Influencia de la Inteligencia Artificial en el Desempeño Organizacional de Empresas Industriales

Luciana  Valenzuela Fourage; Daniela  Fernández García

doi:10.21803/ingecana.6.6.1072

Autores/as

Luciana Valenzuela Fourage Universidad de Lima https://orcid.org/0009-0008-1580-2117
Daniela Fernández García Universidad de Lima https://orcid.org/0009-0002-4233-4562

DOI:

https://doi.org/10.21803/ingecana.6.6.1072

Palabras clave:

Inteligencia artificial, desempeño organizacional, transformación digital, productividad

Resumen

Introducción: Este estudio presenta una revisión sistemática de la literatura (PRISMA) publicada entre 2020 y 2025 sobre el impacto de la inteligencia artificial (IA) en el desempeño organizacional de empresas industriales. Objetivos: A partir de búsquedas en Scopus y Web of Science, con filtros por áreas afines a gestión, ingeniería y ciencias sociales, idiomas y acceso abierto, se conformó un corpus reciente y multidisciplinario. Metodología: Los análisis bibliométricos evidencian un auge 2023–2024 y una alta transversalidad temática. En el plano sustantivo, la IA opera como catalizador de la transformación organizacional al reconfigurar estructuras y procesos, optimizar la toma de decisiones basada en datos y elevar la productividad, eficiencia y sostenibilidad. Revisión: La evidencia también muestra efectos en resiliencia y aprendizaje organizacional mediante automatización, analítica avanzada y métricas inteligentes. No obstante, el impacto positivo depende de condiciones habilitadoras: liderazgo ético, cultura de innovación, gobierno de datos, y desarrollo de capacidades ante la resistencia al cambio. La IA generativa y la inteligencia híbrida amplifican la creatividad y el rendimiento de los equipos, complementando, no sustituyendo, al trabajo humano. Conclusiones: En conjunto, los hallazgos validan que la IA incide de manera significativa y sostenida en la transformación y el desempeño empresarial cuando se integra estratégicamente con el talento humano y marcos de adopción responsables.

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Referencias

[1] M. Tariq, M. Poulin, and A. Abonamah, "Achieving Operational Excellence Through Artificial Intelligence: Driving Forces and Barriers"; Frontiers in Psychology, vol. 12, pp. 1–15, 2021.

[2] A. Zebec and M. Indihar Štemberger, "Creating AI business value through BPM capabilities,"; Business Process Management Journal, vol. 30, no. 8, pp. 1–26, 2024.

[3] R. G. Cooper, ";SMEs’ use of AI for new product development: Adoption rates by application and readiness-toadopt"; Industrial Marketing Management, vol. 126, pp. 159–167, 2025.

[4] Y. Luo, Z. Yang, Y. Ren, M. Škare, and Y. Qin,"Evaluating the Impact of AI Research on Industry Productivity: A Dynamic Qualitative Comparative Analysis Approach-Web of Science Core Collection"; Journal of Competitiveness, vol. 16, no. 3, pp. 187–203, 2024.

[5] C. Ya-Ting, H. L. Chiang, and A. P. L. An-Pan, "Insights from the Job Demands–Resources Model: AI’s dual impact on employees’ work and life well-being"; International Journal of Information Management, vol. 83, pp. 1–17, 2025.

[6] M. Wu, D. C. Kozanoglu, C. Min, and Y. Zhang, "Unraveling the capabilities that enable digital transformation: A data- driven methodology and the case of artificial intelligence", Advanced Engineering Informatics, vol. 50, p. 101368, 2021.

[7] N. Florea and G. Croitoru, "The Impact of Artificial Intelligence on Communication Dynamics and Performance in Organizational Leadership"; Administrative Sciences, vol. 15, no. 2, pp. 1–33, 2025.

[8] V. A. Barcelos and A. M. dos Santos, "Transformação digital e seguro: uma revisão sistemática da literatura"; Revista de Gestão e Secretariado, vol. 14, no. 6, pp. 8849–8874, 2023.

[9] O. Rodríguez-Espíndola, S. Chowdhury, P. K. Dey, P. Albores, and A. Emrouznejad, "Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing" Technological Forecasting and Social Change, vol. 178, p. 121562, 2022.

[10] C. M. Rosca, G. Rădulescu, and A. Stancu, "Artificial Intelligence of Things Infrastructure for Quality Control in Cast Manufacturing Environments Shedding Light on Industry Changes"; Applied Sciences, vol. 15, no. 4, pp.

1–30, 2025.

[11] H. Aly,"Digital transformation, development and productivity in developing countries: is artificial intelligence a curse or a blessing?"; Review of Economics and Political Science, vol. 7, no. 4, pp. 238–256, 2022.

[12] F. Bertani, L. Ponta, M. Raberto, A. Teglio, and S. Cincotti, "The complexity of the intangible digital economy: an agent-based model,"; Journal of Business Research, vol. 129, pp. 527–540, 2021.

[13] S. Chatterjee, N. P. Rana, Y. K. Dwivedi, and A. M. Baabdullah, "Understanding AI adoption in manufacturing and production firms using an integrated TAM-TOE model,"; Technological Forecasting and Social Change, vol. 170, p. 120880, 2021.

