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A Multi-Criteria and Empirical Study for Determining the Influencing Factors of Generative Artificial Intelligence Adoption in Companies

S. Gomes Soares Alcalá, V.L. de Nicolás, A.J. López López, M. Ventosa

Systems Research and Behavioral Science Vol. 43, nº. 2, pp. 750 - 772

Resumen:

Generative artificial intelligence (GenAI) has emerged as a transformative force across business and society due to its ability to generate new content. This potential to reshape businesses introduces challenges and opportunities, necessitating a deeper understanding of GenAI's impact. Despite its promise, the factors that enable effective GenAI adoption within companies remain underexplored. Based on systems thinking principles, this study proposes a comprehensive approach to determine the most critical and influential factors for effective GenAI adoption in companies. Thirteen factors are identified and validated by experts and then aggregated within a technological, business, organizational and environmental framework. After that, a multicriteria approach is applied to identify critical and influential factors, considering their interrelationships and the judgements of chiefs on technology and information from Spanish companies representing several sectors and sizes. Findings indicate that organizational factors are critical in most cases. This study guides companies and individuals in navigating effective GenAI adoption and supports future research.


Palabras Clave: adoption ; analytic network process; companies; GenAI; generative artificial intelligence; systems thinking


Índice de impacto JCR-JIF y cuartil WoS: 1,900 - Q2 (2025)

Referencia DOI: DOI icon https://doi.org/10.1002/sres.3215

Publicado en papel: Marzo 2026.

Publicado on-line: Noviembre 2025.



Cita:
S. Gomes Soares Alcalá, V.L. de Nicolás, A.J. López López, M. Ventosa, "A Multi-Criteria and Empirical Study for Determining the Influencing Factors of Generative Artificial Intelligence Adoption in Companies", Systems Research and Behavioral Science, Vol. 43, nº. 2, pp. 750 - 772, Marzo 2026. [Online: Noviembre 2025] doi: 10.1002/sres.3215

    Grupos de investigación:
  • Instituto de Investigación Tecnológica (IIT)