns

Network administrators and organizations express significant concerns regarding ceding control to automated systems for critical infrastructure management. The opacity of AI decision-making processes creates accountability challenges when automated actions cause service disruptions. Fear of cascading failures from automated remediation limits willingness to enable full autonomy. Regulatory requirements for human oversight in certain industries constrain automation scope. These trust deficits necessitate gradual adoption with extensive testing and validation.

Opportunity:

Zero-touch provisioning

The advancement of zero-touch network provisioning and management presents substantial opportunities for fully autonomous network deployment. AI-driven systems can automatically discover devices, apply configurations, and establish policies without manual intervention. New branch offices, data centers, and cloud resources are instantiated with pre-defined operational parameters. The reduction in deployment time from weeks to hours transforms network agility. These capabilities enable rapid business expansion and disaster recovery without specialized technical staffing.

Threat:

Cybersecurity vulnerabilities

AI-powered automation systems themselves become attractive targets for cyberattacks seeking to manipulate network behavior at scale. Compromised automation platforms could propagate malicious configurations across entire networks instantaneously. Adversarial attacks on machine learning models may deceive anomaly detection systems. The concentration of control in automation platforms creates single points of failure. Security frameworks for AI-driven networks remain immature compared to traditional approaches.

Covid-19 Impact:

The COVID-19 pandemic accelerated AI-powered network automation adoption by demonstrating the limitations of manual management for distributed workforces. Remote work surges required rapid network scaling and policy adjustments that manual processes could not support. Operators prioritized automation investments to maintain service quality with reduced on-site staffing. The crisis highlighted the value of self-healing and predictive capabilities for network resilience. Post-pandemic hybrid models sustain demand for autonomous network management.

The services segment is expected to be the largest during the forecast period

The services segment is expected to account for the largest market share during the forecast period, due to extensive demand for consulting, integration, and managed services supporting AI automation deployment. Organizations require expert guidance to design automation strategies and select appropriate technologies. Implementation services ensure proper integration with existing network management tools and workflows. Ongoing managed services provide model monitoring, retraining, and performance optimization. The complexity of multi-vendor AI automation ecosystems drives sustained professional service demand.

The cloud-based segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the cloud-based segment is predicted to witness the highest growth rate, driven by scalability and reduced infrastructure requirements for AI automation platforms. Cloud deployment enables centralized management of distributed network environments from a single interface. Pre-trained models and shared intelligence across customer networks improve automation effectiveness. The elasticity of cloud resources supports fluctuating analysis and processing demands. Growing confidence in cloud security and data handling accelerates adoption.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to early adoption of advanced network technologies and strong AI research capabilities. The United States leads with significant enterprise and telecom investments in intelligent automation. Major technology vendors concentrate their product development and marketing resources. Venture capital availability fuels innovation in network AI startups. Regulatory frameworks support data-driven network management approaches.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by massive network expansion and government digital infrastructure initiatives. China leads with extensive AI integration in network management by major operators. India's growing digital economy creates demand for automated network operations. Southeast Asian markets invest in smart city and Industry 4.0 infrastructure, requiring intelligent management. Government programs supporting domestic technology development strengthen regional capabilities.

Key players in the market

Some of the key players in AI-Powered Network Automation Market include Cisco Systems Inc., International Business Machines Corporation, Hewlett Packard Enterprise Company, Juniper Networks Inc., Nokia Corporation, Telefonaktiebolaget LM Ericsson, Huawei Technologies Co., Ltd., VMware Inc., Oracle Corporation, Microsoft Corporation, Google LLC, Amazon Web Services Inc., Extreme Networks Inc., Fujitsu Limited, NEC Corporation, Amdocs Limited, Infosys Limited and Capgemini SE.

Key Developments:

In May 2026, Cisco Systems Inc. launched an AI-driven network automation platform with intent-based configuration and self-healing capabilities, reducing manual intervention for enterprise campus and data center networks.

In April 2026, International Business Machines Corporation expanded its AIops for networks solution with generative AI-powered troubleshooting, enabling natural language diagnosis and automated remediation recommendation generation.

