Aplicación de la inteligencia artificial en la administración de empresas: Desafíos y oportunidades

Authors

DOI:

https://doi.org/10.62452/57rdaf30

Keywords:

Artificial Intelligence, business management, automation, predictive analytics, digital transformation

Abstract

Artificial Intelligence (AI) is revolutionizing business administration by enabling process optimization, task automation and improved strategic decision making. Its implementation in different business domains has demonstrated significant benefits in terms of operational efficiency and competitiveness. This article examines how AI is transforming business management, highlighting its applications in automation, predictive analytics and customer service personalization. It also explores the challenges companies face in adopting these technologies, including resistance to change, implementation costs, and ethical implications. Finally, key strategies and recommendations for effective integration of AI into business management are presented.

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Author Biographies

  • Byron Oviedo-Bayas, Universidad Técnica Estatal de Quevedo. Ecuador.

     

     

     

  • Cristian Zambrano-Vega, Universidad Técnica Estatal de Quevedo. Ecuador.

     

     

  • Leyda Zavala-Arteaga, Universidad Bolivariana. Ecuador.

     

     

References

Accenture. (2021). The future of AI in customer experience. Accenture Insights.

Brynjolfsson, E., & McAfee, A. (2017). Machine, platform, crowd: Harnessing our digital future. Norton & Company.

Bughin, J., Hazan, E., Ramaswamy, S., Allas, T., Dahlstrom, P., Henke, N., & Trench, M. (2017). Artificial Intelligence: The Next Digital Frontier? McKinsey Global Institute.

Chui, M., Manyika, J., & Miremadi, M. (2021). The state of AI in business applications. McKinsey Global Institute.

Davenport, T., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116. https://www.bizjournals.com/boston/news/2018/01/09/hbr-artificial-intelligence-for-the-real-world.html

Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://hdsr.mitpress.mit.edu/pub/l0jsh9d1/release/8

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. https://www.nature.com/articles/s42256-019-0088-2

Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, 80(6), 69-96. https://journals.sagepub.com/doi/10.1509/jm.15.0420

McKinsey & Company. (2022). The impact of automation on administrative processes. McKinsey Insights.

Russell, S., & Norvig, P. (2021). Artificial intelligence: A modern approach. Pearson.

Sharda, R., Delen, D., & Turban, E. (2020). Analytics, data science, & artificial intelligence: Systems for decision support. Pearson.

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Published

2025-04-01

How to Cite

Oviedo-Bayas, B. ., Zambrano-Vega, C. ., Zavala-Arteaga, L. ., & Zúñiga-Delgado, M. S. . (2025). Aplicación de la inteligencia artificial en la administración de empresas: Desafíos y oportunidades. Revista Metropolitana De Ciencias Aplicadas, 8(2), 172-176. https://doi.org/10.62452/57rdaf30