INTELIGÊNCIA ARTIFICIAL NA LOGÍSTICA

This article analyzes the applications of Artificial Intelligence (AI) in the logistics sector, highlighting the main areas where academic research connects the two themes. The objective is to understand how logistics is being impacted by AI through a bibliographic study that identifies key areas of focus. Using a search tool (Google Scholar), data were collected on the number of studies conducted in each of these areas. Subsequently, we present a brief description of the approaches adopted by the initial works found in each field. It was observed that topics such as customer service, demand forecasting, route optimization, inventory management, and preventive maintenance stand out in the application of AI in logistics. However, challenges such as integration with legacy systems, organizational culture, and information quality were also identified. These obstacles highlight the need for a more effective use of AI in the logistics context, indicating that there is still room for growth and further research.

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Publication Details

Journal
Revista Interface Tecnológica
Published
2025-09-17
DOI
https://doi.org/10.31510/infa.v21i2.2092
Primary Topic
Quality and Safety in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

INTELIGÊNCIA ARTIFICIAL NA LOGÍSTICA

Ronaldo Ribeiro de Campos, Carlos Eduardo Pereira Rocha
Revista Interface Tecnológica
Quality and Safety in Healthcare
article

INTELIGÊNCIA ARTIFICIAL NA LOGÍSTICA

Ronaldo Ribeiro de Campos, Carlos Eduardo Pereira Rocha
article en

Abstract

This article analyzes the applications of Artificial Intelligence (AI) in the logistics sector, highlighting the main areas where academic research connects the two themes. The objective is to understand how logistics is being impacted by AI through a bibliographic study that identifies key areas of focus. Using a search tool (Google Scholar), data were collected on the number of studies conducted in each of these areas. Subsequently, we present a brief description of the approaches adopted by the initial works found in each field. It was observed that topics such as customer service, demand forecasting, route optimization, inventory management, and preventive maintenance stand out in the application of AI in logistics. However, challenges such as integration with legacy systems, organizational culture, and information quality were also identified. These obstacles highlight the need for a more effective use of AI in the logistics context, indicating that there is still room for growth and further research.

Revista Interface TecnológicaVol. 21(2)
São Paulo State Technological College (BR)
Openalex Percentile: Top 54%
Quality and Safety in Healthcare
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