  Storyboarding is an established method for designing user experiences.
Generative AI can support this process by helping designers quickly create
visual narratives. However, existing tools only focus on accurate text-to-image
generation. Currently, it is not clear how to effectively support the entire
creative process of storyboarding and how to develop AI-powered tools to
support designers' individual workflows. In this work, we iteratively developed
and implemented StoryDiffusion, a system that integrates text-to-text and
text-to-image models, to support the generation of narratives and images in a
single pipeline. With a user study, we observed 12 UX designers using the
system for both concept ideation and illustration tasks. Our findings
identified AI-directed vs. user-directed creative strategies in both tasks and
revealed the importance of supporting the interchange between narrative
iteration and image generation. We also found effects of the design tasks on
their strategies and preferences, providing insights for future development.
