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蜂窩網路中的人工智慧：2025-2029 年全球市場
市場調查報告書
商品編碼
1698611

蜂窩網路中的人工智慧：2025-2029 年全球市場

Global AI in Cellular Networks Market: 2025-2029
出版日期: | 出版商: Juniper Research Ltd | 英文 | 商品交期: 最快1-2個工作天內

價格
簡介目錄

隨著 "零接觸" 成為焦點，預計未來四年電信公司 AI 投資將超過 860 億美元

關鍵統計
2025 年電信業者在蜂巢網路的 AI 支出： 135億美元
2029 年電信業者在蜂巢網路的 AI 支出： 229億美元
電信公司正在投資數位轉型： 1080億美元
預測期間： 2025-2029

此研究套件為電信業者和網路 AI 供應商提供分析和可行的見解。它還包含數據，以幫助市場利益相關者（例如行動網路營運商 (MNO) 和網路 AI 供應商）就其網路中 AI 參與的業務策略做出明智的決策。該研究包括八個關於營運商在蜂窩網路中採用人工智慧的案例研究，以及一個關於 Indosat Ooredoo Hutchison 的 AI-RAN 策略的案例研究。這些案例研究包括：

  • 美國電話電報公司
  • 中國移動
  • 德國電信
  • 西班牙電信公司
  • SK電信
  • 標準
  • 威瑞森
  • 沃達豐

這些案例研究分析了領先的電信營運商如何在其網路中部署和創新人工智慧、其部署和創新的核心優勢，並評估了這些部署如何為營運商的未來定位。這將使其他電信營運商和網路AI供應商瞭解市場領先的營運商如何處理網路AI，幫助他們做出更明智的決策並制定策略。

該研究套件還包括營運商部署網路 AI 的關鍵目標的細分，以及他們預期這些目標未來如何發展的分析。此外，它還對無線存取網路（RAN）中的人工智慧、AI-RAN聯盟、水平RAN堆疊的開發、主權人工智慧、網路規劃中的人工智慧、網路維護中的人工智慧、網路切片中的人工智慧和差異化連接等關鍵概念和技術進行了策略分析。

此外，它還就電信業者如何利用人工智慧來提高網路安全、如何保護其人工智慧部署免受詐欺者和惡意行為者的侵害提供了建議和評估，並就營運商如何最大限度地發揮人工智慧在其數據中心和雲端基礎設施中的影響提供了戰略分析。這將使電信營運商、網路 AI 供應商和其他利害關係人能夠有效地評估 AI 採用的不同領域並做出明智的商業決策。

該報告還提供了對其他技術和標準的見解，包括基於代理的人工智慧、TeleManagement™ Forum 的自主網路、6G、大型語言模型 (LLM) 和 GSMA 的 Open-Telco LLM 基準。每個部分都包含來自 Juniper Research 的建議和分析，以幫助瞭解主要趨勢以及確定未來研發的機會和策略。

主要特點

  • 市場動態：深入瞭解蜂窩網路市場中 AI 的主要趨勢和機遇，包括 AI-RAN 聯盟對 AI-RAN 的開發、主權 AI 的作用、AI 在網路安全中的應用，以及運營商 AI 用例的演變；對八大運營商在其網絡中使用人工智能的戰略分析；以及運營商 AI 用例的演變；對八大運營商在其網絡中使用人工智能的戰略分析；以及運營商部署示例和投資。
  • 關鍵要點和策略建議：本報告深入分析了蜂窩網路市場人工智慧的關鍵發展機會和見解，並為希望增加收入並在產品供應中獲得優勢的營運商和人工智慧網路供應商提供了策略建議。
  • 基準產業預測：提供 SIM 卡總數、營運商收入、營運商數位轉型總投資、營運商 AI 總投資、營運商網路 AI 總投資的數據。營運商在網路 AI 方面的總投資分為營運商在 RAN 方面的網路 AI 總投資、營運商在編排和管理方面的網路 AI 總投資、營運商在網路安全方面的網路 AI 總投資以及營運商在營運和維護 (O&M) 方面的網路 AI 總投資。
  • Juniper Research 的未來領導者指數：評估 16 家網路 AI 供應商的能力，並為每個供應商提供市場規模和詳細分析。

