ARTIFICIAL INTELLIGENCE FOR IMPROVING DECISION-MAKING PROCESSES IN PUBLIC ADMINISTRATION

The integration of artificial intelligence (AI) in public administration represents one of the most promising innovations for enhancing the efficiency and effectiveness of decision-making processes. This study focuses on AI applications to optimize decision-making within public institutions, with particular focus on resource management, strategic planning, and emergency response. Using a multidisciplinary approach, the research analyses case studies of public administrations that have implemented AI-based solutions, highlighting the benefits achieved and the challenges encountered. Through the use of machine learning algorithms and decision support systems, public administrations can improve the accuracy of predictions, reduce response times, and optimize resource allocation. Preliminary results indicate that the adoption of AI leads to greater transparency and accountability in administrative decisions, while also promoting a more proactive and data-driven management approach. However, issues related to data privacy, cybersecurity, and the need for specialized skills to manage advanced technologies also emerge. This study contributes to the existing literature on innovation in public administration by proposing a framework for the effective implementation of AI in decision-making processes. Practical implications include recommendations for policymakers on how to overcome technical and organizational barriers, as well as strategies to ensure sustainable and ethical integration of AI in public systems.