Does AI Save Time on Product Design? A Randomized Controlled Experiment of AI Prompt-to-Design Workflows
cs.HC, cs.AI
Submitted: 2026-09-22
Updated: 2026-09-22
License: http://creativecommons.org/licenses/by-sa/4.0/
The gist: 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
Terminology
Abstract
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.
Sources
- The Fast and Spurious: Developer Productivity with GenAI
- Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
- Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
- Generative AI for Product Design: Getting the Right Design and the Design Right
- A meta-analysis of the effect of generative AI on productivity and learning in programming
- The Impact of AI on Developer Productivity: Evidence from GitHub Copilot
- Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding
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