Does AI Save Time on Product Design? A Randomized Controlled Experiment of AI Prompt-to-Design Workflows

AI tools for digital product design now offer prompt-to-design capabilities, allowing designers and their non-designer colleagues to create prototypes through conversational workflows with large language models (LLMs). While these tools promise time savings, experimental evidence in product design remains limited compared with evidence from software engineering. We conducted a randomized controlled trial with 50 product designers and 50 product managers to evaluate prospective time savings from leveraging Figma Make in design work. Participants attempted three standardized design tasks with or without access to Figma Make. Among participants who completed the study tasks, access to Figma Make was associated with approximately 20% shorter completion times, with larger gains among product managers. Our findings suggest that prompt-to-design tools may enable product managers to further contribute to design work, while the benefits for professional designers may be task dependent.

Introduction. A core value proposition behind why individuals should adopt AI-powered tools is to automate routine tasks and save time. The promise of increased productivity has helped drive both the development of AI tools and their adoption in the workplace. In a 2026 survey, 79% of corporate organizations reported adopting generative AI to some degree [43]. Prior research identifies employee productivity as a partial mediator between AI capabilities and organizational performance and links workforce productivity to organizational readiness and innovative practices [21, 55]. Digital product design is one of the many professions rapidly adopting AI tools, with 91% of designers reporting at least weekly usage in another 2026 survey [13].

Discussion / Conclusion. Estimated completion times for successfully completed tasks were approximately 20% lower in the Figma Make condition than in the control condition when averaging across the three tasks. The estimates account for differences in demographic characteristics, professional experience, and AI tool familiarity. Participants in the Figma Make condition also reported higher task ease and perceived usability scores. These findings suggest that access to Figma Make may support increased productivity and ease of use in structured, reference-based design tasks. Whether these benefits extend to broader design work remains uncertain. For product managers, access to Figma Make was associated with shorter completion times and higher task ease and perceived usability scores. Product managers in the treatment condition also rated their designs more favorably relative to what they thought they could produce outside the study. These findings suggest productivity benefits beyond time savings, encompassing perceived ease of use and self-assessed design quality. Moreover, prompt-to-design tools may help product managers translate their design intentions and ideas into interface changes.