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市場調查報告書
商品編碼
1630587

2024 年通訊服務供應商的人工智慧成長機會

Growth Opportunities for Telecommunications Service Providers in Artificial Intelligence, 2024
出版日期: | 出版商: Frost & Sullivan | 英文 60 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

人工智慧驅動的創新創造了新的收益來源、業務效率和客戶價值

人工智慧是指模仿人類智慧並透過自學能力協助決策的技術。機器學習 (ML) 是人工智慧的一個子領域，專注於模仿人類的學習方式，涉及開發和使用無需遵循明確指令即可學習和適應的演算法。

電信業者已成為採購人工智慧技術的重要通路合作夥伴。通訊業者憑藉與企業密切合作建立解決方案、提供專業服務和託管服務以及整合基於人工智慧的工具和平台的能力，正在成為生態系統中的重要參與者。

所有主要通訊業者都已開始部署人工智慧技術，但成熟度處於不同階段，從概念驗證到多種人工智慧使用案例的大規模部署。人工智慧的採用需要明確的策略和藍圖。很少有通訊業者擁有支援統一企業資料池（包含從即時來源收集的資料）的架構，這表明缺乏支援人工智慧應用的資料準備。這導致為 GenAI 應用訓練 AI 模型變得困難且 AI 結果不佳。

報告確定了通訊業者領域新興的人工智慧使用案例、橫向業務功能、市場促進因素以及影響人工智慧市場的限制因素。這也為通訊業者探索特定產業的人工智慧解決方案和資料管理提供了機會。

Frost＆Sullivan 對各個地區的知名通訊業者進行了深入的初步採訪，以製定競爭概況並了解相關的人工智慧發展、策略和價值提案。此外，還從內部資料庫以及財務報告、行業協會、統計機構和專業網站等公開資訊來源進行了二次研究。

目錄

戰略問題

  • 成長為何變得越來越艱難？
  • The Strategic Imperative 8（TM）
  • 三大策略要務對通訊服務供應商（電信公司）人工智慧應用的影響

成長機會分析

  • 分析範圍
  • 調查方法與流程
  • 主要競爭對手
  • 成長動力
  • 成長抑制因素
  • 人工智慧市場通訊業者領域的人工智慧應用：各有不同但相互關聯
  • 通訊業者採用人工智慧：利用基於人工智慧的模型改善企業決策
  • 通訊業者採用人工智慧：用途和影響
  • 通訊業者AI 應用：投資
  • 利用人工智慧創造新的收益來源：通訊業者從連結服務轉向資訊服務
  • 利用人工智慧創造新收益：通訊業者的新經營模式
  • 利用人工智慧創造新的收益來源：GenAI 和 Edge AI
  • 應用人工智慧創造新收益源：企業對企業 (B2B) 領域的使用案例
  • 應用人工智慧創造新收益源：通訊業者的全新 B2B 產品組合
  • 利用人工智慧創造新收益來源：各行業主要通訊業者使用案例
  • 利用人工智慧創造新的收益來源通訊業者的網路營運管理
  • 利用人工智慧創造新收益來源：通訊業者的網路營運管理通訊業者的客戶體驗管理

公司簡介

  • 比較頂級人工智慧舉措
  • SK Telecom：人工智慧的主要發展
  • SK Telecom：2022 年及以後的全球 AI 公司定位
  • KT 公司：AI 專注於領域
  • KT Corporation：為 2024 年及以後的 AICT 公司定位
  • Telefonica：認知平台的建構模組
  • 西班牙電信：AI 重點關注領域
  • 西班牙電信：人工智慧實施計畫將於 2024 年啟動
  • 沃達豐：人工智慧的關鍵發展
  • 沃達豐：多供應商 AI 架構將於 2024 年發布
  • Verizon：AI 重點關注領域
  • Verizon：2024 年 AI 策略公佈
  • AT&T 關鍵 AI 發展
  • AT&T 的主要 AI 重點領域

成長機會宇宙

  • 成長機會一：人工智慧專業服務
  • 成長機會二：人工智慧產業解決方案
  • 成長機會三：對話平台
  • 成長機會#4：自主網路

後續步驟Next steps

  • 成長機會的好處和影響
  • 行動項目和後續步驟
  • 附件列表
  • 免責聲明
簡介目錄
Product Code: KB33-67

AI-powered Innovation Unlocks New Revenue Streams, Operational Efficiency, and Customer Value

AI refers to technologies that emulate human intelligence and assist decision-making with self-learning capabilities. Machine learning (ML) is a sub-field of AI that focuses on imitating how humans learn and includes the development and use of algorithms that can learn and adapt without following explicit instructions.

