한글목차

통신 분야 인공지능(AI) 시장 규모는 2025년 21억 2,000만 달러에서 2026년부터 2034년까지 CAGR 21.32%로 성장하여 2034년에는 120억 9,000만 달러에 달할 것으로 예측됩니다.

통신 사업자들이 업무 효율성 향상과 고객 경험 개선을 위해 노력하고 있는 가운데, 통신 분야 인공지능 시장은 괄목할 만한 성장이 예상됩니다. 네트워크 관리의 복잡성과 개인화된 서비스에 대한 수요가 증가함에 따라, AI 기술은 통신 기업에게 필수적인 도구가 되고 있습니다. 머신러닝 알고리즘과 데이터 분석을 통해 사업자는 네트워크 성능 최적화, 유지보수 수요 예측, 일상 업무 자동화를 실현할 수 있습니다. 이를 통해 통신 사업자는 운영 비용을 절감할 수 있을 뿐만 아니라, 고객에게 끊김 없는 연결성과 우수한 서비스 품질을 제공할 수 있습니다.

또한, AI의 통신 분야로의 통합은 챗봇과 가상 비서의 도입을 통해 고객 서비스를 혁신하고 있습니다. 이러한 AI 기반 솔루션은 다양한 고객 문의에 대응하고 즉각적인 지원을 제공함으로써 인간 운영자가 더 복잡한 문제에 집중할 수 있는 환경을 조성합니다. 고객의 기대치가 계속 높아지는 가운데, 24시간 365일 지원과 개인화된 대응을 제공할 수 있는 능력은 통신사에게 중요한 차별화 요소가 될 것입니다. 자연어 처리와 감정 분석의 지속적인 발전으로 고객의 니즈를 이해하고 대응하는 AI의 효용성은 더욱 높아지고 있습니다.

또한, 5G 기술의 등장은 통신 분야에서 AI 애플리케이션의 새로운 가능성을 창출하고 있습니다. 5G 네트워크의 고속, 저지연 특성은 실시간 데이터 처리 및 분석을 가능하게 하고, 통신사업자가 네트워크 관리 및 서비스 제공을 강화하는 AI 솔루션 도입을 촉진합니다. IoT 연결과 스마트 기기의 수요 확대에 따라 네트워크 자원을 최적화하고 안정적인 서비스를 보장하는 데 있어 AI의 역할은 더욱 중요해질 것입니다. 이처럼 끊임없이 진화하는 디지털 환경에서 혁신과 효율성의 필요성에 힘입어 통신 분야 인공지능 시장은 크게 확대될 것으로 예상됩니다.

목차

제1장 소개

제2장 주요 요약

제3장 시장 변수, 동향, 프레임워크

제4장 세계의 통신 분야 인공지능(AI) 시장 : 구성요소별

제5장 세계의 통신 분야 인공지능(AI) 시장 : 기술별

제6장 세계의 통신 분야 인공지능(AI) 시장 : 용도별

제7장 세계의 통신 분야 인공지능(AI) 시장 : 전개 방식별

제8장 세계의 통신 분야 인공지능(AI) 시장 : 기업 규모별

제9장 세계의 통신 분야 인공지능(AI) 시장 : 지역별

제10장 경쟁 구도

제11장 기업 개요

영문목차

The Artificial Intelligence in Telecommunication Market size is expected to reach USD 12.09 Billion in 2034 from USD 2.12 Billion (2025) growing at a CAGR of 21.32% during 2026-2034.

The artificial intelligence in telecommunication market is poised for remarkable growth as telecom operators seek to enhance operational efficiency and improve customer experiences. With the increasing complexity of network management and the demand for personalized services, AI technologies are becoming indispensable tools for telecom companies. By leveraging machine learning algorithms and data analytics, operators can optimize network performance, predict maintenance needs, and automate routine tasks. This not only reduces operational costs but also enables telecom providers to deliver seamless connectivity and superior service quality to their customers.

Furthermore, the integration of AI in telecommunications is revolutionizing customer service through the deployment of chatbots and virtual assistants. These AI-driven solutions are capable of handling a wide range of customer inquiries, providing instant support and freeing up human agents to focus on more complex issues. As customer expectations continue to rise, the ability to offer 24/7 support and personalized interactions will be a key differentiator for telecom companies. The ongoing advancements in natural language processing and sentiment analysis are further enhancing the effectiveness of AI in understanding and responding to customer needs.

