Inteligencia Artificial aplicada a la eficiencia logística y exportación de la agroindustria: Revisión sistemática y análisis bibliométrico

Nayelly Alvarado-Varas; Karla Zavaleta-Guzmán

doi:10.17268/agroind.sci.2026.01.07

Autores/as

Nayelly Alvarado-Varas Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo. Trujillo, Perú. https://orcid.org/0009-0002-4634-5349
Karla Zavaleta-Guzmán Facultad de Ciencias Agropecuarias, Universidad Nacional de Trujillo. Trujillo, Perú. https://orcid.org/0000-0001-9993-3510

DOI:

https://doi.org/10.17268/agroind.sci.2026.01.07

Palabras clave:

IA, logística, exportaciones, alimento, cienciometría, bibliometría

Resumen

El presente estudio analiza cómo la Inteligencia Artificial está transformando la eficiencia logística y las exportaciones en la agroindustria. Mediante una revisión sistemática de literatura científica (2020–2025) y un análisis bibliométrico con datos de Scopus, se identifican tecnologías como Machine Learning, Deep Learning, IoT y blockchain, las cuales están mejorando la trazabilidad, predicción de demanda y sostenibilidad en la cadena agroalimentaria. Los resultados muestran que países como China, India y Estados Unidos lideran la producción científica en este campo, mientras que regiones como Sudamérica enfrentan limitaciones por falta de infraestructura tecnológica. Las aplicaciones de inteligencia artificial abarcan desde monitoreo en tiempo real y control de calidad, hasta la predicción de cultivos y reducción de pérdidas. El estudio concluye que la inteligencia artificial fortalece la competitividad del sector agroindustrial en mercados internacionales. Se recomienda a los países en desarrollo invertir en infraestructura digital, promover la investigación local y capacitar al personal para cerrar brechas tecnológicas.

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