AI-Driven Decision Support for Public Budgeting: Insights from an Exploratory Case Study

Public budget preparation is a multilayered complex process, requiring the reconciliation of diverse political, economic, and societal interests while managing large-scale financial data. In this study, we explore the potential of artificial intelligence (AI) to support and enhance public budget preparation, with a specific focus on Germany's state and municipal levels. Using an exploratory case study and a human-centered development approach, we identify key challenges in budget planning, including information overload, stakeholder communication difficulties, and last-minute adjustments. We investigate various AI-driven solutions, such as large language models, intelligent communication tools, and machine learning-based anomaly detection. Among these, anomaly detection received the most positive feedback from stakeholders, leading to the development of a prototype aimed at assisting decision-makers throughout the budgeting process. While our findings indicate that AI systems can provide valuable support in public budgeting, significant challenges remain, particularly regarding data availability and system integration. This study contributes to the ongoing discourse on AI applications in public administration, highlighting both the opportunities and limitations of AI-driven budget planning.