Designers use ai tools differently across four design phases
AI Tools Adoption across the Double Diamond Workflow: Phase, Mode, and Barriers in Designer Practice
Human-Computer Interaction
Summary
Designers are using AI tools in different ways depending on the stage of their design process. A large survey showed most designers work with AI in some phases but not all, with more use in the early idea stages than in finishing or delivering. Different types of AI tools suit different phases, like chatbots for brainstorming and AI image generators for creating designs. The main difference between those who use AI and those who don't is how useful they think it is.
What this means in practice
- •For design tool developers: Develop phase-specific AI features that match designers’ preferred activities and collaboration modes identified in each Double Diamond phase.$Commercial implications: Enables design software companies to create AI tools tailored to each design phase, improving adoption and user satisfaction.
- •For creative agency managers: Allocate AI tools strategically during design workflows by recognizing which phases benefit most from AI-generated versus embedded AI assistance.
A survey. It maps existing work.
Authors
Sepideh Tajarmakan, Khashayar Hojjati Emami
Abstract
Designers are adopting AI faster than the tools built for them can keep up. This survey of 443 designers across 43 countries, among the first phase-disaggregated accounts of its kind, examined reported AI use across the four phases of the Double Diamond workflow (Discover, Define, Develop, Deliver). 79.7 percent reported confirmed AI use in at least one phase, but engagement was typically partial, spanning a mean of 2.89 of 4 phases, with adopters retaining the earliest phases and dropping the latest. Tool choice tracked each phase's dominant activity: conversational tools drove Discover and Define, AI-native image generation took over Develop, and Deliver showed a hybrid profile. AI-native and embedded AI use peaked in different phases, pointing to two distinct modes of human-AI collaboration: generating from scratch versus refining within existing software. Use intensity declined through fewer designers engaging, not scaled-back use. Adopters and non-adopters differed on one dimension: perceived usefulness.