This paper explores the integration of Artificial Intelligence (AI) and Big Data as innovative mechanisms for risk prevention and management within public services. It examines how these technologies enable real-time data analysis, identification of patterns and trends, and prediction of potential risks, thereby enhancing decision-making and operational efficiency. The study highlights both the opportunities—such as improved service quality, reduced costs, and proactive risk mitigation—and the challenges, particularly concerning data privacy, infrastructure security, and skill requirements. While the conceptual framework underlines the theoretical contributions of AI and Big Data, the paper also considers the need for practical applications and case-based studies that can validate these technologies in real-world public sector environments. By analyzing use cases including critical infrastructure monitoring, natural disaster forecasting, and fraud detection, the paper argues that AI and Big Data hold significant promise for reshaping risk management practices in public administration. Keywords: Artificial Intelligence; Big Data; Risk Management; Public Services; Predictive Analytics; Decision-Making; Operational Efficiency; Data Privacy.
Houda HANATY (Sun,) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: