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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

Published by Tractica Product code 630464
Published Content info 55 Pages; 19 Tables, Charts & Figures
Delivery time: 1-2 business days
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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
Published: September 5, 2019 Content info: 55 Pages; 19 Tables, Charts & Figures
Description

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
Product Code: AITEL-19

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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