Additionally, the emergence of 5G technology is creating new opportunities for AI applications within the telecommunications sector. The high-speed, low-latency capabilities of 5G networks enable real-time data processing and analytics, allowing telecom operators to implement AI solutions that enhance network management and service delivery. As the demand for IoT connectivity and smart devices grows, the role of AI in optimizing network resources and ensuring reliable service will become increasingly critical. The artificial intelligence in telecommunication market is thus positioned for significant expansion, driven by the need for innovation and efficiency in an ever-evolving digital landscape.

Our reports are meticulously crafted to provide clients with comprehensive and actionable insights into various industries and markets. Each report encompasses several critical components to ensure a thorough understanding of the market landscape:

Market Overview: A detailed introduction to the market, including definitions, classifications, and an overview of the industry's current state.

Market Dynamics: In-depth analysis of key drivers, restraints, opportunities, and challenges influencing market growth. This section examines factors such as technological advancements, regulatory changes, and emerging trends.

Segmentation Analysis: Breakdown of the market into distinct segments based on criteria like product type, application, end-user, and geography. This analysis highlights the performance and potential of each segment.

Competitive Landscape: Comprehensive assessment of major market players, including their market share, product portfolio, strategic initiatives, and financial performance. This section provides insights into the competitive dynamics and key strategies adopted by leading companies.

Market Forecast: Projections of market size and growth trends over a specified period, based on historical data and current market conditions. This includes quantitative analyses and graphical representations to illustrate future market trajectories.

Regional Analysis: Evaluation of market performance across different geographical regions, identifying key markets and regional trends. This helps in understanding regional market dynamics and opportunities.

Emerging Trends and Opportunities: Identification of current and emerging market trends, technological innovations, and potential areas for investment. This section offers insights into future market developments and growth prospects.

MARKET SEGMENTATION

By Component

• Solutions
• Services

By Technology

• Machine Learning
• Natural Language Processing
• Computer Vision
• Others

By Application

• Network Optimization
• Customer Analytics
• Virtual Assistants
• Fraud Detection
• Others

By Deployment Mode

• On-Premises
• Cloud

By Enterprise Size

• Small and Medium Enterprises
• Large Enterprises

COMPANIES PROFILED

• IBM Corporation, Microsoft Corporation, Google LLC, Amazon Web Services Inc, Nokia Corporation, Huawei Technologies Co Ltd, Cisco Systems Inc, Ericsson AB, Intel Corporation, Qualcomm Technologies Inc, ATT Inc, Verizon Communications Inc, Samsung Electronics Co Ltd, Oracle Corporation, Accenture plc

We can customise the report as per your requriements

TABLE OF CONTENTS

Chapter 1. PREFACE

• 1.1. Market Segmentation & Scope
• 1.2. Market Definition
• 1.3. Information Procurement
  • 1.3.1 Information Analysis
  • 1.3.2 Market Formulation & Data Visualization
  • 1.3.3 Data Validation & Publishing
• 1.4. Research Scope and Assumptions
  • 1.4.1 List of Data Sources

Chapter 2. EXECUTIVE SUMMARY

• 2.1. Market Snapshot
• 2.2. Segmental Outlook
• 2.3. Competitive Outlook

Chapter 3. MARKET VARIABLES, TRENDS, FRAMEWORK

• 3.1. Market Lineage Outlook
• 3.2. Penetration & Growth Prospect Mapping
• 3.3. Value Chain Analysis
• 3.4. Regulatory Framework
  • 3.4.1 Standards & Compliance
  • 3.4.2 Regulatory Impact Analysis
• 3.5. Market Dynamics
  • 3.5.1 Market Drivers
  • 3.5.2 Market Restraints
  • 3.5.3 Market Opportunities
  • 3.5.4 Market Challenges
• 3.6. Porter's Five Forces Analysis
• 3.7. PESTLE Analysis

Chapter 4. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY COMPONENT 2022-2034 (USD MN)

• 4.1. Market Analysis, Insights and Forecast Component
• 4.2. Solutions Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 4.3. Services Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 5. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY TECHNOLOGY 2022-2034 (USD MN)

• 5.1. Market Analysis, Insights and Forecast Technology
• 5.2. Machine Learning Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.3. Natural Language Processing Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.4. Computer Vision Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 5.5. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 6. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY APPLICATION 2022-2034 (USD MN)

