Hybrid Model for Strategic Decision-Making in Enterprise Architecture through Cooperation between Humans and Intelligent Agents

María Fernanda Díaz Velásquez, Carlos Andrés Tavera Romero, Fernando Pinciroli, Jesús Hamilton Ortiz

Abstract

The purpose of the article is to present a hybrid model for strategic decision-making in enterprise architecture through cooperation between humans and intelligent agents. The article describes a new conceptual and technical framework, based on the principles of co-intelligence and the ArchiMate modelling language, enabling explicit representation of collaboration between human experts and AI systems in organizational processes. Using a four-stage research approach including conceptual analysis, model design and implementation in the Enterprise Architect platform, application to a business scenario, and result evaluation the authors demonstrate how the proposed framework enhances the modelling of digital transformation processes. The method is applied to a real business requirement, illustrating how human–machine cooperation can support more adaptive and informed strategic decisions. The proposed approach allows enterprise architects to improve modelling efficiency and decision transparency by integrating AI-driven elements directly into business architecture. The effectiveness of the model is confirmed through application-based validation within an industrial context. These research results improve existing enterprise architecture practices and can be applied in both private and public sectors to facilitate digital transformation towards Industry 4.0 and the future Industry 5.0. This paper is novel because it formalizes co-intelligence at a high level of abstraction within enterprise modelling.

 

Keywords: Enterprise architecture; Business architecture; Industry 4.0; Business model; Digital transformation; Co-intelligence; Archimate.

 

DOI https://doi.org/10.55463/issn.1674-2974.52.9.11


Full Text:

PDF


References


LEE, S. K., KAVYA, P. and LASSER, S. C. Social interactions and relationships with an intelligent virtual agent, 2021. International Journal of Human-Computer Studies, 150, 102608. https://doi.org/10.1016/j.ijhcs.2021.102608

YAO, Y. Human-machine Co-intelligence through symbiosis in the SMV space, 2023. Applied Intelligence, 53(3), 2777–2797. https://doi.org/10.1007/s10489-022-03574-5

AROKIARAJ, S., AMUDHA, T. and SWAMYNATHAN, R. Intelligent agents for crowd-sourced software engineering: A survey, Proceedings of the 4th International Conference on Information Management & Machine Intelligence. New York, NY, USA, 2023. Association for Computing Machinery, pp. 409–414. https://doi.org/10.1145/3590837.3590868

ZHONG, N., WANG, Y., XIONG, R., ZHENG, Y., LI, Y., OUYANG, M., SHEN, D. and ZHU, X. CASIT: Collective intelligent agent system for Internet of Things, 2024. IEEE Internet of Things Journal, 11(11), 19646–19656. https://doi.org/10.1109/JIOT.2024.3366906

TSARAMIRSIS, G., KANTAROS, A., AL-DARRAJI, I., PIROMALIS, D., APOSTOLOPOULOS, C., PAVLOPOULOU, A., ALRAMMAL, M., ISMAIL, Z., BUHARI, S. M., STOJMENOVIC, M., TAMIMI, H., RANDHAWA, P., P., PATEL, A. and KHAN, F. Q. A modern approach towards an Industry 4.0 model: From driving technologies to management, 2022, Journal of Sensors, 5023011. https://doi.org/10.1155/2022/5023011

CHENG W. and ZHUOWEI Z. Strategic Contracting for Software Upgrade Outsourcing in Industry 4.0. Computer Modeling in Engineering & Sciences, 2024, 138(2), 1563–1592. ISSN: 1526-1506. , https://doi.org/10.32604/cmes.2023.031103 [7] ANUMBE, N., SAIDY, C. and HARIK, R. A primer on the factories of the future, 2022, Sensors, 22(15), 5834. https://doi.org/10.3390/s22155834

YERRAMILLI-RAO, B., CORWIN, J., LI, Y. AND LAKHANI, K. R. Strategy in an era of abundant expertise, Harvard Business Review, 2025 March.

WORLD ECONOMIC FORUM. System initiative on shaping the future of production: Impact of the Fourth Industrial Revolution on supply chains, 2017. Available at: https://www3.weforum.org (document ID: WEF Impact Supply Chains).

TAVERA ROMERO, C. A., ORTIZ, J. H., KHALAF, O. I. and RIOS PRADO, A. Web Application Commercial Design for Financial Entities Based on Business Intelligence. Computers, Materials &Continua, 2021, 67(3), 3177–3188. https://doi.org/10.32604/cmc.2021.014738 DOI: 10.32604/cmc.2021.014738.

PUERTA-RAMÍREZ, J., GIRALDO-GARCÍA, J. and TABARES-LÓPEZ, M. Evaluación de la arquitectura de negocio a través del análisis de factores críticos para el desempeño no de una organización. 2019. Información tecnológica, 30(2), 33–44. http://dx.doi.org/10.4067/S0718-07642019000200033

KOTUSEV, S. Enterprise architecture and enterprise architecture artifacts: Questioning the old concept in light of new findings. Journal of Information Technology, 2019, 34(2), 102–128. https://doi.org/10.1177/0268396218816273

ROELENS, G., WOUT, B. and STEENACKER, G. Realizing strategic fit within the business architecture: the design of a Process-Goal Alignment modeling and analysis technique, 2019, Software & Systems Modeling, 18(1), 631–662. https://doi.org/10.1007/s10270-016-0574-5

THE OPEN GROUP. ArchiMateR 3.1 Specification, 2019. https://pubs.opengroup.org/architecture/archimate3-doc/

OSPINA GARCÍA, N., DÍAZ VELÁSQUEZ, M., TAVERA ROMERO, C., ORTIZ MONEDERO, J. and KHALAF, O. (2021). Remote academic platforms in times of a pandemic. International Journal of Emerging Technologies in Learning (iJET), 16(21), 121–131.. https://doi.org/10.3991/ijet.v16i21.25377

MALAKHOV, K. From Archimate to Computer Ontologies: Advancing Semantic Enterprise Architecture With RAG/RIG AI Services in RDF/OWL. ISUDP Proceedings, 2025, pp. 57–111. http://dx.doi.org/10.31274/isudp.2025.197.02

SHANKARAVELU, K., WU, H. and HELFERT, M. Unlocking Enterprise Value: A Comprehensive Review of ArchiMate’s Value Modelling Landscape and Stakeholder Perspectives. Proceedings of the 26th International Conference on Business Informatics (CBI), 2024, pp. 10–19. http://dx.doi.org/10.1109/CBI62504.2024.00012

SANYOTO, A. E. A., SAPUTRA, M. C. and AKNURANDA, I. Analyzing the impact of UML, BPMN, and ArchiMate integration from user perspective. Proceedings of the 2024 10th International Conference on Computing and Artificial Intelligence, New York, NY, USA, 2024. Association for Computing Machinery, pp. 409–414. https://doi.org/10.1145/3669754.3669817

CRUZ PÉREZ, Y. V. and TAVERA ROMERO, C. A. La comunicación en el estudio comparativo entre lenguajes textuales y lenguajes visuales: caso PiCO y GraPiCO. Editorial de la Universidad Santiago de Cali, 2018.


Refbacks

  • There are currently no refbacks.