[14] F. Han, X. Zhang, K. Chan, and Y. Li, "Firms’ digital transformation and management earnings forecasts: Evidence from China", Borsa Istanbul Review, vol. 23, no. 6, pp. 1356–1366, 2023.

[15] C. F. A. Arranz, M. F. Arroyabe, N. Arranz, and J. C. F. de Arroyabe, "Digitalisation dynamics in SMEs: An approach from systems dynamics and artificial intelligence";Technological Forecasting and Social Change, vol. 196, p.

122880, 2023.

[16] J. Gao, Z. Li, T. Nguyen, and W. Zhang"Digital transformation and enterprise employment"; International Review of Economics & Finance, vol. 99, pp. 1–13, 2025.

[17] A. Przegalinska, T. Triantoro, A. Kovbasiuk, L. Ciechanowski, R. B. Freeman, and K. Sowa, "Collaborative AI in the workplace: Enhancing organizational performance through resource-based and task-technology fit perspective",

International Journal of Information Management, vol. 81, pp. 1–23, 2025.

[18] A. Tursunbayeva and H. Chalutz-Ben Gal, "Adoption of artificial intelligence: A TOP framework-based checklist for digital leaders," Business Horizons, vol. 67, no. 4, pp. 357–368, 2024.

[19] A. Kumar, A. Shankar, A. Behl, V. Pereira, P. Kapoor, and A. Papa,"Implementing enterprise metaverse as a means of enhancing growth hacking performance: Will adopting the metaverse be a success in organizations?"; Journal of Business Research, vol. 188, p. 115079, 2025.

[20] P. Karácsony, Z. Metzker, T. Vasic, and J. P. Koltai, "Employee Attitude to Organisational Change in Small and Medium-Sized Enterprises";M Economics and Management, vol. 26, no. 1, pp. 94–110, 2023.

[21] A. Amayreh, M. A. Ta’Amnha, I. K. Magableh, M. H. Mahrouq, and S. A. Alfaiza, "Exploring the impact of AI on employee self-competence performance key variables and outcomes"; Discover Sustainability, vol. 6, no. 1, pp. 1–23,

2025.

[22] S. P. Klein, P. Spieth, and M. Söllner,"Employee acceptance of digital transformation strategies: A paradox perspective"; Journal of Product Innovation Management, vol. 41, no. 5, pp. 999–1021, 2024.

[23] S. Strazzullo, "Fostering digital trust in manufacturing companies: Exploring the impact of industry 4.0 technologies"; Journal of Innovation: Knowledge, vol. 9, no. 4, p. 100621, 2024.

[24] C. H. Lee, L. Li, F. Li, and C. H. Chen,"Requirement-driven evolution and strategy-enabled service design for new customized quick-response product order fulfillment process",Technological Forecasting and Social Change, vol.

176, p. 121464, 2022.

[25] L. Marioni, A. Rincon-Aznar, and F. Venturini, "Productivity performance, distance to frontier and AI innovation: Firm-level evidence from Europe" Journal of Economic Behavior and Organization, vol. 228, pp. 1–25, 2024.

[26] J. M. Spreitzenbarth, C. Bode, and H. Stuckenschmidt, "Artificial intelligence and machine learning in purchasing and supply management: A mixed-methods review of the state-of-the-art in literature and practice"; Journal of

Purchasing and Supply Management, vol. 30, no. 1, p.100896, 2024.

[27] J. Holm, D. Hain, R. Jurowetzki, and E. Lorenz,"Innovation dynamics in the age of artificial intelligence: introduction to the special issue"; Industry and Innovation, vol. 30, no. 9, pp. 1141–1155, 2023.

[28] F. Qu, Q. Tang, C. Li, and J. Liu, "Exploring the impact of digital transformation on productivity: the role of artificial intelligence technology, green technology, and energy technology"; Technological and Economic Development of Economy, pp. 1–32, 2025.

[29]F. Qu, Q. Tang, C. Li, and J. Liu, “Exploring the impact of digital transformation on productivity: the role of artificial intelligence technology, green technology, and energy technology,” Technological and Economic Development of Economy, pp. 1–32, 2025.

[30] F. A. Fierro Celis, “Fuentes de financiación: factores de análisis en la toma de decisiones”, Adm. Desarro., vol. 52, no. 1, pp. 35–54, Jun. 2022, doi: 10.22431/25005227.vol52n1.3.

[31] W. E. Cifuentes Martínez and C. Duarte Vega, “Creación de valor público desde la perspectiva de los stakeholders. Una revisión semisistemática de literatura”, Adm. Desarro., vol. 53, no. 1, pp. 1–39, Jun. 2023, doi: 10.22431/25005227.vol53n1.10

[32] L. A. Velásquez Castro y J. A. Paredes-Águila, «Revisión sistemática sobre los desafíos que enfrenta el desarrollo e integración de las tecnologías digitales en el contexto escolar chileno, desde la docencia», Región Científica, vol. 3, n.º 1, p. 2024226, ene. 2024.