範例視圖

市場數據與預測


市場數據與預測

研究套件包括存取包含超過 7,900 個資料點的全套預測資料。該調查套件包括以下指標：

  • 承運商總收入
  • 電信業者數位轉型投資總額
  • 電信公司在人工智慧方面的總投資
  • 網路人工智慧總投資
  • 營運商對 RAN 網路 AI 的總投資
  • 電信公司在網路 AI 編排與管理的總投資
  • 電信業者在網路安全方面對網路人工智慧的總投資
  • 營運商在網路維運人工智慧方面的總投資

Juniper Research Interactive Forecast (Excel) 包含以下功能：

  • 統計分析：能夠搜尋資料期間所有地區和國家顯示的特定指標。可以輕鬆修改圖表並將其匯出到剪貼簿。
  • 國家資料工具：此工具可讓您查看預測期間內所有地區和國家的指標。您可以使用搜尋欄縮小顯示的指標範圍。
  • 國家比較工具：您可以選擇特定的國家進行比較。該工具具有匯出圖表的功能。
  • 假設分析：透過三個互動式場景，使用者可以比較預測假設。

目錄

市場趨勢/策略

第1章 重點與策略建議

第2章 市場狀況

  • 為什麼電信業者希望在其網路中部署人工智慧
  • 利用人工智慧降低網路整體擁有成本
  • 利用人工智慧實現淨零目標
  • 利用人工智慧改善和擴展營運商服務 世界領先的電信營運商如何在其網路中使用人工智慧

第3章 關鍵科技與未來機會

  • 網路人工智慧關鍵技術
    • 代理人工智慧
    • 6G
    • 法學碩士
  • 人工智慧網路應用的重大機遇
    • 艾然
    • 網路資料中心和雲端管理的人工智慧
    • 網路安全人工智慧
    • 人工智慧用於網路維護
    • 人工智慧用於網路規劃
    • 用於網路切片和差異化連接的人工智慧

競技排行榜

第1章競技排行榜

第2章 供應商簡介

  • 供應商資料
    • Blue Planet
    • Cisco
    • Ericsson
    • Google Cloud
    • Huawei
    • IBM
    • Jio Platforms
    • Juniper Networks
    • Mavenir
    • Microsoft
    • Netcracker
    • Nokia
    • NVIDIA
    • Samsung
    • Subex
    • ZTE
  • Juniper Research 排行榜評估方法
  • 限制和解釋
  • 相關研究

數據和預測

第1章 引言與研究方法

第2章市場總結及未來市場展望

  • 營運商總收入
  • 電信業者在網路人工智慧方面的總投資
  • 營運商對 RAN AI 的網路 AI 總投資
  • 電信業者在網路編排和管理方面對網路 AI 的總投資
  • 電信業者在網路安全方面對網路人工智慧的總投資
  • 電信業者在網路運維人工智慧方面的總投資
簡介目錄

'Operator AI Investment to Exceed $86bn Over the Next Four Years as 'Zero Touch' Becomes the Focus'

KEY STATISTICS
Total operator investment in AI in cellular networks in 2025:$13.5bn
Total operator investment in AI in cellular networks in 2029:$22.9bn
Total operator investment in digital transformation:$108bn
Forecast period:2025-2029

Overview

Our "AI in Cellular Networks" research suite provides operators and AI in network vendors with analysis and actionable insights. It also includes data which enables stakeholders in the market, such as mobile network operators (MNOs) and network AI vendors, to make informed decisions on business strategy for their involvement with AI in networks. The research suite covers eight case studies into operators' AI in cellular networks deployments, as well as a further case study for Indosat Ooredoo Hutchison's AI-RAN strategy. These case studies include:

  • AT&T
  • China Mobile
  • Deutsche Telekom
  • Telefonica
  • SK Telecom
  • stc
  • Verizon
  • Vodafone

Each of these case studies breaks down how a leading operator is deploying and innovating with AI in their networks, with analysis from Juniper Research on the core strengths of their deployments and innovations, and evaluation of how these deployments position the operator in the future. This allows other operators and network AI vendors to understand how those at the forefront of the market are approaching network AI; supporting informed decision-making and strategy formulation.

The research suite also includes a breakdown of the key goals of operators' AI in networks deployments, with analysis of how Juniper Research expects these goals to evolve in the future. This is coupled with strategic analysis of key concepts and technologies, including AI in Radio Access Network (RAN), the AI-RAN Alliance, the development of horizontal RAN stacks, sovereign AI, AI in network planning, AI in network maintenance, and AI in network slicing and differentiated connectivity.

