AI: Amplification rather than Replacement—Positioning in the Design Field
People often think, "AI will make designers' jobs disappear," but in practice what you can sense on the ground is less replacement and more amplification. In other words, AI helps with ideation, validation, mass production, and refinement, while designers focus on judgment, editing, and ensuring consistency.
In particular, from 2024 to 2026, entry points into workflows have expanded beyond image generation to include building UI from text, encoding design intent in code, and rapidly producing a large number of variations, which can improve not only production speed but also the quality of proposals (depth of comparison and validation).
Overview: The Five Stages to Integrate AI
We recommend dividing design into the following five stages and assigning AI roles. Tools can be swapped later, but the stage design sticks lasting value.
- ① Requirements Understanding & Research: information gathering, competitive comparisons, a draft of user personas
- ② Concept & Direction: articulation, mood exploration, ideation branching
- ③ Production (UI/Visuals): layout concepts, style concepts, generation/editing of image assets
- ④ Validation & Review: consistency checks, accessibility reviews, copy adjustments
- ⑤ Handoff & Operations: documenting design specifications, component management, asset management
For each of these five stages, the trick is to decide which parts to leave to AI and which parts to humans. AI is fast, but it can misread rationale and constraints, so the final decision rests with the designer.
① Requirements Understanding & Research: Boosting the Initial Pace with AI
What AI can do
- From the product overview, hypothesize user problems and use cases
- Summarize features of competitor sites and create a comparison table
- Extract key points and tag interview notes
What matters here is not to take AI output at face value. AI excels at plausible organization, but if the primary information is weak, it can end up cleanly wrong. The recommended approach is to have AI summarize after you provide source materials (meeting minutes, notes, URLs).
Useful tools
- ChatGPT / Claude: meeting notes summary, issue organization, question drafting
- Notion AI: document shaping, extraction of key points
- Perplexity: to get a first sense of the investigation (source verification is essential)
Practical prompt example
Break down the following meeting notes into five items: (1) user problems, (2) success metrics, (3) constraints, (4) undecided items, (5) questions to confirm next time. Organize them as bullet points. Mark any guesses as "Assumption".
② Concept & Direction: Language and Mood in a Back-and-Forth
The design direction isn't decided by visuals alone. The brand identity, the impression you want to give users, and the product promise must align to speed up decisions.
