INDEX

Artificial Intelligence Platforms for Telecom Networks

The use of Artificial Intelligence (AI) and machine learning in telecom network is skyrocketing with several use cases becoming increasingly popular: customer segmentation, service assurance, chatbots, customer services and many more. These are usually deployed and used in isolation in a single department, addressing a specific pain point.

On the other hand, there are AI platforms being developed that aim to be used in a broader context by many departments. These platforms are still in infancy but aim to create ecosystems where mobile service providers can utilize their own workforce as well as external developers to create AI applications.

This report covers the AI platform market, specifically targeted towards telecom networks. Initial use cases are outlined, and key operators are profiled with respect to their AI platform activities. Open source and industry initiatives are also covered, where several operators are waiting for them to mature before formulating a company-wide AI strategy.

 

Table of Contents

  • 1. EXECUTIVE SUMMARY
    • 1.1. Conclusions and Recommendations
  • 2. INTRODUCTION
    • 2.1. Need for AI in Telcos
  • 3. AI FRAMEWORK
  • 4. AI IMPLEMENTATION PREREQUISITES
    • 4.1. Stakeholder Buy-in and ROI
    • 4.2. Predictability and Human Input
    • 4.3. Data Lake
    • 4.4. Cultural Shift and Talent
    • 4.5. Network Programmability
  • 5. DEPLOYMENT STRATEGIES
    • 5.1. Stages of Implementation
    • 5.2. Centralized and Distributed AI Platforms
  • 6. CASE STUDIES
    • 6.1. AT&T
    • 6.2. British Telecom
    • 6.3. Deutsche Telekom
    • 6.4. NTT DOCOMO
    • 6.5. Telef√≥nica
  • 7. INDUSTRY ACTIVITIES
    • 7.1. Telco Associations
    • 7.2. Open-Source Activities