It further provides recommendations and assessments on how operators can use AI to improve their network security, as well as protect their own AI deployments from fraudsters and malicious actors, and strategic analysis of how operators can maximise the impact of AI in their datacentres and cloud infrastructure. Through this, operators, network AI vendors, and other stakeholders can effectively evaluate and make informed business decisions regarding different areas of AI deployments.

As well as this, the report offers insight into technologies and standards including agentic AI, TeleManagement (TM) Forum's Autonomous Networks, 6G, large language model (LLM), and the GSMA's Open-Telco LLM Benchmarks. Accompanied by Juniper Research's recommendations and analysis, each of these sections identifies future development opportunities and strategies, in addition to providing an understanding of key trends.

The market forecast suite includes several different options that can be purchased separately, including access to data mapping and a forecast document, a strategy and trends document detailing critical trends in the market, and strategic recommendations for monetising and innovating AI in cellular networks.

The research suite includes a Competitor Leaderboard, which can be purchased separately; containing analysis and market sizing for 16 leading network AI vendors, who each provide operators with software for AI in network deployments.

Collectively, the suite provides a critical tool for understanding the AI in cellular networks market allowing operators, AI in network vendors, and other stakeholders to optimise their future business and product development strategies for the market; providing a competitive advantage over their rivals.

All report content is delivered in the English language.

Key Features

  • Market Dynamics: Insights into the key trends and opportunities within the AI in cellular networks market, including the development of AI-RAN by the AI-RAN Alliance, the role of sovereign AI, how AI is being used in network security, and how operators are progressing their AI use cases. It also includes strategic analysis of eight leading operators' use of AI in their networks, with a case study into each operator's deployments and investments.
  • Key Takeaways & Strategic Recommendations: In-depth analysis of key development opportunities and findings within the AI in cellular networks market, accompanied by strategic recommendations for operators and AI in network vendors seeking to grow their revenue or gain an advantage in their product offerings.
  • Benchmark Industry Forecasts: The suite provides four-year forecasts for the global AI in cellular networks market; providing data for the total number of SIMs, total operator revenue, total operator investment in digital transformation, total operator investment in AI, and total operator investment in network AI. Total operator investment in network AI is provided with splits for total operator investment in network AI for RAN, total operator investment in network AI for orchestration and management, total operator investment in network AI for network security, and total operator investment in network AI for operations and maintenance (O&M).
  • Juniper Research Future Leaders' Index: Key player capability and capacity assessment for 16 AI in networks vendors, with market sizing and detailed analysis for each vendor's offering.

SAMPLE VIEW

Market Data & Forecasts


The numbers tell you what's happening, but our written report details why, alongside the methodologies.

Market Data & Forecasts

The market-leading research suite for the AI in networks market includes access to the full set of forecast data, comprising more than 7,900 datapoints. Metrics in the research suite include:

  • Total Operator Revenue
  • Total Operator Investment in Digital Transformation
  • Total Operator Investment in AI
  • Total Operator Investment in Network AI
  • Total Operator Investment in Network AI for RAN
  • Total Operator Investment in Network AI for Orchestration and Management
  • Total Operator Investment in Network AI for Network Security
  • Total Operator Investment in Network AI for O&M

Juniper Research's Interactive Forecast Excel contains the following functionality:

  • Statistics Analysis: Users benefit from the ability to search for specific metrics, displayed for all regions and countries across the data period. Graphs are easily modified and can be exported to the clipboard.
  • Country Data Tool: This tool lets users look at metrics for all regions and countries in the forecast period. Users can refine the metrics displayed via a search bar.
  • Country Comparison Tool: Users can select and compare specific countries. The ability to export graphs is included in this tool.
  • What-if Analysis: Here, users can compare forecast metrics against their own assumptions, via three interactive scenarios.

Market Trends & Strategies Report

The report thoroughly examines the global "AI in Cellular Networks" market; assessing market trends, technological developments, and commercial opportunities which are shaping the market both in the present and the future. Alongside this analysis, the document includes a comprehensive analysis of the different areas of AI deployment, such as in RAN, datacentre management, and network slicing; with this analysis supporting stakeholders in evaluating how they can separate from their competition and become a market leader.

