AI-Enabled Decision Support Systems for Improving Public Administration Effectiveness

Artificial Intelligence (AI) is becoming one of the sources for transforming public administration through introducing new techniques in information processing, policy analysis, service provision, resource management, and decision-making. Public organizations work in an information-intensive environment in which administrators have to analyze large amounts of structured and unstructured data, taking into account changes in the socio-economic, environmental, and technological environment. Traditional decision-making techniques can be restricted by fragmented information systems, manual information processing, limited analytic capacity, time delays in information processing, and difficulties in finding complex interrelations in large datasets. Integration of artificial intelligence techniques with databases, analytic models, visualization techniques, and current e-governance technologies in AI-enabled Decision Support Systems (DSS) creates an opportunity to overcome these limitations and provide administrators with information, predictions, recommendations, and scenarios for decision-making based on evidence. This paper analyzes the role of AI-enabled DSS in enhancing the efficiency of public administration through a conceptual and literature review approach. The study will focus on the evolution of DSS, application of AI in public administration, decision-making theories, technological, organizational, and governance issues. Conceptual framework is generated through the integration of decision-support concepts into the Technology–Organization–Environment framework. The use cases under discussion include applications in the development of policies, delivery of services to citizens, resource allocation, fraud detection, urban planning, healthcare, education, social services, and disaster response. Challenges associated with data accuracy, privacy issues, cybersecurity, biases of algorithms, explainability of decisions, legal aspects, digital divide, skills of personnel, and organizational barriers are discussed as well. The analysis shows that the utilization of AI technologies within decision support systems may increase the effectiveness, analytical capabilities, timeliness, forecasting abilities, monitoring and resource planning if there is relevant data and proper organizational and governance mechanisms. Nonetheless, the application of AI needs to be limited to a decision-support tool rather than a substitute for the human decision-making in public organizations.