Impacto de la IA para la toma de decisiones estratégicas en una agencia de carga: Una revisión sistemática
Impact of AI on strategic decision-making in a freight forwarding agency: A systematic reviewContenido principal del artículo
La creciente complejidad y volatilidad del comercio global exigen que las agencias de carga internacional incorporen tecnologías avanzadas para optimizar la toma de decisiones. Este estudio presenta una revisión sistemática de la literatura cuyo objetivo fue determinar el impacto de la inteligencia artificial (IA) en dicho proceso dentro del sector. La investigación se desarrolló siguiendo los lineamientos PRISMA, mediante una búsqueda en Scopus, Web of Science y SciELO, analizándose 40 artículos relacionados con eficiencia operacional, resiliencia estratégica y gobernanza de la cadena de suministro. Los resultados evidencian que la IA actúa como un habilitador estratégico que trasciende la automatización, al optimizar la planificación de redes, el ruteo y la gestión documental, con reducciones de hasta el 30% en distancias logísticas. Asimismo, fortalece la resiliencia organizacional mediante gemelos digitales y análisis de riesgo objetivo. No obstante, su implementación enfrenta desafíos vinculados a la explicabilidad, la calidad de los datos y la capacitación del personal. En conclusión, la IA constituye un factor clave de diferenciación competitiva, siempre que se integre con gobernanza ética y gestión estratégica del capital humano.
The growing complexity and volatility of global trade require international freight agencies to incorporate advanced technologies to optimize decision-making processes. This study presents a systematic literature review aimed at determining the impact of artificial intelligence (AI) on decision-making within the sector. The research followed PRISMA guidelines and involved a comprehensive search of Scopus, Web of Science, and SciELO, analyzing 40 articles related to operational efficiency, strategic resilience, and supply chain governance. The results show that AI acts as a strategic enabler that goes beyond automation by optimizing network planning, routing, and document management, achieving reductions of up to 30% in logistics distances. Furthermore, AI strengthens organizational resilience through digital twins and objective risk analysis. However, its implementation faces challenges related to explainability, data quality, and workforce training. In conclusion, AI represents a key factor for competitive differentiation, provided it is integrated with ethical governance and strategic human capital management.
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Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., y Verma, S. (2024). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: An empirical investigation. Annals of Operations Research, 333(2-3), 627-652. https://doi.org/10.1007/s10479-021-03956-x
Bermúdez, L., Anaya, D., y Belles-Sampera, J. (2025). Leveraging xAI for enhanced surrender risk management in life insurance products. European Research on Management and Business Economics, 31(3), 100286. https://doi.org/10.1016/j.iedeen.2025.100286
Bilad, A., Zaim, M., y Zaim, F. (2025). Empirical Modeling of the Impact of Industry 4.0 Technologies on Logistics Service Quality. Logforum, 21(3), 443-457. https://doi.org/10.17270/J.LOG.001249
Boy, M., Osorio, D., Rodríguez, R., y López, P. (2024). Inteligencia artificial en la toma de decisiones: Implicaciones éticas y eficiencia. Revista Venezolana de Gerencia, 29(Especial 11), 342-355. https://doi.org/10.52080/rvgluz.29.e11.20
Caldera, J. (2025). Aplicaciones de la Inteligencia Artificial para automatización de procesos documentales en los archivos audiovisuales televisivos. Revista Interamericana de Bibliotecología, 48(1). https://doi.org/10.17533/udea.rib.v48n1e356060
Chakrabarti, M., Fabozzi, F. J., Narain, A., y Sood, A. (2025). Ethical AI in Asset Management: Frameworks for Transparency, Compliance, and Trust. The Journal of Financial Data Science, 7(1), 18-35. https://doi.org/10.3905/jfds.2025.7.1.018
Chavaglia, J., y António, J. (2024). Innovation and Entrepreneurship: The Role of Prospect Theory in Decision-Making. En L. Aldieri (Ed.), Business, Management and Economics (Vol. 17). IntechOpen. https://doi.org/10.5772/intechopen.111396
Chen, C., Chung, E., y Correa, N. (2023). Inteligencia Artificial y su Impacto en la Industria de la Ingeniería. REICIT, 3(1), 26-40. https://doi.org/10.48204/reict.v3n1.3948
