Reflections on Public Management and Budget Control with Artificial Intelligence for Population Well-being

[e-2604]: https://doi.org/10.5281/zenodo.20806243

Abstract

Objective: To analyze how public-administrative management, budget control, and artificial intelligence can be articulated to strengthen efficiency, transparency, and population well-being. Methodology: A documentary-reflective review was conducted of indexed academic literature, regulatory documents, and institutional reports published between 2000 and 2024, with emphasis on public administration, digital governance, and resource management. Results: The reviewed evidence shows that artificial intelligence can support planning, resource allocation, risk detection, target tracking, and accountability in state entities. Its use promotes more timely decisions, reduces information asymmetries, and improves spending traceability. Likewise, budget control supported by data analytics makes it possible to identify inefficiencies, prevent deviations, and direct investment toward social priorities. Conclusions: The integration of public management, budgeting, and artificial intelligence should not be understood as a replacement for human judgment, but as support to enhance state capacity. However, its adoption requires ethical governance, interoperability, public servant training, and clear data-protection rules. In Latin American contexts, where institutional gaps persist, this articulation can become a concrete route to improve public policy quality and consolidate a more efficient, transparent, and citizen-oriented State. Moreover, it helps strengthen intersectoral coordination, standardize processes, prioritize vulnerable territories, and generate early alerts to correct management failures before they affect the population, thereby consolidating a more intelligent, responsible, sustainable, inclusive, and human public administration