AI
Product
Patterns
Learn the key UX patterns for designing AI features in SaaS products, from setting expectations to showing sources and handling errors.
Set Clear Expectations
Quick answer: good AI product UX sets clear expectations, shows how results were produced, makes outputs easy to edit and handles mistakes gracefully. Users need to trust AI features before they rely on them. Tell users what the AI can and cannot do, with example prompts or suggested actions to get started. Onboarding for AI features should show users how to get good results, with examples of effective requests.
Label AI-generated content so users know what came from the model. Design for different confidence levels. When the AI is less certain, say so clearly.
AI
SaaS Design
Patterns That Build Trust
Show sources and reasoning: link to the data or documents behind an answer where possible. Keep humans in control: let users review, edit, accept or reject outputs before they take effect. Let users undo AI actions easily, especially when the AI changes data or sends messages.
Show progress: streaming responses and loading states make waiting feel shorter. Offer feedback controls: simple thumbs up or down and regenerate options help users and improve the model. Keep AI features consistent with the rest of the product, so they feel integrated rather than bolted on.
Handle Errors and Edge Cases
Design for wrong answers. Make it easy to correct the AI and recover without losing work. Protect privacy by explaining what data is used and giving users control over it. Monitor how users interact with AI features and refine prompts, suggestions and layouts over time.
Kites Design designs AI features for SaaS products, from chat interfaces to smart suggestions, on our monthly plans. Be transparent about limitations in your help docs and in the interface itself.
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