¿Cómo influye la confianza del usuario en la adopción de sistemas de información impulsados por IA? Un enfoque de modelado de ecuaciones estructurales

Oscar Danilo  Gavilánez Alvarez; John Javier Cruz Garzón; Cristian Luis Inca Balseca

doi:10.70577/ASCE/395.413/2025

Authors

Oscar Danilo Gavilánez Alvarez Escuela Superior Politécnica de Chimborazo (ESPOCH) https://orcid.org/0000-0002-7245-5640
John Javier Cruz Garzón Universidad de las Fuerzas Armadas (ESPE) https://orcid.org/0009-0006-7550-9962
Cristian Luis Inca Balseca Escuela Superior Politécnica de Chimborazo (ESPOCH) https://orcid.org/0000-0002-4795-8297

DOI:

https://doi.org/10.70577/ASCE/395.413/2025

Keywords:

User trust; Perceived usefulness; AI adoption; SEM Model; Algorithmic Transparency.

Abstract

This study employs Structural Equation Modeling (SEM) to analyze the factors influencing the adoption of AI systems, highlighting the central role of user trust (β = 0.49) and perceived usefulness (β = 0.089) as key predictors. The results validate the Technology Acceptance Model (TAM) but extend its framework by demonstrating that trust acts as a critical mediator, especially in contexts of technological uncertainty. Perceived security showed a moderate effect (β = 0.23), relevant in sensitive applications, while usability had a minimal impact (β = 0.04), suggesting that users prioritize reliability over ease of use. Organizational variables (e.g., size) had a marginaleffect, emphasizing the predominance of individual factors. The findings underscore the need for transparency and explainability (XAI)-centered designs to strengthen trust and facilitate adoption.

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