Córdova, E. C., Hernández, W. G., Quevedo, A. M., Darwinparism@Gmail.Com, y Sánchez, I. T. (2023). La inteligencia artificial y automatización en la toma de decisiones gerenciales. Open Science Framework. https://doi.org/10.31219/osf.io/cmnwh
De La Torrez, J., Ramírez, A., y Romero, J. R. (2023). Artificial intelligence to automate the systematic review of scientific literature. Computing, 105(10), 2171-2194. https://doi.org/10.1007/s00607-023-01181-x
Dinçer, H., Yüksel, S., Mikhaylov, A., y Ivanyuk, V. (2025). An integrated analysis for digital financial assets and artificial intelligence-based financial management using AI-based neuro quantum picture fuzzy rough sets and econometric modeling. Financial Innovation, 11(1), 122. https://doi.org/10.1186/s40854-025-00793-w
Dwivedi, Y. K. (2025). Generative Artificial Intelligence (GenAI) in entrepreneurial education and practice: Emerging insights, the GAIN Framework, and research agenda. International Entrepreneurship and Management Journal, 21(1), 82. https://doi.org/10.1007/s11365-025-01089-2
Faris, A., y Elhachloufi, M. (2025). Artificial Intelligence and Machine Learning Models for Credit Risk Prediction in Morocco. Statistics, Optimization y Information Computing, 14(4), 1716-1740. https://doi.org/10.19139/soic-2310-5070-2486
Feng, P., Bi, Z., Wen, Y., Pan, X., Peng, B., Liu, M., Xu, J., Chen, K., Liu, J., Yin, C. H., Zhang, S., Wang, J., Niu, Q., Li, M., y Wang, T. (2024). Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI’s Potential Through Tools, Techniques, and Applications (Versión 2). arXiv. https://doi.org/10.48550/ARXIV.2410.01268
Forero, W., y Negre, F. (2023). Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: Una revisión sistemática. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 209-253. https://doi.org/10.5944/ried.27.1.37491
Hadi Al, M., Al Ghurabli, Z., Raafat, R., y Aburayya, A. (2025). Enhancing Logistical Efficiency in Public Institutions through AI: A Managerial Framework for Regulatory and Technological Integration. International Journal of Industrial Engineering y Production Research, 36(3). https://doi.org/10.22068/ijiepr.36.3.2459
He, S., Zhang, M., Wang, S., y Huang, G. Q. (2025). Channel structures and subscription strategies for AI-driven logistics data products. European Journal of Operational Research, 326(3), 597-614. https://doi.org/10.1016/j.ejor.2025.04.003
Hosseini, S. J. (2025). Reverse logistics and lean, agile, resilient, and green paradigms in supply chain: A comparative analysis of fuzzy decision-making methods. Cleaner Logistics and Supply Chain, 17, 100284. https://doi.org/10.1016/j.clscn.2025.100284
Ivanov, D. (2025). Conceptual and formal models for design, adaptation, and control of digital twins in supply chain ecosystems. Omega, 137, 103356. https://doi.org/10.1016/j.omega.2025.103356
Jaime, R. (2025). Algoritmos Predictivos y la Tecnología Blockchain en la Distribución Musical: Ecosistema Más Justo y Eficiente. Ciencia Latina Revista Científica Multidisciplinar, 9(1), 11913-11940. https://doi.org/10.37811/cl_rcm.v9i1.16765
Karbovska, L., Kalina, I., Voroshnov, S., Mazur, Y., Zhelezniak, K., y Kozlova, A. (2025). Increasing the role of military logistics in the context of growing geopolitical instability based on strategic management. Technology audit and production reserves, 4(4(84)), 24-29. https://doi.org/10.15587/2706-5448.2025.336198
Koliousis, I., Al-Surmi, A., y Bashiri, M. (2024). Artificial intelligence and policy making; can small municipalities enable digital transformation? International Journal of Production Economics, 274, 109324. https://doi.org/10.1016/j.ijpe.2024.109324
Kyriakopoulos, N., Kim, E., Hultink, E. J., y Santema, S. (2025). The impact of design thinking and artificial intelligence capabilities on performance: The role of new product development decision-making agility. Journal of Business Research, 200, 115633. https://doi.org/10.1016/j.jbusres.2025.115633
Lin, K. (2025). Generative artificial intelligence–driven sustainable supply chain management: A UNISONE framework for smart logistics and predictive analytics under Industry 5.0. International Journal of Logistics Research and Applications, 1-32. https://doi.org/10.1080/13675567.2025.2540855
Lv, J., Rani, S., y Li, K. (2025). Intelligent multi-level network optimization for medical logistics in underground transportation systems: A computational intelligence approach. Computers y Industrial Engineering, 209, 111451. https://doi.org/10.1016/j.cie.2025.111451
