9 UX patterns that make AI products feel trustworthy
People judge an AI product in the first minute: do I know what to ask, can I trust the answer, can I fix it when it’s wrong? Nine patterns that answer those questions.
The nine patterns
- Never show an empty boxStarter prompts, examples from the user’s own data, or one-click tasks.
- Put AI where the work isInline suggestions and buttons often beat a separate chat window.
- Show your sourcesLink each claim to the document or row it came from.
- Be honest about confidence“I couldn’t find a price in this contract” beats a confident guess.
- Make output editableA first draft: edit in place, regenerate, compare.
- Undo everythingEvery AI action is reversible, with a clear history.
- Show the plan for agentsSteps, progress and approvals before it sends, buys or deletes.
- Ask for feedback at the right momentWatch edits and rejections; ask one short question then.
- Fail gracefullyDesign slow, wrong and unavailable states, with a way to a human.
Where to start
Most teams get the biggest win from the first three: no blank box, AI in the flow, visible sources. They decide whether people try the product a second time.
Further reading
FAQ
What makes AI UX different from regular UX?
The output isn’t predictable. Design has to cover a range of answers, including wrong ones, and help people check and correct them.
Should every AI product have a chat interface?
No. Chat suits open questions. For repeat tasks, buttons, inline suggestions or background agents are usually faster.
How do you build trust in an AI feature?
Show sources, be clear about uncertainty, make output editable and every action reversible.