Autonomous enterprises: strategic decision-making powered by artificial intelligence in business administration

Authors

DOI:

https://doi.org/10.64183/pw7nw416

Keywords:

Cognitive Artificial Intelligence, Autonomous Enterprises, Strategic Decision-Making, Business Administration, Human-AI Collaboration

Abstract

This paper looks at the growth of autonomous companies, in which cognitive artificial intelligence (AI) technologies directly support strategic decision-making, planning, and forecasting. The study looks at how artificial intelligence integration affects decision speed, cost efficiency, and management satisfaction by means of a mixed-methods methodology spanning four Latin American companies in banking, logistics, technology, and services. Results indicate that management satisfaction remained high, especially when AI systems were visible and interpretable, decision-making agility increased by up to 42%, and cost savings reached 18%. But ethical issues including algorithmic opacity and over-automation were also noted, indicating the necessity of more robust control. The paper suggests a co-leadership approach in which people and artificial intelligence work together to make decisions. Real organizational value comes from integrating analytical intelligence with ethical responsibility; it does not come from automation by itself. This paper supports the creation of strategic, human-centered AI adoption frameworks by stressing that in a time motivated by smart systems, leadership has to stay anchored in human values.

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References

Abdurrahman, A. (2025). Examining the impact of digital transformation on digital product innovation performance in banking industry through the integration of resource-based view and dynamic capabilities. Journal of Strategy & Innovation, 36(1). https://doi.org/10.1016/j.jsinno.2025.200540

Acuña Acuña, E. G. (2023). Fortaleciendo la enseñanza de ingeniería en Educación Superior. Actualización docente en minería de datos, internet de las cosas y metaversos. Codes. https://doi.org/10.15443/codes2044

Acuña Acuña, E. G. (2024). Sustainable digital business management: Challenges and opportunities Proceedings of the 22nd LACCEI International Multi-Conference for Engineering, Education and Technology (LACCEI 2024): “Sustainable Engineering for a Diverse, Equitable, and Inclusive Future at the Service of Education, Research, and Industry for a Society 5.0.”. https://laccei.org/LACCEI2024-CostaRica/full-papers/Contribution_261_final_a.pdf

Acuña Acuña, E. G., Huertas Rosales, Á., & Vásquez Espinoza, S. (2024). Sistemas De Monitoreo Iot Para La Seguridad Laboral En Costa Rica. New Trends in Qualitative Research, 20(4). https://doi.org/10.36367/ntqr.20.4.2024.e1054

Acuña, E. G. A., Ferruzca, A. A., Rojas, J. M. C., Bayona, M. F. G., Soto, J. S. P., & Rojo Rojo, C. N. (2025). Optimization of Urban Mobility with IoT and Big Data: Technology for the Information and Knowledge Society in Industry 5.0. In S. Nesmachnow & L. Hernández Callejo, Smart Cities Cham.

Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities. Journal of Cleaner Production, 289. https://doi.org/10.1016/j.jclepro.2021.125834

Arranz, C. F. A., Arroyabe, M. F., Arranz, N., & de Arroyabe, J. C. F. (2023). Digitalisation dynamics in SMEs: An approach from systems dynamics and artificial intelligence. Technological Forecasting and Social Change, 196. https://doi.org/10.1016/j.techfore.2023.122880

Borges, A. F. S., Laurindo, F. J. B., Spínola, M. M., Gonçalves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2020.102225

Chaturvedi, V. (2025). A futuristic aspect towards modern healthcare system facilitated through artificial intelligence: A comprehensive perspective. In Revolutionizing Medical Systems using Artificial Intelligence (pp. 245-264). https://doi.org/10.1016/b978-0-443-32862-6.00013-4

Dahiya, R., Le, S., & Kroll, M. J. (2025). Big data analytics and firm performance: The effects of human capital and mediating firm capabilities. Journal of Strategy & Innovation, 36(1). https://doi.org/10.1016/j.jsinno.2025.200535

Garay Gallastegui, L. M., & Reier Forradellas, R. (2024). FASECO: A Framework for Advanced Support of E-Commerce and digital transformation in SMEs with natural language processing- enhanced analysis. Journal of Open Innovation: Technology, Market, and Complexity, 10(4). https://doi.org/10.1016/j.joitmc.2024.100412

Ji, L., & Huang, X. (2022). Analysis of social governance in energy-oriented cities based on artificial intelligence. Energy Reports, 8, 11151- 11160. https://doi.org/10.1016/j.egyr.2022.08.206

Kar, A. K., Choudhary, S. K., & Singh, V. K. (2022). How can artificial intelligence impact sustainability: A systematic literature review. Journal of Cleaner Production, 376. https://doi.org/10.1016/j.jclepro.2022.134120

