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市場調查報告書

通訊部門AI:網路營運監測&管理、顧客服務&行銷用VDA、智慧型CRM系統、客戶經驗管理、網路安全、詐欺降低

Artificial Intelligence for Telecommunications Applications: Network Operations Monitoring/Management, Customer Service/Marketing VDAs, Intelligent CRM Systems, CEM, Cybersecurity, Fraud Mitigation, Other - Global Market Analysis and Forecasts

出版商 Tractica 商品編碼 630464
出版日期 內容資訊 英文 55 Pages; 19 Tables, Charts & Figures
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通訊部門AI:網路營運監測&管理、顧客服務&行銷用VDA、智慧型CRM系統、客戶經驗管理、網路安全、詐欺降低 Artificial Intelligence for Telecommunications Applications: Network Operations Monitoring/Management, Customer Service/Marketing VDAs, Intelligent CRM Systems, CEM, Cybersecurity, Fraud Mitigation, Other - Global Market Analysis and Forecasts
出版日期: 2019年09月05日內容資訊: 英文 55 Pages; 19 Tables, Charts & Figures
簡介

本報告提供通訊部門AI的市場調查,市場及技術定義和概要,市場成長的促進因素及課題分析,通訊部門的各種利用案例,技術趨勢,主要加入企業的簡介,各種硬體設備、軟體、業務收益的變化與預測,總論,各種建議等彙整資料。

第1章 摘要整理

第2章 市場分析

  • 簡介
  • 市場成長的促進因素
  • 市場障礙

第3章 利用案例

  • 簡介
  • 網路營運監測&管理
    • Apstra
    • EnterpriseWeb
    • Aria Networks
    • Huawei
    • Juniper Networks
    • Nokia
  • 預知保全
  • 詐欺降低
  • 網路安全
    • Darktrace
  • 顧客服務&行銷用虛擬數位助理
    • 市場成長的促進因素
    • Creative Virtual
    • Nuance
  • 智慧型CRM系統
    • Automation Anywhere
    • CallidusCloud (SAP)
    • Conversica
  • 客戶經驗管理的改善
    • DeviceBits
    • Guavus (Thales)
  • Sandvine

第4章 技術分析

  • 簡介
  • AI定義
  • 機器學習
  • 深度學習
  • 機器學習、深度學習的差異
  • 結構化資料 vs 非結構型資料
  • 教師螞蟻學習 vs 沒有教師學習
  • 自然語言處理
  • 自然地語言生成
  • 硬體設備基礎設施
    • 硬體設備相關考察:晶片組、電力、效能
    • 伺服器環境
    • 雲端基礎設施
    • 巨量資料AI用途:技術課題

第5章 主要企業

  • 簡介
  • Amdocs
  • Apstra
  • Aria Networks
  • AT&T
  • Automation Anywhere
  • CallidusCloud
  • Conversica
  • Creative Virtual
  • Darktrace
  • DeviceBits
  • EnterpriseWeb
  • Ericsson
  • Guavus
  • Huawei
  • Juniper Networks
  • Nokia
  • Nuance
  • Sandvine

第6章 市場預測

  • 預測手法
  • 通訊部門AI軟體的收益
    • 各利用案例
    • 各地區
    • 總收益:各種類
  • 通訊部門AI服務的收益
    • 引進服務
    • 培訓
    • 客製化服務
    • 應用整合服務
    • 支援、維護服務
    • 雲端服務
  • 通訊部門AI相關硬體設備的收益
    • GPU
    • CPU、ASIC、FPGA
    • 網路產品
    • 儲存裝置
  • 總論、建議

第7章 企業目錄

第8章 用語、簡稱

第9章 目錄

第10章 圖表

第11章 調查範圍、資訊來源、調查手法、註記

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目錄
Product Code: AITEL-19

Telecommunications service providers face a handful of daunting market conditions. Around the globe, revenue and subscriber growth are flat. To combat profit erosion, most communications service providers (CSPs) are struggling through a process to become digital service providers more akin to web companies that offer rapidly evolving and highly customized services.

5G/Internet of Things (IoT) and digital transformation are initiatives that CSPs hope will drive top-line growth. While they pursue these, CSPs are under equal pressure to find ways to become more efficient and cut costs as a means to increase profitability. This is an industry ripe for artificial intelligence (AI)-driven solutions. Telecom operators have begun to experiment and deploy AI-driven solutions that leverage fast, scalable interpretation, analytics, and prediction to provide top-line revenue or reduce costs. According to Tractica's analysis, telecom AI software revenue is expected to grow from $419.0 million in 2018 to more than $11.2 billion in 2025.

This Tractica report details the major market drivers and barriers, technologies, key players, and forecasts related to eight telecom AI use cases. These include network operations monitoring and management; predictive maintenance; fraud mitigation; cybersecurity; customer service and marketing virtual digital assistants (VDAs); intelligent customer relationship management (CRM) systems; customer experience management (CEM)/service delivery; and video compression. The technologies covered include machine learning (ML), deep learning (DL), and natural language processing (NLP). Global software market forecasts for telecom AI, segmented by region, use case, and meta category, extend through 2025.

