AI Use Cases for Telcos: Networks & Operations, Products & Services, and Customer Interactions

AI Use Cases for Telcos: Networks & Operations, Products & Services, and Customer Interactions

Summary

AI is driving telecom operators’ digital transformation. It’s set of available technologies including machine learning (ML), deep learning, computer vision, context-aware computing, robotics, predictive modelling, and conversational platforms have the potential to shift the economic paradigms for telcos at an unprecedented pace. Agility, cost efficiency, and accuracy are now transforming telco business models towards the digital data-driven platform model, in a race to achieve market responsiveness, drive innovation, and new revenue streams. Artificial intelligence (AI) along with its set of available technologies will be the cornerstone powering internal and external digital transformation for telcos.

Telcos need to augment their products and services with AI for more personalization and on-demand flexibility. AI is key to helping telcos optimize their networks and automate their network operations. The report “AI Use Cases for Telcos: Networks & Operations, Products & Services, and Customer Interactions” deep dives into the possible use cases that AI makes available for telcom operators to turn into smart digital service providers & produce value.

The report is structured as follows -

  • Taxonomy & Market Context; offers an overview of the key AI definitions, technologies, and value chain.
  • Telecoms AI Use Cases; maps out the telecoms AI application areas. It then offers a series of examples of telcos’ AI implementations in networks & operations, products & services, and customer interactions & knowledge.
  • Case Studies; offers two telco case studies focusing on AI for predictive industrial maintenance and autonomous telecom networks. It analyzes the partnerships involved, the service features, and the benefits generated.
  • Findings and recommendations; we conclude the report with a set of key findings and recommendations for telecom operators to help them harness the benefits of AI and drive new revenue streams.
Furthermore, the report outlines a multitude of AI use cases in several consumer and corporate areas possible for telcos. The four key areas identified in the report which AI can help telcos transform to more agile, intelligence-driven and customer-focused digital players: (1) networks optimization & operations automation - e.g., predictive maintenance and network operations automation; (2) AI-powered products and services - e.g., cyberdefense and SD-WAN; (3) smart customer interactions and knowledge - e.g., AI personal assistants; and (4) potential new revenue streams - e.g., chatbots as a service.

The report AI Use Cases for Telcos: Networks & Operations, Products & Services, and Customer Interactions, helps inform global industry executives' decision-making process on the possible use cases of AI in their telecom businesses, as well as of the possible service and commercial positioning strategies.

Companies mentioned: Alibaba, Google, QTnet, Amazon, Huawei, Servicefriend, AT&T, IBM, Softbank, China Telecom, Korea Telecom, South Korea Telecom, Ciena, Kyivstar Ukraine, Swisscom, ELM Leblanc, Magic Leap, Telefonica, Ericsson, Microsoft, T-Mobile, Etisalat, MTN, T-Systems, Facebook, Nanosemantika, Verizon, Flyxt, NBN, Vodafone, Globe Philippines, Nokia, Google, Ooredoo, Huawei, Orange Business Services, IBM, P.I. Works.

Scope
  • Telcos need to augment their products and services with AI for more personalization and on-demand flexibility.
  • AI is key to helping telcos optimize their networks and automate their network operations.
  • Telco customer interaction touchpoints & channels are also benefitting from AI.
Reasons to buy
  • The report objective is to help inform global industry executives' decision-making process on the possible use cases of AI in their telecom businesses, as well as of the possible service and commercial positioning strategies.
  • Two case studies illustrate the findings of the report, providing insights into telecom operators' AI implementations, the partnerships they harnessed and the benefits they generated; this will help industry executives understand the drivers and benefits AI can create for them as well as the business & partnership models telcos can adopt to get access and deploy AI capabilities.
  • The report also provide a reminder of the key AI definitions, technologies, and value chain. This will help telcos better understand the ecosystem, play an active role in it and monetize the opportunity arising from the AI space.
  • With nine exhibits, the report is designed for an executive-level audience, to help them understand and determine the adequate evolution moves for their AI strategies.


Executive Summary
Section 1: Taxonomy & Market Context
Defining AI
AI technologies overview
AI value chain - overview
Section 2: Telecoms' AI Use Cases
Telecoms’ AI use cases overview
Telecoms' AI use cases - network optimization & operations automation
Telecoms' AI use cases - AI-powered products & services
Telecoms' AI use cases - smart customer interactions & knowledge
Section 3: Case Studies
AI for offering predictive maintenance
AI for autonomous & self-driving networks
Section 4: Key Findings & Recommendations
Appendix
Acronyms and definitions
Companies mentioned
Related research
Contact information
List of Figures
Exhibit 1: AI definitions and key technologies
Exhibit 2: AI technologies’ application examples
Exhibit 3: AI value chain components
Exhibit 4: Sample AI application use cases in telecoms
Exhibit 5: Sample AI use cases in telco network optimization & operations automation
Exhibit 6: Sample AI use cases in telco AI-powered products & services
Exhibit 7: Sample AI use cases in telco smart customer interactions & knowledge
Exhibit 8: OBS IoT platform for predictive maintenance - ELM Leblanc boilers predictive maintenance use case
Exhibit 9: Wavelogic Ai monitors optical link data to enable capacity decision automation

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