In March 2026, Hewlett Packard Enterprise Company introduced a cloud-native network automation suite with embedded machine learning for predictive capacity planning and automated policy enforcement across hybrid infrastructure.

Components Covered:

  • Solutions
  • Services

Deployment Models Covered:

  • Cloud-Based
  • On-Premises
  • Hybrid Deployment

Organization Sizes Covered:

  • Large Enterprises
  • Small & Medium Enterprises
  • Telecom Operators

Technologies Covered:

  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Computer Vision
  • Reinforcement Learning
  • Predictive Analytics
  • Intent-Based Networking

Applications Covered:

  • Network Traffic Management
  • Network Security Automation
  • Self-Healing Networks
  • Cloud Network Management
  • 5G Network Automation
  • IoT Network Optimization
  • Data Center Automation

End Users Covered:

  • Telecom Operators
  • Cloud Service Providers
  • Enterprises
  • Government & Defense
  • BFSI Organizations
  • Healthcare Institutions
  • Manufacturing Enterprises

Regions Covered:

  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • United Kingdom
    • Germany
    • France
    • Italy
    • Spain
    • Netherlands
    • Belgium
    • Sweden
    • Switzerland
    • Poland
    • Rest of Europe
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Australia
    • Indonesia
    • Thailand
    • Malaysia
    • Singapore
    • Vietnam
    • Rest of Asia Pacific
  • South America
    • Brazil
    • Argentina
    • Colombia
    • Chile
    • Peru
    • Rest of South America
  • Rest of the World (RoW)
    • Middle East
  • Saudi Arabia
  • United Arab Emirates
  • Qatar
  • Israel
  • Rest of Middle East
    • Africa
  • South Africa
  • Egypt
  • Morocco
  • Rest of 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, 2027, 2028, 2030, 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

  • 1.1 Market Snapshot and Key Highlights
  • 1.2 Growth Drivers, Challenges, and Opportunities
  • 1.3 Competitive Landscape Overview
  • 1.4 Strategic Insights and Recommendations

2 Research Framework

  • 2.1 Study Objectives and Scope
  • 2.2 Stakeholder Analysis
  • 2.3 Research Assumptions and Limitations
  • 2.4 Research Methodology
    • 2.4.1 Data Collection (Primary and Secondary)
    • 2.4.2 Data Modeling and Estimation Techniques
    • 2.4.3 Data Validation and Triangulation
    • 2.4.4 Analytical and Forecasting Approach

3 Market Dynamics and Trend Analysis

  • 3.1 Market Definition and Structure
  • 3.2 Key Market Drivers
  • 3.3 Market Restraints and Challenges
  • 3.4 Growth Opportunities and Investment Hotspots
  • 3.5 Industry Threats and Risk Assessment
  • 3.6 Technology and Innovation Landscape
  • 3.7 Emerging and High-Growth Markets
  • 3.8 Regulatory and Policy Environment
  • 3.9 Impact of COVID-19 and Recovery Outlook

4 Competitive and Strategic Assessment

  • 4.1 Porter's Five Forces Analysis
    • 4.1.1 Supplier Bargaining Power
    • 4.1.2 Buyer Bargaining Power
    • 4.1.3 Threat of Substitutes
    • 4.1.4 Threat of New Entrants
    • 4.1.5 Competitive Rivalry
  • 4.2 Market Share Analysis of Key Players
  • 4.3 Product Benchmarking and Performance Comparison

5 Global AI-Powered Network Automation Market, By Component

  • 5.1 Solutions
  • 5.2 Services

6 Global AI-Powered Network Automation Market, By Deployment Model

  • 6.1 Cloud-Based
  • 6.2 On-Premises
  • 6.3 Hybrid Deployment

7 Global AI-Powered Network Automation Market, By Organization Size

  • 7.1 Large Enterprises
  • 7.2 Small & Medium Enterprises
  • 7.3 Telecom Operators

8 Global AI-Powered Network Automation Market, By Technology

  • 8.1 Machine Learning
  • 8.2 Deep Learning
  • 8.3 Natural Language Processing
  • 8.4 Computer Vision
  • 8.5 Reinforcement Learning
  • 8.6 Predictive Analytics
  • 8.7 Intent-Based Networking

