Telco AI: How to organise and partner for maximum success

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Our latest research shows that only one in five telco AI projects has made the leap from proof of concept (PoC) to live deployment. How can telcos improve the hit rate and achieve real performance improvements?


Format: PDF filePages: 30 pagesCharts: 10Author: Tilly GilbertPublication Date: June 2019

Table of Contents

  • Executive Summary
  • Not a passing fad: AI is becoming a core capability for telcos
  • What is artificial intelligence?
  • Cutting through the hype 8
  • Telcos’ current AI focus: Speed and efficiency
  • How are telcos using AI today?
  • Sharing is caring: How telco AI initiatives are organised
  • Centralised AI initiatives
  • Cross-functional R&D units
  • Individual AI initiatives
  • The stumbling blocks for AI implementation — and how to get around them
  • AI initiatives need to be powered by high-quality data
  • Data governance is an essential requirement
  • Exploring the link between data maturity and AI success
  • The tricky transition from the lab to in-field deployment
  • Accept failure and embrace innovation
  • Revamp partnership strategies
  • New challenges, new expectations
  • Finding the impact: How telcos assess the benefits of AI
  • Different types of telcos, different levels of AI maturity
  • Conclusion

Table of Figures

  • Figure 1: FigureMoving toward AI
  • Figure 2: Telco AI initiatives by domain
  • Figure 3: Centrally coordinated AI initiatives are more likely to scale
  • Figure 4: Poor data and a lack of internal skills are key challenges
  • Figure 5: Telcos struggle with data management at every step of the AI journey
  • Figure 6: Issues with data governance do not preclude AI implementation
  • Figure 7: Only 1 in 5 AI projects has advanced to live deployment
  • Figure 8: Collaborative partnering is key to AI success
  • Figure 9: Nearly half of telcos have not gone live with AI
  • Figure 10: Fixed-line and wholesale operators lag behind

Companies: AT&T, Cloudera, DataSpark, Telefonica, Vodafone

Keywords: AI, artificial intelligence, automation, centralisation, customer experience, Innovation, Machine Learning, network planning, organisational structure, partnering, Pilot, proof of concept, skills