AI in the Design Process: Which Tools Actually Work

The hype around generative AI has subsided, and the market has brutally verified thousands of "revolutionary" plugins. So, it's worth asking a concrete question: which AI tools are genuinely becoming a staple in a Product Designer's toolkit, and which were just a fleeting trend?

Research and Analysis (Generative Research)

Undoubtedly, AI's biggest win in UX isn't UI generation, but rather qualitative data analysis. Tools like Dovetail leverage LLMs to automatically tag hundreds of hours of interview recordings.

AI won't replace a researcher, but a researcher using AI will replace one who doesn't. Automating transcription and sentiment analysis allows us to focus on strategic insights.

UI Generation: Hype Relic or Practical Tool?

Tools like v0.dev (from Vercel) have demonstrated that generating UI from text prompts can save hours on wireframing. While it's not production-ready code or design without revisions, it's a brilliant starting point. When you're creatively blocked on a dashboard layout, you type "SaaS dashboard for logistics company" and get five variants in 30 seconds.

On the other hand, Figma plugins that generate entire design systems based on a single word, 99% of the time, produce aesthetically pleasing but useless clutter (no auto-layout, no logical structure).

UX Copywriting: The Silent Hero

Most often, I use LLMs (like Claude 3.5 or GPT-4o) not for images, but for words. UX Copywriting is incredibly challenging. A prompt like: "Rewrite this 404 error message; it needs to be max 50 characters, tone: professional yet friendly" saves a lot of frustration.

In summary: AI in 2025 isn't about flying cars. It's about advanced cruise control, allowing us to navigate faster through the tedious, repetitive stages of the design process.