세계의 셀룰러 네트워크용 AI 시장(2025-2029년)

'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:

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:

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