"This article aims to examine where we actually have use cases for AI that have been implemented, rather than predict where it's going to be useful in the future. By considering all of the phases of a user experience project, including research and concept, wire framing, visual design, writing content, and testing, we will be in a position to determine where we actually see the benefits of AI's capabilities in all of those phases."
"AI isn't something we're waiting on - it's already part of our daily UX workflow. We use it to research, brainstorm, wireframe, write copy, and analyze tests. But it doesn't transform every stage of UX in the same way. Some areas move faster with AI. Others are still evolving. And a few parts of the process benefit more from AI in the background than at the center."
"Because this shift isn't only about speed - it's about responsibility. AI gives us more output, faster. But it also introduces new questions around quality, bias, and judgment. Designers aren't just producing screens - we're filtering, shaping, and deciding which ideas are worth bringing to life. This is not about whether AI will "replace designers." It's about how designers can design differently now that AI is here."
AI already supports many UX activities including research, brainstorming, wireframing, copywriting, and test analysis. Adoption varies by phase: some stages accelerate rapidly, others evolve more slowly, and some benefit most when AI operates in the background. Greater output speed introduces new responsibilities around quality, bias, and judgment. Designers retain decision-making authority by filtering, shaping, and selecting ideas to bring forward. The UX process remains structured around research, concept, design, and testing, with teams tailoring workflows to product and maturity. Practical, implemented use cases determine where AI currently delivers real benefits across the UX lifecycle.
Read at LogRocket Blog
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