通訊業中AI的地位

本報告提供通訊業的AI地位調查，AI技術概要，通訊領域中AI引進的推動因素，通訊業者的AI策略的案例研究等資訊。

目錄

第1章 摘要整理

第2章 AI技術概要

• AI，機器學習，深層學習定義
• 主要的AI為基礎的技術與用途
• AI的價值鏈

第3章 通訊領域的AI的推進因素

• 通訊領域的主要課題
• 通訊領域的AI引進的推進因素
• 通訊領域的AI引進的推進因素- 5G及目標的演變
• 通訊領域的AI引進的推進因素- AI為基礎的用途
• 通訊領域的AI引進的推進因素- 電腦網路傳統的安全模式
• 通訊領域的AI引進的推進因素- 有效的網路管理
• 通訊領域的AI引進的推進因素- 收益增加，成本的削減

第4章 通訊業者的AI策略:案例研究

• Orange
• Telefonica
• Deutsche Telekom
• AT&T
• China Mobile

Summary

Artificial Intelligence (AI) is one of the most disruptive technologies of this decade and has the potential to transform every aspect of our society, including vertical industries. Telecom operators are transforming themselves into AI companies, starting with the automation of their network operations.

This report focuses on several key questions:

• What are the different concepts of AI , including machine learning, deep learning and generative AI?

• What are the key components of AI, and what is the AI value chain?

• How do telecom operators position themselves in the AI value chain?

• What are the drivers for telecom operators to adopt AI?

• What are the AI strategies of the major telecom operators?

Table of Contents

1. Executive summary

2. Overview of AI technologies

• 2.1. Definition of artificial intelligence, machine learning and deep learning
• 2.2. Key AI-based technologies and applications
• 2.3. Artificial intelligence value chain

3. Drivers of artificial intelligence in the telecom sector

• 3.1. Key challenges for the telecoms sector
• 3.2. Drivers of AI adoption in telecommunications
• 3.3. Drivers of AI adoption in telecoms - Evolution to 5G and beyond
• 3.4. Drivers of AI adoption in telecoms - AI-based applications
• 3.5. Drivers of AI adoption in telecoms - Increasing sophistication of cyber-attacks
• 3.6. Drivers of AI adoption in telecoms - Effective network management
• 3.7. Drivers of AI adoption in telecoms - Revenue growth, cost reduction

4. Telco AI strategy case studies

• 4.1. Orange
• 4.2. Telefonica
• 4.3. Deutsche Telekom
• 4.4. AT&T
• 4.5. China Mobile