Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Abstract
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions and user experiences, especially in the context of 6G systems. It highlights the development and deployment of Large Telecom Models (LTMs), which are tailored AI models designed to address the complex challenges faced by modern telecom networks. The paper covers a wide range of topics, from the architecture and deployment strategies of LTMs to their applications in network management, resource allocation, and optimization. It also explores the regulatory, ethical, and standardization considerations for LTMs, offering insights into their future integration into telecom infrastructure. The goal is to provide a comprehensive roadmap for the adoption of LTMs to enhance scalability, performance, and user-centric innovation in telecom networks.
Keywords
Cite
@article{arxiv.2503.04184,
title = {Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences},
author = {Adnan Shahid and Adrian Kliks and Ahmed Al-Tahmeesschi and Ahmed Elbakary and Alexandros Nikou and Ali Maatouk and Ali Mokh and Amirreza Kazemi and Antonio De Domenico and Athanasios Karapantelakis and Bo Cheng and Bo Yang and Bohao Wang and Carlo Fischione and Chao Zhang and Chaouki Ben Issaid and Chau Yuen and Chenghui Peng and Chongwen Huang and Christina Chaccour and Christo Kurisummoottil Thomas and Dheeraj Sharma and Dimitris Kalogiros and Dusit Niyato and Eli De Poorter and Elissa Mhanna and Emilio Calvanese Strinati and Faouzi Bader and Fathi Abdeldayem and Fei Wang and Fenghao Zhu and Gianluca Fontanesi and Giovanni Geraci and Haibo Zhou and Hakimeh Purmehdi and Hamed Ahmadi and Hang Zou and Hongyang Du and Hoon Lee and Howard H. Yang and Iacopo Poli and Igor Carron and Ilias Chatzistefanidis and Inkyu Lee and Ioannis Pitsiorlas and Jaron Fontaine and Jiajun Wu and Jie Zeng and Jinan Li and Jinane Karam and Johny Gemayel and Juan Deng and Julien Frison and Kaibin Huang and Kehai Qiu and Keith Ball and Kezhi Wang and Kun Guo and Leandros Tassiulas and Lecorve Gwenole and Liexiang Yue and Lina Bariah and Louis Powell and Marcin Dryjanski and Maria Amparo Canaveras Galdon and Marios Kountouris and Maryam Hafeez and Maxime Elkael and Mehdi Bennis and Mehdi Boudjelli and Meiling Dai and Merouane Debbah and Michele Polese and Mohamad Assaad and Mohamed Benzaghta and Mohammad Al Refai and Moussab Djerrab and Mubeen Syed and Muhammad Amir and Na Yan and Najla Alkaabi and Nan Li and Nassim Sehad and Navid Nikaein and Omar Hashash and Pawel Sroka and Qianqian Yang and Qiyang Zhao and Rasoul Nikbakht Silab and Rex Ying and Roberto Morabito and Rongpeng Li and Ryad Madi and Salah Eddine El Ayoubi and Salvatore D'Oro and Samson Lasaulce and Serveh Shalmashi and Sige Liu and Sihem Cherrared and Swarna Bindu Chetty and Swastika Dutta and Syed A. R. Zaidi and Tianjiao Chen and Timothy Murphy and Tommaso Melodia and Tony Q. S. Quek and Vishnu Ram and Walid Saad and Wassim Hamidouche and Weilong Chen and Xiaoou Liu and Xiaoxue Yu and Xijun Wang and Xingyu Shang and Xinquan Wang and Xuelin Cao and Yang Su and Yanping Liang and Yansha Deng and Yifan Yang and Yingping Cui and Yu Sun and Yuxuan Chen and Yvan Pointurier and Zeinab Nehme and Zeinab Nezami and Zhaohui Yang and Zhaoyang Zhang and Zhe Liu and Zhenyu Yang and Zhu Han and Zhuang Zhou and Zihan Chen and Zirui Chen and Zitao Shuai},
journal= {arXiv preprint arXiv:2503.04184},
year = {2025}
}