Generative Agents at Work: Redesigning Administrative Processes at the German Federal Employment Agency

Abstract

The integration of Generative Artificial Intelligence (GenAI) in public administration offers new ways to handle service and technology complexity while meeting high standards. This paper presents a case study from the German Federal Employment Agency, where a multi-agent system using local large language models (LLMs) automates the conversion of information technology (IT) change requests into structured IT development tasks (Jira tickets). Specialized agents interpret requirements, break them into tasks, and generate consistent entries. This improves organizational efficiency, reduces routine work, and outperforms traditional automation by enabling context-aware reasoning and dialogue, all within a secure, on-premise environment. While motivated by Germany’s demographic challenges, the findings have global relevance for public sector modernization and automation.