Organizational change management in the era of artificial intelligence: a model for digital transformation in public service companies

Authors

DOI:

https://doi.org/10.71112/hhyt4410

Keywords:

organizational change management, artificial intelligence, digital transformation, structural equation modeling (PLS-SEM), and public utility services

Abstract

Introduction: the aim of this research was to propose an organizational change management model adapted to the socioeconomic, cultural, and technological conditions of the Colombian Caribbean region, with an emphasis on the integration of artificial intelligence (AI) in the public services sector, using Aguas de Cartagena S.A. E.S.P. as a case study. Methodology: a quantitative, exploratory, and longitudinal approach was used. Data were collected through an ad hoc survey applied to 120 employees. The structural equation modeling technique (PLS-SEM) was employed to analyze the relationships among five key constructs: visionary leadership, adaptable organizational culture, human talent development, technological infrastructure, and artificial intelligence. Results: the model explained 79.89% of the variance (R²) of the artificial intelligence construct. All dependent factors showed significant effects (ƒ² > 0.29). The model reached a goodness-of-fit index (GOF) of 0.7041 and a Q² value of 0.472, confirming its predictive and structural validity. Discussion: the study demonstrates that effective organizational change management in emerging contexts requires the integration of human, cultural, and technological factors. Although the model is robust, future research should expand its application to other sectors and regions to validate its generalizability.

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References

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Published

2026-01-06

Issue

Section

Applied Sciences

How to Cite

Mendoza Betin, D. J. A. (2026). Organizational change management in the era of artificial intelligence: a model for digital transformation in public service companies. Multidisciplinary Journal Epistemology of the Sciences, 3(1), 125-153. https://doi.org/10.71112/hhyt4410