• 6.1. Market Analysis, Insights and Forecast Application
• 6.2. Network Optimization Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.3. Customer Analytics Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.4. Virtual Assistants Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.5. Fraud Detection Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 6.6. Others Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 7. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY DEPLOYMENT MODE 2022-2034 (USD MN)

• 7.1. Market Analysis, Insights and Forecast Deployment Mode
• 7.2. On-Premises Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 7.3. Cloud Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 8. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY ENTERPRISE SIZE 2022-2034 (USD MN)

• 8.1. Market Analysis, Insights and Forecast Enterprise Size
• 8.2. Small and Medium Enterprises Estimates and Forecasts By Regions 2022-2034 (USD MN)
• 8.3. Large Enterprises Estimates and Forecasts By Regions 2022-2034 (USD MN)

Chapter 9. GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION MARKET: BY REGION 2022-2034(USD MN)

• 9.1. Regional Outlook
• 9.2. North America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.2.1 By Component
  • 9.2.2 By Technology
  • 9.2.3 By Application
  • 9.2.4 By Deployment Mode
  • 9.2.5 By Enterprise Size
  • 9.2.6 United States
  • 9.2.7 Canada
  • 9.2.8 Mexico
• 9.3. Europe Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.3.1 By Component
  • 9.3.2 By Technology
  • 9.3.3 By Application
  • 9.3.4 By Deployment Mode
  • 9.3.5 By Enterprise Size
  • 9.3.6 United Kingdom
  • 9.3.7 France
  • 9.3.8 Germany
  • 9.3.9 Italy
  • 9.3.10 Russia
  • 9.3.11 Rest Of Europe
• 9.4. Asia-Pacific Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.4.1 By Component
  • 9.4.2 By Technology
  • 9.4.3 By Application
  • 9.4.4 By Deployment Mode
  • 9.4.5 By Enterprise Size
  • 9.4.6 India
  • 9.4.7 Japan
  • 9.4.8 South Korea
  • 9.4.9 Australia
  • 9.4.10 South East Asia
  • 9.4.11 Rest Of Asia Pacific
• 9.5. Latin America Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.5.1 By Component
  • 9.5.2 By Technology
  • 9.5.3 By Application
  • 9.5.4 By Deployment Mode
  • 9.5.5 By Enterprise Size
  • 9.5.6 Brazil
  • 9.5.7 Argentina
  • 9.5.8 Peru
  • 9.5.9 Chile
  • 9.5.10 South East Asia
  • 9.5.11 Rest of Latin America
• 9.6. Middle East & Africa Market Analysis, Insights and Forecast, 2022-2034 (USD MN)
  • 9.6.1 By Component
  • 9.6.2 By Technology
  • 9.6.3 By Application
  • 9.6.4 By Deployment Mode
  • 9.6.5 By Enterprise Size
  • 9.6.6 Saudi Arabia
  • 9.6.7 UAE
  • 9.6.8 Israel
  • 9.6.9 South Africa
  • 9.6.10 Rest of the Middle East And Africa

Chapter 10. COMPETITIVE LANDSCAPE

• 10.1. Recent Developments
• 10.2. Company Categorization
• 10.3. Supply Chain & Channel Partners (based on availability)
• 10.4. Market Share & Positioning Analysis (based on availability)
• 10.5. Vendor Landscape (based on availability)
• 10.6. Strategy Mapping

Chapter 11. COMPANY PROFILES OF GLOBAL ARTIFICIAL INTELLIGENCE IN TELECOMMUNICATION INDUSTRY

• 11.1. Top Companies Market Share Analysis
• 11.2. Company Profiles
  • 11.2.1 IBM Corporation
  • 11.2.2 Microsoft Corporation
  • 11.2.3 Google LLC
  • 11.2.4 Amazon Web Services Inc
  • 11.2.5 Nokia Corporation
  • 11.2.6 Huawei Technologies Co. Ltd
  • 11.2.7 Cisco Systems Inc
  • 11.2.8 Ericsson AB
  • 11.2.9 Intel Corporation
  • 11.2.10 Qualcomm Technologies Inc
  • 11.2.11 AT&T Inc
  • 11.2.12 Verizon Communications Inc
  • 11.2.13 Samsung Electronics Co. Ltd
  • 11.2.14 Oracle Corporation
  • 11.2.15 Accenture Plc