Leads Management Applying Artificial Intelligence to Optimize Business Processes in a Metallurgical Company: A Systematic Literature Review

Ramirez R.O.S.; Mandujano B.Y.V.; Pucuhuayla-Revatta F.; Zamora Mondragón J. · Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology (2025) · DOI: 10.18687/leird2025.1.1.659

Resumen

Digital transformation through Artificial Intelligence (AI) tools represents a key opportunity to optimize business processes, especially in small and medium-sized companies in the metallurgical sector. This systematic literature review aims to analyze how AI-supported lead management can improve sales efficiency and customer experience. The PRISMA methodology was used to select 441 scientific articles, indexed in reliable databases such as Scopus, published between May 2022 and May 2025. The reviewed studies show that the implementation of virtual assistants, automatic lead classification systems, and predictive models increases lead conversion, reduces response time, and enables more precise segmentation. Barriers such as low technological adoption in SMEs and the need for digital training are also identified. The results support that the integration of AI into sales management not only improves productivity but also adds value to customer service processes. The conclusion is that AI is an accessible and adaptable solution that enables metalworking companies to optimize their sales strategies, facilitating data-driven decision-making and promoting operational innovation. © LEIRD 2025.All rights reserved.

Instituciones: Universidad Tecnológica del Perú