Artificial intelligence and efficiency in agricultural production costs: a bibliometric study

Authors

DOI:

https://doi.org/10.31908/19098367.3299

Keywords:

Precision agriculture, Agricultural production , costs, Cost efficiency, Artificial intelligence

Abstract

Artificial intelligence applied to agricultural production has become an increasingly relevant topic in recent scientific literature, particularly because of its connection with efficiency, resource management, and the reduction of operating costs. Even so, existing studies are still distributed across technical, productive, and economic approaches, which makes it difficult to understand how this research field has actually taken shape. Based on this gap, the objective of this article was to analyze the evolution of scientific production on artificial intelligence and efficiency in agricultural production costs through a bibliometric study of documents indexed in Scopus between 2015 and 2026. To do so, performance indicators and science mapping techniques were used to identify publication trends, influential sources, author productivity, thematic structures, and emerging research lines. The results show a growing field, marked by high levels of collaboration, thematic dispersion, and an increasing orientation toward precision agriculture, data-driven decision making, and cost reduction. The main contribution of the study lies in organizing a fragmented body of literature and identifying the conceptual cores that are currently guiding academic discussion. It is concluded that artificial intelligence does not operate only as a technological support tool, but as an articulating axis between productive management, input optimization, and economic sustainability in agriculture.

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Author Biographies

  • Angélica Jiménez Coronado, Universidad del Atlántico

    Profesora de la Facultad de Ciencias Económicas de la Universidad del Atlántico. Ingeniera de Sistemas, especialista en Redes de Computadores, magíster en Administración de Empresas y doctora en Administración. Investigadora Asociada (IA) reconocida por Minciencias. Sus áreas de interés se relacionan con administración, sistemas de información, gestión organizacional y aplicación de tecnologías digitales en procesos productivos.

    ORCID: https://orcid.org/0000-0002-5067-1721.

  • Hugo Gaspar Hernández Palma, Universidad del Atlántico

    Profesor de planta de la Universidad del Atlántico, adscrito a la Facultad de Ciencias Económicas y al Programa de Administración de Empresas. Ingeniero Industrial, especialista en Diseño y Evaluación de Proyectos, magíster en Sistemas de Gestión y doctorando en Gerencia de Proyectos. Sus líneas de trabajo se relacionan con gestión organizacional, proyectos, productividad, calidad y sistemas de gestión aplicados al sector empresarial.

    ORCID: https://orcid.org/0000-0002-3873-0530.

  • Daniel Alfonso Mendoza Casseres, Universidad del Atlántico

    Profesor asociado del Programa de Ingeniería Industrial de la Universidad del Atlántico, Barranquilla, Colombia. Ingeniero Químico de la Universidad del Atlántico y magíster en Ingeniería Industrial de la Universidad de Los Andes. Su experiencia académica e investigativa se ha orientado hacia procesos industriales, gestión de operaciones, productividad y análisis aplicado a sistemas de producción.

    ORCID: https://orcid.org/0000-0001-5514-750X

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Published

2026-06-30

Issue

Vol. 20 No. 39 (2026)

Section

Artículos

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Copyright (c) 2026 Angelica Jiménez Coronado, Hugo Gaspar hernandez palma, Daniel Alfonso Mendoza Casseres

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

[1]
A. Jiménez Coronado, H. G. Hernández Palma, and D. A. Mendoza Casseres, “Artificial intelligence and efficiency in agricultural production costs: a bibliometric study”, Entre cienc. ing., vol. 20, no. 39, pp. 41–49, Jun. 2026, doi: 10.31908/19098367.3299.
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