The Agent-Based Model (ABM) described in this chapter simulates a simplified model of the asylum procedure in Germany, capturing registration, hearing, decision, and court appeal. Its primary aim is to visualize the complexity of the asylum process and highlight how artificial intelligence (AI) applications must be understood within their operational context. The model serves both as a heuristic tool for understanding decision-making and an instrument to examine potential barriers and trade-offs in using AI technologies, and what they might imply for those affected by the technology, i.e. refugees and street-level bureaucrats. The research aims will be approached with a parameter sensitivity analysis, exploring links between decisions by the Federal Office for Migration and Refugees (German acronym: BAMF) and appeal outcomes, as well as narrative scenarios that illustrate possible refugee pathways. These examples are contextualized with stakeholder perspectives exploring possible implications of AI use. The findings indicate that AI-based technologies are likely to make decision-making processes more opaque, undermining refugees’ agency, and lead to dispersed accountability, especially if the structural problems as well as risks of AI use remain neglected. The chapter concludes that early stakeholder engagement, technology assessment, and governance are crucial.