Mahajan, A., Singh, G., Devgan, S., Singh, G., y Kaur, P. (2026). Next-generation manufacturing: Leveraging AI for industrial innovation and growth. Computers & Industrial Engineering, 211, 111618. https://doi.org/10.1016/j.cie.2025.111618
Malhotra, G., y Kharub, M. (2025). Elevating logistics performance: Harnessing the power of artificial intelligence in e-commerce. The International Journal of Logistics Management, 36(1), 290-321. https://doi.org/10.1108/IJLM-01-2024-0046
Matoni, M., Kesper, A., y Taentzer, G. (2025). How to Define the Quality of Data? A Feature-Based Literature Survey (Versión 1). arXiv. https://doi.org/10.48550/ARXIV.2504.01491
Mizrak, A. Prof. F., y Cantürk, A. Prof. S. (2025). Strategic multi-criteria assessment for cold chain logistics optimization in the aviation sector. Research in Transportation Business & Management, 63, 101500. https://doi.org/10.1016/j.rtbm.2025.101500
Nascimento, P. V. M., De Siqueira, P. B. B., Chrispim, N., Chaves, R. M., Barbosa, C. E., y De Souza, J. M. (2025). The future of AI in government services and global risks: Insights from design fictions. European Journal of Futures Research, 13(1), 9. https://doi.org/10.1186/s40309-025-00253-9
Oliveira, C. de, Bueno, N., Lima, A., De Araújo, S. A., Belan, P. A., Carvalho, D., y Almeida, C. M. V. B. (2025). Artificial intelligence-based optimization of the WEEE reverse chain in São Paulo − Brazil to promote economic, environmental and social benefits. Journal of Cleaner Production, 521, 146073. https://doi.org/10.1016/j.jclepro.2025.146073
Palomino, F., García, F., García, E., García, A., Pacherres, E., Villar, L., Castro, L., Choque, L., Zapana, D., y Guanilo, E. (2023). Quantitative Evaluation of the Impact of Artificial Intelligence on the Automation of Processes. Data and Metadata, 2, 101. https://doi.org/10.56294/dm2023101
Pantiris, P., Pallis, P. L., Chountalas, P. T., y Dasaklis, T. K. (2025). Enhancing Coordination and Decision Making in Humanitarian Logistics Through Artificial Intelligence: A Grounded Theory Approach. Logistics, 9(3), 113. https://doi.org/10.3390/logistics9030113
Pei, R., Chen, M., y Liu, Z. (2025). Identifying Key Digital Enablers for Urban Carbon Reduction: A Strategy-Focused Study of AI, Big Data, and Blockchain Technologies. Systems, 13(8), 646. https://doi.org/10.3390/systems13080646
Puyol, L. (2024). Factores determinantes en la toma de decisiones estratégicas en el sector retail. Revista Científica Zambos, 3(1), 36-55. https://doi.org/10.69484/rcz/v3/n1/11
Rastogi, S., y Pandita, D. (2025). Driving entrepreneurial success: Navigating AI-driven transformation through workforce agility and sustainability. Journal of Innovation and Entrepreneurship, 14(1), 75. https://doi.org/10.1186/s13731-025-00554-0
Sánchez, E., Hurtado, M., Valverde, G., y Mucha, C. (2023). Toma de decisiones organizacionales en el contexto de la pandemia. Horizontes. Revista de Investigación en Ciencias de la Educación, 7(27), 229-238. https://doi.org/10.33996/revistahorizontes.v7i27.509
Tamás, P. (2025). New Dimensions in the Study of Outsourcing Logistics Services: The Role of Digitalization in Enhancing Efficiency. Logistics, 9(2), 44. https://doi.org/10.3390/logistics9020044
Vanegas, A., Tarazona, M., y Rodríguez, A. (2020). Mejora de la toma de decisiones en ciclo de ventas del subsistema comercial de servicios en una empresa de IT. Revista Científica, 38(2), 174-183. https://doi.org/10.14483/23448350.15241
Vera, P., y Pico, P. (2024). Inteligencia artificial en el desarrollo administrativo de la empresa moderna. Revista Científica Arbitrada Multidisciplinaria PENTACIENCIAS, 6(2), 264-282. https://doi.org/10.59169/pentaciencias.v6i2.1046
Yin, F., Lo, M. C., Mohamad, A. A., y Sin, K. Y. (2025). The impact of AI applications, information sharing, and supply chain resilience on agricultural supply chain performance. Journal of Data, Information and Management, 7(4), 287-300. https://doi.org/10.1007/s42488-025-00155-2
Zogaan, W. A., Ajabnoor, N., y Salamai, A. A. (2025). Leveraging deep learning for risk prediction and resilience in supply chains: Insights from critical industries. Journal of Big Data, 12(1), 94. https://doi.org/10.1186/s40537-025-01143-4
Zúñiga, F., Mora, A., y Molina, P. (2023). La importancia de la inteligencia artificial en las comunicaciones en los procesos marketing. Vivat Academia. Revista de Comunicación, 19-39. https://doi.org/10.15178/va.2023.156.e1474