Large Language Models for Telecom: Forthcoming Impact on the Industry

Ali Maatouk, Nicola Piovesan, Fadhel Ayed, Antonio De Domenico, Merouane Debbah

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Large language models (LLMs) – AI-driven models that can achieve general-purpose language understanding and generation – have emerged as a transformative force, revolutionizing fields well beyond natural language processing (NLP) and garnering unprecedented attention. As LLM technology continues to progress, the telecom industry is facing the prospect of its impact on the landscape. To elucidate these implications, we delve into the inner workings of LLMs, providing insights into their current capabilities and limitations. We also examine the use cases that can be readily implemented in the telecom industry, streamlining tasks, such as anomaly resolution and technical specification comprehension, which currently hinder operational efficiency and demand significant manpower and expertise. Furthermore, we uncover essential research directions that deal with the distinctive challenges of utilizing the LLMs within the telecom domain. Addressing them represents a significant stride toward fully harnessing the potential of LLMs, and unlocking their capabilities to the fullest extent within the telecom domain.

Original languageBritish English
Pages (from-to)62-68
Number of pages7
JournalIEEE Communications Magazine
Volume63
Issue number1
DOIs
StatePublished - 2025

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