Artificial Intelligence and Organizational Decision-Making: An Empirical Analysis of Operational Variables in Companies in Cartagena de Indias
Jose Sarmiento Perez Polo
Abstract
This article analyzes the relationship between the implementation of Artificial Intelligence
(AI) and the quality of decision-making in organizations located in Cartagena de Indias,
Colombia. Using a quantitative cross-sectional methodological design, seven operational
variables were evaluated in a sample of 120 organizations: AI use, decisional quality,
decisional speed, employee satisfaction, operational efficiency, error reduction, and
technological adoption. The results show positive and significant correlations between the
level of AI adoption and improvements in decision-making processes (r = 0.78; p < 0.01).
The correlation matrix analysis and multiple regression models indicate that AI use significantly predicts operational efficiency (β = 0.71) and error reduction (β = 0.68). It is
concluded that the strategic integration of AI tools into organizational processes constitutes
a critical factor for competitive improvement in Cartagena's business context, although its
effectiveness depends on the level of human talent training and available technological
infrastructure.
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