Inteligencia artificial y toma de decisiones en la gestión pública: oportunidades y desafíos. Revisión sistemática
Artificial intelligence and decision-making in public management: opportunities and challenges. A systematic reviewContenido principal del artículo
La incorporación de la inteligencia artificial (IA) en la gestión pública representa una transformación significativa en los procesos de toma de decisiones, planificación y prestación de servicios. El objetivo del estudio es examinar críticamente el rol de la inteligencia artificial (IA) en la toma de decisiones en la gestión pública, identificando oportunidades principales, desafíos sustantivos y principios para una implementación responsable. Se realizó una revisión sistemática de literatura siguiendo las directrices PRISMA 2020. La búsqueda abarcó cinco bases de datos (Scopus, Web of Science, ProQuest, IEEE Xplore, Google Scholar) para el período 2019-2024. De 850 registros iniciales, se seleccionaron 16 estudios empíricos y casos de aplicación mediante criterios rigurosos de inclusión y exclusión. Los hallazgos permitieron identificar cinco áreas críticas de aplicación: análisis predictivo, automatización administrativa, detección de fraude, personalización de servicios y optimización de recursos. La IA demuestra capacidad para incrementar la eficiencia operativa entre 30-50% y mejorar la precisión predictiva hasta 85%. Sin embargo, la implementación enfrenta desafíos como sesgos algorítmicos, opacidad de modelos, brechas de capacidades técnicas y marcos regulatorios insuficientes. Las conclusiones señalan que el éxito de la IA gubernamental depende menos de la sofisticación tecnológica que del diseño institucional apropiado. Se propone el Marco de Implementación Responsable de IA en Gestión Pública (MIRAGP) para integrar principios de transparencia, equidad, rendición de cuentas y participación ciudadana en todo el ciclo de vida de los sistemas automatizados.
The integration of artificial intelligence (AI) into public administration represents a significant transformation in decision-making, planning, and service delivery processes. This study aims to critically examine the role of AI in public administration decision-making, identifying key opportunities, substantive challenges, and principles for responsible implementation. A systematic literature review was conducted following the PRISMA 2020 guidelines. The search encompassed five databases (Scopus, Web of Science, ProQuest, IEEE Xplore, and Google Scholar) for the period 2019–2024. From an initial 850 records, 16 empirical studies and case studies were selected using rigorous inclusion and exclusion criteria. The findings identified five critical application areas: predictive analytics, administrative automation, fraud detection, service personalization, and resource optimization. AI demonstrates the capacity to increase operational efficiency by 30–50% and improve predictive accuracy by up to 85%. However, implementation faces challenges such as algorithmic biases, model opacity, technical capability gaps, and insufficient regulatory frameworks. The findings indicate that the success of government AI depends less on technological sophistication than on appropriate institutional design. The Framework for Responsible Implementation of AI in Public Management (MIRAGP) is proposed to integrate principles of transparency, equity, accountability, and citizen participation throughout the lifecycle of automated systems.
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