Kuppuchamy, S. K., Srinivasan, S., Dhandapani, G., Nagaraj, S., Celin, J. A., & Subramanian, M. (2025). Journey of computational intelligence in sustainable computing and optimization techniques: An introduction. In Computational Intelligence in Sustainable Computing and Optimization (pp. 1-51). https://doi.org/10.1016/b978-0-443-23724-9.00001-3

Li, L. T., Haley, L. C., Boyd, A. K., & Bernstam, E. V. (2023). Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review. J Biomed Inform, 147, 104531. https://doi.org/10.1016/j.jbi.2023.104531

Miracle, D. B., & Thoma, D. J. (2024). Autonomous research and development of structural materials – An introduction and vision. Current Opinion in Solid State and Materials Science, 33. https://doi.org/10.1016/j.cossms.2024.101188

Mishra, R., Kr Singh, R., Daim, T. U., Fosso Wamba, S., & Song, M. (2024). Integrated usage of artificial intelligence, blockchain and the internet of things in logistics for decarbonization through paradox lens. Transportation Research Part E: Logistics and Transportation Review, 189. https://doi.org/10.1016/j.tre.2024.103684

Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4(1). https://doi.org/10.1016/j.jjimei.2023.100208

Shang, Y., Jiang, J., Zhang, R., Zhang, Y., Liu, P., & Yu, L. (2025). The mechanism of human-machine collaboration driving sustainable business models: A single case study from the electric vehicle industry. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2025.145152

Sumrit, D. (2024). Enhancing readiness degree for Industrial Internet of Things adoption in manufacturing enterprises: An integrated Pythagorean fuzzy approach. Heliyon, 10(20), e39007. https://doi.org/10.1016/j.heliyon.2024.e39007

Sun, Z., Che, S., & Wang, J. (2024). Deconstruct artificial intelligence’s productivity impact: A new technological insight. Technology in Society, 79. https://doi.org/10.1016/j.techsoc.2024.102752

Uctu, R., Tuluce, N. S. H., & Aykac, M. (2024). Creative destruction and artificial intelligence: The transformation of industries during the sixth wave. Journal of Economy and Technology, 2, 296-309. https://doi.org/10.1016/j.ject.2024.09.004

Valle-Cruz, D., Fernandez-Cortez, V., & Gil-Garcia, J. R. (2022). From E-budgeting to smart budgeting: Exploring the potential of artificial intelligence in government decision-making for resource allocation. Government Information Quarterly, 39(2). https://doi.org/10.1016/j.giq.2021.101644

Verbeke, A., Oh, C. H., & Jain, R. (2025). What is the future of regional multinational enterprises? International Business Review. https://doi.org/10.1016/j.ibusrev.2025.102442

Wang, S., & Zhang, H. (2025). Generative artificial intelligence and internationalization green innovation: Roles of supply chain innovations and AI regulation for SMEs. Technology in Society, 82. https://doi.org/10.1016/j.techsoc.2025.102898

Wang, X., Shi, X., Chen, J., Guo, X., & Li, D. (2024). Exploring optimal pathways for enterprise procurement management systems based on fast neural modeling and semantic segmentation. Heliyon, 10(7), e26474. https://doi.org/10.1016/j.heliyon.2024.e26474

Wu, L., Sun, L., Chang, Q., Zhang, D., & Qi, P. (2022). How do digitalization capabilities enable open innovation in manufacturing enterprises? A multiple case study based on resource integration perspective. Technological Forecasting and Social Change, 184. https://doi.org/10.1016/j.techfore.2022.122019

Ye, X., Yan, Y., Li, J., & Jiang, B. (2024). Privacy and personal data risk governance for generative artificial intelligence: A Chinese perspective. Telecommunications Policy, 48(10). https://doi.org/10.1016/j.telpol.2024.102851

Zamlynskyi, V., Kalinichenko, S., Kniazkova, V., Skrypnyk, N., & Avriata, A. (2025). Healthcare management using artificial intelligence. In Revolutionizing Medical Systems using Artificial Intelligence (pp. 1-24). https://doi.org/10.1016/b978-0-443-32862-6.00001-8

Zhang, C., Zhu, W., Dai, J., Wu, Y., & Chen, X. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Information Systems, 49. https://doi.org/10.1016/j.accinf.2023.100619

Zhong, Q., Zhang, Q., & Yang, J. (2025). Can artificial intelligence empower energy enterprises to cope with climate policy uncertainty? Energy Economics, 141. https://doi.org/10.1016/j.eneco.2024.108088

Published

2025-07-14

How to Cite

Acuña Acuña, E. G. (2025). Autonomous enterprises: strategic decision-making powered by artificial intelligence in business administration. Revista Académica Institucional, 7(2), 1-18. https://doi.org/10.64183/pw7nw416

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