Key Questions Addressed:

  • What is the current state of the market for telecom AI and how will it develop over the next decade?
  • What use cases will drive greater telecom AI adoption around the globe?
  • What are the key drivers of market growth and the major challenges faced by telecom AI in each world region?
  • Which companies are the major players in the market, what is their competitive positioning, and which are poised for the greatest success in the years ahead?
  • What is the size of the global telecom AI market opportunity?

Who Needs This Report?

  • Telecom network operators
  • Telecom hardware and software providers
  • AI hardware and software companies
  • Network operations solutions providers
  • Customer experience-focused solutions providers
  • Cybersecurity and fraud management solutions providers
  • Government agencies
  • Investor community

Table of Contents

1. Executive Summary

  • 1.1. Introduction
  • 1.2. Market Drivers
  • 1.3. Market Barriers
  • 1.4. Use Cases
  • 1.5. Market Forecast Highlights
  • 1.6. Conclusions and Recommendations

2. Market Issues

  • 2.1. Introduction
  • 2.2. Market Drivers
    • 2.2.1. Top-Line Revenue Growth
    • 2.2.2. World-Class Customer Experience and Service Delivery
    • 2.2.3. Bottom-Line Cost Savings
    • 2.2.4. Complexity of Service Offerings
    • 2.2.5. 5G Networks
  • 2.3. Market Barriers
    • 2.3.1. ROI
    • 2.3.2. Cross-Departmental Harmonization
    • 2.3.3. Challenging Abstraction Layers for Telecom Data
    • 2.3.4. Slow Rollout of Software-Defined Networks and Network Functions Virtualization
    • 2.3.5. Digital Transformation

3. Use Cases

  • 3.1. Introduction
  • 3.2. Network Operations Monitoring and Management
    • 3.2.1. Network Management and AI
  • 3.3. Predictive Maintenance
  • 3.4. Fraud Mitigation
  • 3.5. Cybersecurity
  • 3.6. Customer Service and Marketing VDAs
    • 3.6.1. VDA Market Drivers
    • 3.6.2. Telecom Leadership in VDAs
  • 3.7. Intelligent CRM Systems
  • 3.8. CEM/Service Delivery
  • 3.9. Video Compression

4. Technology Issues

  • 4.1. Introduction
  • 4.2. Definition of AI
  • 4.3. Machine Learning
  • 4.4. Deep Learning
  • 4.5. Natural Language Processing
    • 4.5.1. Importance of Machine and Deep Learning to NLP
    • 4.5.2. Natural Language Generation
  • 4.6. Hardware Infrastructure
    • 4.6.1. Hardware Considerations: Chipsets, Power, and Performance
    • 4.6.2. Big Data AI Applications: Technology Challenges
      • 4.6.2.1. Volume of Big Data
      • 4.6.2.2. High Variety of Data
      • 4.6.2.3. Data Velocity

5. Key Industry Players

  • 5.1. Introduction
  • 5.2. Amdocs
  • 5.3. Aria Networks
  • 5.4. CenturyLink
  • 5.5. Cisco
  • 5.6. DeviceBits
  • 5.7. Ericsson
  • 5.8. Guavus
  • 5.9. Huawei
  • 5.10. Juniper Networks
  • 5.11. Nokia
  • 5.12. Sandvine
  • 5.13. Telefónica
  • 5.14. Vodafone
  • 5.15. ZTE
  • 5.16. Additional Industry Participants

6. Market Forecasts

  • 6.1. Forecast Methodology
  • 6.2. Telecom AI Software Revenue
  • 6.3. Telecom AI Software Revenue by Use Case
  • 6.4. Telecom AI Software Revenue by Region
  • 6.5. Telecom AI Software Revenue by Meta Category
  • 6.6. Telecom AI Total Revenue by Segment
  • 6.7. Conclusions and Recommendations

7. Company Directory

8. Acronym and Abbreviation List

9. Table of Contents

10. Table of Charts and Figures

11. Scope of Study, Sources and Methodology, Notes

Tables

  • Telecom AI Software Revenue by Region, World Markets: 2018-2025
  • Telecom AI Total Revenue by Segment, World Markets: 2018-2025
  • Telecom AI Hardware Revenue by Region, World Markets: 2018-2025
  • Telecom AI Services Revenue by Region, World Markets: 2018-2025
  • Telecom AI Total Software, Services, and Hardware Revenue by Region, World Markets: 2018-2025
  • Telecom AI Software Revenue by Use Case, World Markets: 2018-2025
  • Telecom AI Software Revenue by Meta Category, World Markets: 2018-2025
  • Telecom AI Software Revenue by Meta Category Use Case, World Markets: 2018-2025
  • Additional Industry Participants

Charts

  • Telecom AI Software Revenue Share by Use Case, World Markets: 2025
  • Telecom AI Software Revenue by Region, World Markets: 2018-2025
  • Telecom AI Total Revenue by Segment, World Markets: 2018-2025
  • Telecom AI Software Revenue by Use Case, World Markets: 2018-2025
  • Telecom AI Software Revenue by Meta Category, World Markets: 2018-2025
  • Telecom AI Total Revenue by Segment, World Markets: 2018-2025

Figures

  • CSP Revenue Forecast
  • AI Encompasses Numerous Technologies
  • Schematic Representation of a Deep Neural Network
  • Progression of Natural Language Generation
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