9 Global AI-Powered Network Automation Market, By Application

  • 9.1 Network Traffic Management
  • 9.2 Network Security Automation
  • 9.3 Self-Healing Networks
  • 9.4 Cloud Network Management
  • 9.5 5G Network Automation
  • 9.6 IoT Network Optimization
  • 9.7 Data Center Automation

10 Global AI-Powered Network Automation Market, By End User

  • 10.1 Telecom Operators
  • 10.2 Cloud Service Providers
  • 10.3 Enterprises
  • 10.4 Government & Defense
  • 10.5 BFSI Organizations
  • 10.6 Healthcare Institutions
  • 10.7 Manufacturing Enterprises

11 Global AI-Powered Network Automation Market, By Geography

  • 11.1 North America
    • 11.1.1 United States
    • 11.1.2 Canada
    • 11.1.3 Mexico
  • 11.2 Europe
    • 11.2.1 United Kingdom
    • 11.2.2 Germany
    • 11.2.3 France
    • 11.2.4 Italy
    • 11.2.5 Spain
    • 11.2.6 Netherlands
    • 11.2.7 Belgium
    • 11.2.8 Sweden
    • 11.2.9 Switzerland
    • 11.2.10 Poland
    • 11.2.11 Rest of Europe
  • 11.3 Asia Pacific
    • 11.3.1 China
    • 11.3.2 Japan
    • 11.3.3 India
    • 11.3.4 South Korea
    • 11.3.5 Australia
    • 11.3.6 Indonesia
    • 11.3.7 Thailand
    • 11.3.8 Malaysia
    • 11.3.9 Singapore
    • 11.3.10 Vietnam
    • 11.3.11 Rest of Asia Pacific
  • 11.4 South America
    • 11.4.1 Brazil
    • 11.4.2 Argentina
    • 11.4.3 Colombia
    • 11.4.4 Chile
    • 11.4.5 Peru
    • 11.4.6 Rest of South America
  • 11.5 Rest of the World (RoW)
    • 11.5.1 Middle East
      • 11.5.1.1 Saudi Arabia
      • 11.5.1.2 United Arab Emirates
      • 11.5.1.3 Qatar
      • 11.5.1.4 Israel
      • 11.5.1.5 Rest of Middle East
    • 11.5.2 Africa
      • 11.5.2.1 South Africa
      • 11.5.2.2 Egypt
      • 11.5.2.3 Morocco
      • 11.5.2.4 Rest of Africa

12 Strategic Market Intelligence

  • 12.1 Industry Value Network and Supply Chain Assessment
  • 12.2 White-Space and Opportunity Mapping
  • 12.3 Product Evolution and Market Life Cycle Analysis
  • 12.4 Channel, Distributor, and Go-to-Market Assessment

13 Industry Developments and Strategic Initiatives

  • 13.1 Mergers and Acquisitions
  • 13.2 Partnerships, Alliances, and Joint Ventures
  • 13.3 New Product Launches and Certifications
  • 13.4 Capacity Expansion and Investments
  • 13.5 Other Strategic Initiatives

14 Company Profiles

  • 14.1 Cisco Systems Inc.
  • 14.2 International Business Machines Corporation
  • 14.3 Hewlett Packard Enterprise Company
  • 14.4 Juniper Networks Inc.
  • 14.5 Nokia Corporation
  • 14.6 Telefonaktiebolaget LM Ericsson
  • 14.7 Huawei Technologies Co., Ltd.
  • 14.8 VMware Inc.
  • 14.9 Oracle Corporation
  • 14.10 Microsoft Corporation
  • 14.11 Google LLC
  • 14.12 Amazon Web Services Inc.
  • 14.13 Extreme Networks Inc.
  • 14.14 Fujitsu Limited
  • 14.15 NEC Corporation
  • 14.16 Amdocs Limited
  • 14.17 Infosys Limited
  • 14.18 Capgemini SE

