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The intelligent chatbot for customer service in Telecommunications companies (#577)

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Date of Conference

July 16-18, 2025

Published In

"Engineering, Artificial Intelligence, and Sustainable Technologies in service of society"

Location of Conference

Mexico

Authors

Mauricio Cruz, Yerssin Leandro

Sanchez Mato, Josue Antonio

Navas Gotopo, Soratna Veronica

Ramirez Calderón, Luis Enrique

Abstract

The objective of this systematic literature review (RSL) is to evaluate the impact of the implementation of intelligent chatbots compared to traditional customer service methods in telecommunications companies, analyzing its influence on customer satisfaction, resolution efficiency of problems and reduction of operating costs. An exhaustive search was carried out in academic databases and research repositories, following the guidelines of the PRISMA method. Studies published between 2019 and 2024 were included, addressing the use of chatbots in customer services in relevant sectors, with a focus on specific performance metrics and user perception. The selected articles were evaluated for relevance, methodological quality and contribution to the topic. The results highlight that chatbots improve operational efficiency by reducing response times and resolving common queries without human intervention, Furthermore, personalizing interactions and using anthropomorphic communication styles increases customer satisfaction. However, limitations related to privacy and acceptance have been identified, particularly in interactions involving sensitive data. From an economic perspective, chatbots have proven to be effective in reducing operational costs, especially in small and medium-sized companies. In conclusion, intelligent chatbots represent an innovative and efficient solution for customer service in the telecommunications sector. However, its success depends on user-centered design, personalization of interactions, and proper privacy management. These findings can guide companies in implementing technology strategies that balance operational efficiency and customer experience

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