Gobernanza digital y gestión pública en la era de la inteligencia artificial: una revisión sistemática

Digital governance and public management in the age of artificial intelligence: a systematic review

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Contexto: La integración de sistemas inteligentes en la gestión pública representa una transformación global que redefine los modelos de gobernanza digital, modificando los procesos de toma de decisiones, transparencia institucional y relación entre Estado y ciudadanía. Objetivo: Analizar sistemáticamente las contribuciones científicas publicadas entre 2019 y 2026 sobre gobernanza digital y gestión pública en la era de la Inteligencia Artificial. Metodología: Se desarrolló una revisión sistemática con enfoque cualitativo y diseño descriptivo, siguiendo el protocolo PRISMA 2020. Se aplicó análisis de contenido temático mediante una matriz de vaciado como instrumento de organización de la información. La muestra final estuvo conformada por 17 estudios seleccionados según criterios de elegibilidad. Resultados: Los hallazgos evidenciaron que el 60 % de los estudios se concentra en transparencia algorítmica, el 55 % en creación de valor público y el 45 % en marcos éticos para la implementación de inteligencia artificial en la gestión estatal. La evidencia muestra que la IA está reconfigurando los procesos administrativos públicos y las formas de interacción ciudadana, aunque su impacto depende de la capacidad institucional para garantizar mecanismos de control y responsabilidad. Conclusiones: La gobernanza digital basada en Inteligencia Artificial puede fortalecer la confianza ciudadana mediante transparencia, generación de valor público y rendición de cuentas. No obstante, su implementación requiere capacidades institucionales sólidas, marcos éticos contextualizados y una adopción crítica que evite la incorporación automática de modelos tecnológicos externos sin adaptación a las realidades locales.
Background: The integration of intelligent systems into public management represents a global transformation that is redefining digital governance models. This shift is reshaping decision-making processes, institutional transparency, and the relationship between the State and its citizens. Objective: This study aims to systematically analyze scientific contributions published between 2019 and 2026 regarding digital governance and public management in the era of Artificial Intelligence (AI). Methodology: A systematic review was conducted using a qualitative approach and a descriptive design, following the PRISMA 2020 protocol. Thematic content analysis was applied using a data extraction matrix to organize the information. The final sample consisted of 17 studies selected based on predefined eligibility criteria. Results: The findings revealed that 60% of the studies focus on algorithmic transparency, 55% on public value creation, and 45% on ethical frameworks for AI implementation in state management. The evidence indicates that AI is reconfiguring public administrative processes and citizen interaction patterns; however, its impact depends on institutional capacity to ensure control and accountability mechanisms. Conclusions: AI-driven digital governance can strengthen citizen trust through transparency, public value generation, and accountability. Nevertheless, its implementation requires robust institutional capacities, contextualized ethical frameworks, and a critical adoption approach that avoids the automatic incorporation of external technological models without adaptation to local realities.

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Mamani Tacuri, M. P., Medina Sotelo, C. G., & Llacho Mayhua, I. K. (2026). Gobernanza digital y gestión pública en la era de la inteligencia artificial: una revisión sistemática. Impulso, Revista De Administración, 6(15), 1-13. https://doi.org/10.59659/impulso.v.6i15.353
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Mamani Tacuri, M. P., Medina Sotelo, C. G., & Llacho Mayhua, I. K. (2026). Gobernanza digital y gestión pública en la era de la inteligencia artificial: una revisión sistemática. Impulso, Revista De Administración, 6(15), 1-13. https://doi.org/10.59659/impulso.v.6i15.353

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