List of Tables

  • Table 1 Global AI-Powered Network Automation Market Outlook, By Region (2023-2034) ($MN)
  • Table 2 Global AI-Powered Network Automation Market Outlook, By Component (2023-2034) ($MN)
  • Table 3 Global AI-Powered Network Automation Market Outlook, By Solutions (2023-2034) ($MN)
  • Table 4 Global AI-Powered Network Automation Market Outlook, By Services (2023-2034) ($MN)
  • Table 5 Global AI-Powered Network Automation Market Outlook, By Deployment Model (2023-2034) ($MN)
  • Table 6 Global AI-Powered Network Automation Market Outlook, By Cloud-Based (2023-2034) ($MN)
  • Table 7 Global AI-Powered Network Automation Market Outlook, By On-Premises (2023-2034) ($MN)
  • Table 8 Global AI-Powered Network Automation Market Outlook, By Hybrid Deployment (2023-2034) ($MN)
  • Table 9 Global AI-Powered Network Automation Market Outlook, By Organization Size (2023-2034) ($MN)
  • Table 10 Global AI-Powered Network Automation Market Outlook, By Large Enterprises (2023-2034) ($MN)
  • Table 11 Global AI-Powered Network Automation Market Outlook, By Small & Medium Enterprises (2023-2034) ($MN)
  • Table 12 Global AI-Powered Network Automation Market Outlook, By Telecom Operators (2023-2034) ($MN)
  • Table 13 Global AI-Powered Network Automation Market Outlook, By Technology (2023-2034) ($MN)
  • Table 14 Global AI-Powered Network Automation Market Outlook, By Machine Learning (2023-2034) ($MN)
  • Table 15 Global AI-Powered Network Automation Market Outlook, By Deep Learning (2023-2034) ($MN)
  • Table 16 Global AI-Powered Network Automation Market Outlook, By Natural Language Processing (2023-2034) ($MN)
  • Table 17 Global AI-Powered Network Automation Market Outlook, By Computer Vision (2023-2034) ($MN)
  • Table 18 Global AI-Powered Network Automation Market Outlook, By Reinforcement Learning (2023-2034) ($MN)
  • Table 19 Global AI-Powered Network Automation Market Outlook, By Predictive Analytics (2023-2034) ($MN)
  • Table 20 Global AI-Powered Network Automation Market Outlook, By Intent-Based Networking (2023-2034) ($MN)
  • Table 21 Global AI-Powered Network Automation Market Outlook, By Application (2023-2034) ($MN)
  • Table 22 Global AI-Powered Network Automation Market Outlook, By Network Traffic Management (2023-2034) ($MN)
  • Table 23 Global AI-Powered Network Automation Market Outlook, By Network Security Automation (2023-2034) ($MN)
  • Table 24 Global AI-Powered Network Automation Market Outlook, By Self-Healing Networks (2023-2034) ($MN)
  • Table 25 Global AI-Powered Network Automation Market Outlook, By Cloud Network Management (2023-2034) ($MN)
  • Table 26 Global AI-Powered Network Automation Market Outlook, By 5G Network Automation (2023-2034) ($MN)
  • Table 27 Global AI-Powered Network Automation Market Outlook, By IoT Network Optimization (2023-2034) ($MN)
  • Table 28 Global AI-Powered Network Automation Market Outlook, By Data Center Automation (2023-2034) ($MN)
  • Table 29 Global AI-Powered Network Automation Market Outlook, By End User (2023-2034) ($MN)
  • Table 30 Global AI-Powered Network Automation Market Outlook, By Telecom Operators (2023-2034) ($MN)
  • Table 31 Global AI-Powered Network Automation Market Outlook, By Cloud Service Providers (2023-2034) ($MN)
  • Table 32 Global AI-Powered Network Automation Market Outlook, By Enterprises (2023-2034) ($MN)
  • Table 33 Global AI-Powered Network Automation Market Outlook, By Government & Defense (2023-2034) ($MN)
  • Table 34 Global AI-Powered Network Automation Market Outlook, By BFSI Organizations (2023-2034) ($MN)
  • Table 35 Global AI-Powered Network Automation Market Outlook, By Healthcare Institutions (2023-2034) ($MN)
  • Table 36 Global AI-Powered Network Automation Market Outlook, By Manufacturing Enterprises (2023-2034) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Rest of the World (RoW) Regions are also represented in the same manner as above.