UX Designer’s Perception of Trust in AI-Generated Design Recommendation

As AI becomes more integrated into UX design tools, building trust in AI-generated output is important for successful adoption. This thesis investigates how UX designers perceive and build trust in AI-assisted design tools including Figma AI, ChatGPT and Adobe Sense. Using a qualitative approach, semi-structured interviews with professional fissional were conducted to investigate their interactions with AI-generated content. The findings build on the Hoff and Bashir Trust Model by identifying six trust influencing themes: initial expectations, trust criteria, task-specific usage, human oversight, consistency and ethical concerns. These findings provide practical insights into how designers evaluate, modify, or reject AI proposals, highlighting the significance of transparency, control and inclusion in AI design. The findings contribute to a better understanding of trust in human-AI collaboration and can help developers create more trustworthy, user-centered AI tools for design workflows.