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市场调查报告书

通讯部门AI:网路营运监测&管理、顾客服务&行销用VDA、智慧型CRM系统、客户经验管理、网路安全、诈欺降低

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 商品编码 630464
出版日期 内容资讯 英文 55 Pages; 19 Tables, Charts & Figures
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通讯部门AI:网路营运监测&管理、顾客服务&行销用VDA、智慧型CRM系统、客户经验管理、网路安全、诈欺降低 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日内容资讯: 英文 55 Pages; 19 Tables, Charts & Figures
简介

本报告提供通讯部门AI的市场调查,市场及技术定义和概要,市场成长的促进因素及课题分析,通讯部门的各种利用案例,技术趋势,主要加入企业的简介,各种硬体设备、软体、业务收益的变化与预测,总论,各种建议等汇整资料。

第1章 摘要整理

第2章 市场分析

  • 简介
  • 市场成长的促进因素
  • 市场障碍

第3章 利用案例

  • 简介
  • 网路营运监测&管理
    • Apstra
    • EnterpriseWeb
    • Aria Networks
    • Huawei
    • Juniper Networks
    • Nokia
  • 预知保全
  • 诈欺降低
  • 网路安全
    • Darktrace
  • 顾客服务&行销用虚拟数位助理
    • 市场成长的促进因素
    • Creative Virtual
    • Nuance
  • 智慧型CRM系统
    • Automation Anywhere
    • CallidusCloud (SAP)
    • Conversica
  • 客户经验管理的改善
    • DeviceBits
    • Guavus (Thales)
  • Sandvine

第4章 技术分析

  • 简介
  • AI定义
  • 机器学习
  • 深度学习
  • 机器学习、深度学习的差异
  • 结构化资料 vs 非结构型资料
  • 教师蚂蚁学习 vs 没有教师学习
  • 自然语言处理
  • 自然地语言生成
  • 硬体设备基础设施
    • 硬体设备相关考察:晶片组、电力、效能
    • 伺服器环境
    • 云端基础设施
    • 巨量资料AI用途:技术课题

第5章 主要企业

  • 简介
  • 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 市场预测

  • 预测手法
  • 通讯部门AI软体的收益
    • 各利用案例
    • 各地区
    • 总收益:各种类
  • 通讯部门AI服务的收益
    • 引进服务
    • 培训
    • 客制化服务
    • 应用整合服务
    • 支援、维护服务
    • 云端服务
  • 通讯部门AI相关硬体设备的收益
    • GPU
    • CPU、ASIC、FPGA
    • 网路产品
    • 储存装置
  • 总论、建议

第7章 企业目录

第8章 用语、简称

第9章 目录

第10章 图表

第11章 调查范围、资讯来源、调查手法、注记

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目录
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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