What it means
The interface and interaction patterns that make AI outputs understandable, verifiable, and controllable for the task at hand.
Why designers should care
Users abandon AI features when they cannot tell what the system did, whether to believe it, or how to undo it. AI UX patterns encode solutions seen in shipped products.
Example
A search assistant streams an answer, shows numbered citations inline, and lets users open the source panel without leaving the thread.
Common mistakes
- Copying static-app layouts without states for loading, partial results, or errors.
- Equal visual weight for high-confidence and low-confidence outputs.
- Hiding that the feature uses AI until something goes wrong.
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Frequently asked questions
What is AI UX?
AI UX (AI user experience) is how people perceive and interact with AI features: streaming replies, tool pickers, citations, autonomy, memory, and recovery when something goes wrong.
Why should designers care about AI UX?
Users abandon AI features when they cannot tell what the system did, whether to believe it, or how to undo it. AI UX patterns encode solutions seen in shipped products.
What are common mistakes with AI UX?
Copying static-app layouts without states for loading, partial results, or errors; Equal visual weight for high-confidence and low-confidence outputs; Hiding that the feature uses AI until something goes wrong.