This innovative ecosystem report also includes a breakdown and evaluation of eight leading operators' investments and deployments for network AI. These case studies allow players in the network AI market to better understand the direction of leaders in the market, in turn providing insight into key trends and a foundation to develop their own business and product or technology development strategies.

Competitor Leaderboard Report

The Competitor Leaderboard included in this report provides detailed evaluation and market positioning for 16 network AI vendors. These key companies are positioned as established leaders, leading challengers, or disruptors and challengers, based on a capacity, capability, and product assessment. This includes analysis of their key advantages in the market, future development plans, and key partnerships.

The AI in Cellular Networks Competitor Leaderboard includes the following key vendors:

  • Blue Planet
  • Cisco
  • Ericsson
  • Google Cloud
  • Huawei
  • IBM
  • Jio Platforms
  • Juniper Networks
  • Mavenir
  • Microsoft
  • Netcracker
  • Nokia
  • NVIDIA
  • Samsung
  • Subex
  • ZTE

Table of Contents

Market Trends & Strategies

1. Key Takeaways Strategic Recommendations

  • 1.1. Key Takeaways
  • 1.2. Key Strategic Recommendations

2. Market Landscape

  • 2.1. Introduction
    • Figure 2.1: Total Operator Investment in Network AI ($m), Split By 8 Key Regions, 2024-2029
    • 2.1.1. Why Are Operators Seeking to Deploy AI in Their Networks
    • 2.1.2. Using AI to Reduce Network TCO
      • Figure 2.2: Total Number of 5G Connections (m), Split By 8 Key Regions, 2024-2029
    • 2.1.3. Using AI to Meet Net Zero Goals
      • Figure 2.3: Total Operator Energy Savings (TWh), Split By 8 Key Regions, 2024-2029
      • Table 2.4: Examples of Areas Explored for AI Use for Energy Efficiency in 5G
    • 2.1.4. Using AI to Improve and Expand Operator Services
      • Figure 2.5: Total Operator Revenue ($m), Split By 8 Key Regions, 2024-2029
  • 2.2. How Leading Operators Are Using AI in Their Networks Around the World

3. Key Technologies and Future Opportunities

  • 3.1. Key Technologies for AI in Networks
    • 3.1.1. Agentic AI
      • i. TM Forum's Autonomous Networks
        • Figure 3.1: TM Forum's Autonomous Network Levels
    • 3.1.2. 6G
      • Figure 3.3: 3GPP Timeline and Ericsson Expectations for First Commercial System
    • 3.1.3. LLMs
      • Figure 3.4: Use Cases for LLMs in Operator Networks
      • i. GSMA Open Telco LLM Benchmarks and Custom Operator LLMs
        • Table 3.5: Accuracy Comparison Between GPT-3.5, GPT-4, and Active Professionals
  • 3.2. Key Opportunities for AI Network Deployments
    • 3.2.1. AI RAN
      • Figure 3.6: Benefits Expected to be Provided by AI-RAN
      • ii. AI Services and Multi-tenant RAN Infrastructure
        • Table 3.7: NVIDIA and Softbank's Achievements With AI-RAN as of February 2025
        • Figure 3.8: Schematic of Multi-tenant AI RAN Reference Architecture
        • Figure 3.9: GPT-4 3-Shot Accuracy on MMLU Languages
        • Tables 3.10: Examples of Sovereign AI Initiatives, Investments and Policies
    • 3.2.2. AI for Network Datacentre and Cloud Management
      • Figure 3.11: Total Operator Expenditure on Cloud ($m), Split by 8 Key Regions, 2023-2028
    • 3.2.3. AI for Network Security
      • i. Operator Strategies for Using AI to Protect Their Networks
        • Figure 3.12: Key Use Cases for AI Security in Cellular Networks
      • ii. The Threat of AI to Operator Networks
    • 3.2.4. AI for Network Maintenance
    • 3.2.5. AI for Network Planning
    • 3.2.6. AI for Network Slicing and Differentiated Connectivity
      • Figure 3.13: Key Types of Network Slicing

Competitor Leaderboard

1. Competitor Leaderboard

  • 1.1. Why Read This Report
    • AI Development Must Be Focused on Creating Dynamic Infrastructure and Operations
      • Table 1.1: Juniper Research Competitor Leaderboard Vendors and Product Portfolios
      • Figure 1.2: Juniper Research Competitor Leaderboard: Network AI Vendors
        • Source: Juniper ResearchTable 1.3: Juniper Research Competitor Leaderboard: Network AI Vendors
      • Table 1.4: Juniper Research Competitor Leaderboard Heatmap: Network AI Vendors (1 of 2)
      • Table 1.5: Juniper Research Competitor Leaderboard Heatmap: Network AI Vendors (2 of 2)

