Zózimo, RicardoHeur, Maximilian Michael D'2025-03-312025-03-312025-01-302024-12-17http://hdl.handle.net/10362/181710Rapid population growth, inequalities, and technological disruption create interconnected societal challenges driven by dynamic interactions among social, technological, and environmental factors. System mapping, while vital for understanding these complexities, is resource intensive. Generative AI (GenAI) can potentially accelerate the study of such issues, though its practical application remains underexplored. This research employs a mixed-methods approach to examine GenAI's role in system mapping, identifying three dimensions: the potentials of GenAI in system mapping, its challenges and limitations, and the benefits of managing complexity through Human AI Collaboration. These findings provide a foundation for further exploration and practical applications in addressing complex problems.engGenerative AISystems thinkingSystem mappingParticipatory modellingmaster thesis203927222