Inteligencia Artificial y Sistemas de Decisión en Economías Emergentes: Un Análisis Bibliométrico y de Evolución Temática

Abstract

Introduction: The application of artificial intelligence to decision-making has become a relevant field of study for management and innovation, as it allows researchers to examine not only what is being studied, but also how this knowledge connects with organizational realities.
Objective: To analyze the evolution of the field of artificial intelligence applied to decision-making, with particular attention to the differences between global scientific production and research developed in more applied contexts.
Method: A quantitative bibliometric approach was employed, based on the comparative analysis of two corpora: one with international scope and another corresponding to an emerging journal. Frequency analysis, proportions, Pearson correlation, and linear regression modeling were used to identify patterns of convergence and divergence in the thematic structure of the field.
Results: The results reveal an inverse relationship between both corpora, with a strong concentration on artificial intelligence and decision systems at the global level, contrasted with a more balanced and contextual distribution in the emerging corpus. This difference suggests that the development of the field is not uniform, but rather reflects different levels of maturity and contextual conditions.
Conclusions: Emerging economies, far from being lagging behind, represent a strategic space for the application and adaptation of AI-based decision systems, opening new opportunities for research closely linked to real organizational challenges.