2. Vendor Profiles

  • 2.1. Vendor Profiles
    • 2.1.1. Blue Planet
      • i. Corporate Information
        • Figure 2.1: Blue Planet Revenue ($m), Financial Year 2023-2024
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.2: Blue Planet 5G Network Planning and Deployment Solution
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.2. Cisco
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.3: Cisco Crosswork Network Automation Tenets
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.3. Ericsson
      • i. Corporate Information
        • Table 2.4. Ericsson's Financial Information ($m), 2021-2024
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.5: Ericsson Intelligent Automation Platform (EIAP)
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.4. Google Cloud
      • i. Corporate Information
      • ii. Geographical Spread
        • Figure 2.6: Google Cloud Platform Regions
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.5. Huawei
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.6. IBM
      • i. Corporate Information
        • Table 2.7: IBM's Select Financial Information ($m), 2021-2023
      • ii. Geographical Spread
        • Figure 2.8: IBM Datacentre and Machine-readable Zones (MZRs) Location Map
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.9: IBM Cloud Paks for Network Automation
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.7. Jio Platforms
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.8. Juniper Networks
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.10: Juniper Networks' O-RAN Offering
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.9. Mavenir
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.11: Mavenir's AI & Analytics Solutions
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.10. Microsoft
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.12: Azure Operator Nexus
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.11. Netcracker
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.13: Netcracker Network Automation Suite
        • Figure 2.14: E2E Service and Slice Automation
        • Figure 2.15: Network Domain Orchestration
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.12. Nokia
      • i. Corporate Information
        • Table 2.16: Nokia's Select Financial Information ($m), 2021-2024
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.13. NVIDIA
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.17: NVIDIA Aerial CUDA-accelerated RAN Stack Diagram Showing Full-Stack Virtualised RAN Acceleration
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.14. Samsung
      • Table 2.18: Samsung's Financial Information ($b), 2022-2023
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
        • Figure 2.19: Samsung SMO
        • Figure 2.20: Samsung VISTA
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.15. Subex
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
    • 2.1.16. ZTE
      • i. Corporate Information
      • ii. Geographical Spread
      • iii. Key Clients & Strategic Partnerships
      • iv. High-level View of Offerings
      • v. Juniper Research's View: Key Strengths & Strategic Development Opportunities
  • 2.2. Juniper Research Leaderboard Assessment Methodology
  • 2.3. Limitations & Interpretations
    • Table 2.21: Juniper Research Competitor Leaderboard: Global AI in Cellular Networks Market
  • 2.4. Related Research

Data & Forecasting

1. Introduction and Methodology

  • 1.1. Introduction: AI in Networks Market
    • Figure 1.1: Total Operator Investment in Digital Transformation ($m), 2024-2029
  • 1.2. Forecast Methodology
    • Figure 1.2: AI in Networks Forecast Methodology

2. Market Summary and Future Market Outlook

  • 2.1. Total Operator Revenue
    • Figure & Table 2.1: Total Operator Revenue ($m), Split By 8 Key Regions, 2024-2029
  • 2.2. Total Operator Investment in Network AI
    • Figure & Table 2.2: Total Operator Investment in Network AI ($m), Split By 8 Key Regions, 2024-2029
  • 2.3. Total Operator Investment in Network AI for AI for RAN
    • Figure & Table 2.3: Total Operator Investment in Network AI for AI for RAN ($m), Split By 8 Key Regions, 2024-2029
  • 2.4. Total Operator Investment in Network AI for Network Orchestration and Management
    • Figure & Table 2.4: Total Operator Investment in Network AI for Network Orchestration and Management ($m), Split By 8 Key Regions, 2024-2029
  • 2.5. Total Operator Investment in Network AI for Network Security
    • Figure & Table 2.5: Total Operator Investment in Network AI for Network Security ($m), Split By 8 Key Regions, 2024-2029
  • 2.6. Total Operator Investment in Network AI for Operations and Maintenance
    • Figure & Table 2.6: Total Operator Investment in Network AI for O&M ($m), Split By 8 Key Regions, 2024-2029