ArticleFrontiers in artificial intelligence2026
Use of artificial intelligence in Ecuadorian companies.
Article in Frontiers in artificial intelligence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Introduction: Artificial intelligence (AI) has become increasingly embedded in organizational processes; however, the mechanisms explaining its adoption are not yet fully understood, particularly in emerging economy contexts. This study examines the relationship between perceived usefulness (PU) and perceived ease of use (PEOU) in the adoption of AI among firms located in Guayas, Ecuador. Methods: Drawing on the Technology Acceptance Model (TAM), the study analyzes both the conventional directional effect of PEOU on PU and the potential existence of a reciprocal association between these constructs, considering the adaptive nature of AI systems. A quantitative research design was applied using survey data collected from 398 managers of medium and large firms. The analysis was conducted through exploratory and confirmatory factor analyses, followed by structural equation modeling. Results: The findings indicate that perceived ease of use is positively associated with perceived usefulness, consistent with TAM. In addition, perceived usefulness is also positively associated with perceived ease of use, suggesting a reinforcing interaction between the two constructs. These results are consistent with a dynamic interpretation of AI adoption, where user interaction and system responsiveness may evolve together over time. Discussion: This study contributes to the literature by extending TAM to AI contexts through a reciprocal perspective and by providing empirical evidence from an underexplored emerging economy. From a managerial perspective, the findings highlight the importance of combining usability and value delivery in AI system design. Given the cross-sectional nature of the data, the results should be interpreted with caution, as causal relationships cannot be established.
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