Telcos have emerged as essential channel partners for procuring AI technology. Their ability to work closely with enterprises to build solutions, offer professional and managed services, and integrate AI-based tools and platforms make them crucial ecosystem participants.

All major telcos have started implementing AI technology; however, they are at different stages of maturity-from proofs of concept to deploying multiple AI use cases in scale. A clear strategy and roadmap articulation are critical in AI adoption. Few telcos have architectures that support integrated enterprise data pools, including data gathered from real-time sources, indicating low data readiness to support AI applications. This results in difficulty training AI models for GenAI applications and ineffective AI outcomes.

This report highlights emerging AI use cases across telcos and horizontal business functions, drivers, and restraints impacting the AI market. It also offers telcos opportunities to explore industry-specific AI solutions and data management.

Frost & Sullivan conducted detailed primary interviews with telcos that stand out in different regions to generate a competitive profile and understand relevant AI developments, strategies, and value propositions. In addition, we performed extensive secondary research across our internal database and other public information sources, such as financial reports, industry associations, statistic agencies, and specialized websites.

Table of Contents

Strategic Imperatives

  • Why is it Increasingly Difficult to Grow?
  • The Strategic Imperative 8™
  • The Impact of the Top 3 Strategic Imperatives on AI's Applications for Telecommunications Service Providers (Telcos)

Growth Opportunity Analysis

  • Scope of Analysis
  • Research Process and Methodology
  • Key Competitors
  • Growth Drivers
  • Growth Restraints
  • AI Adoption in Telcos' Segments of the AI Market: Distinct yet Interrelated
  • AI Adoption in Telcos: Enterprise Decision-making Evolution with AI-based Models
  • AI Adoption in Telcos: Utilization and Impact
  • AI Adoption in Telcos: Investment
  • Applying AI to Generate New Revenue Streams: Telcos Shift from Connectivity to Data Services
  • Applying AI to Generate New Revenue Streams: Telcos' New Business Models
  • Applying AI to Generate New Revenue Streams: GenAI and Edge AI
  • Applying AI to Generate New Revenue Streams: Use Cases in the Business-to-Business (B2B) Segment
  • Applying AI to Generate New Revenue Streams: New B2B Portfolio for Telcos
  • Applying AI to Generate New Revenue Streams: Key AI Vertical Use Cases for Telcos
  • Applying AI to Generate New Revenue Streams: Network Operations Management for Telcos
  • Applying AI to Generate New Revenue Streams: Customer Experience Management for Telcos

Company Profiles

  • Comparison of Top AI Initiatives
  • SK Telecom: Key AI Developments
  • SK Telecom: Global AI Company's Positioning Since 2022
  • KT Corporation: Key AI Focus Areas
  • KT Corporation: AICT Company's Positioning Since 2024
  • Telefonica: Building Blocks for a Cognitive Platform
  • Telefonica: Key AI Focus Areas
  • Telefonica: AI Adoption Program That Launched in 2024
  • Vodafone: Key AI Developments
  • Vodafone: Multivendor AI Architecture That Released in 2024
  • Verizon: Key AI Focus Areas
  • Verizon: AI Strategy That Released in 2024
  • AT&T: Key AI Developments
  • AT&T: Key AI Focus Areas

Growth Opportunity Universe

  • Growth Opportunity 1: AI Professional Services
  • Growth Opportunity 2: AI Industry Vertical Solutions
  • Growth Opportunity 3: Conversational Platforms
  • Growth Opportunity 4: Autonomous Networks

Next Steps

  • Benefits and Impacts of Growth Opportunities
  • Action Items & Next Steps
  • List of Exhibits
  • Legal Disclaimer