AI chat and assistant UX checklist
Chat is the default interface for large language models, and most of its usability problems are the same from product to product: people don't know what to ask, long answers scroll away from them, sources are hard to check, and nobody can find where the history went.
This checklist covers the conversation itself, from an empty input box to a saved chat. It draws on Nielsen Norman Group's research on AI chatbots and prompt suggestions, Apple's guidelines for generative AI, and Microsoft's Guidelines for Human-AI Interaction. Items without a source are common practice in shipping chat products, written as checks rather than claims.
Download the PDF
AI chat and assistant UX checklist as a print-ready PDF (A4, 151 KB). Everything in it is also free to read on this page.
How to use it
Test it on the real product with real prompts, including long answers, slow answers and a question the assistant should refuse. Most of these items only show up when something goes wrong.
For the error and failure states of the assistant, use the AI error and hallucination checklist alongside this one.
Ticks are saved in this browser only. Nothing you tick here is sent to UX Pickle.
Starting a conversation
NN/g recommends informative opening messages and suggested prompts that show the chatbot's capabilities and scope. An empty box gives no hints. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
NN/g found prompt suggestions work when they are contextually relevant, personalised, and matched to the task and the person's experience level. NN/g: Prompt Suggestions
Clickable suggestions cut typing and make the next step obvious. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
NN/g recommends consolidating AI chat with other chat features; multiple bots confuse people about which one to use. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
Losing the conversation on navigation forces people to start again. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
The input
W3C: placeholder text is not a replacement for labels, screen readers do not treat it as one, and browsers usually show it below minimum contrast. W3C WAI Forms Tutorial: Instructions
People paste long text into assistants; a single-line box hides most of what they are sending.
A rejected file after a long upload is a dead end unless the message says what would work.
NN/g lists voice input as an option that suits accessibility needs and personal preference. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
Retyping a long prompt after a network error is the most avoidable frustration in chat.
Responses and streaming
Apple suggests specific messages such as “Summarizing key themes from your notes” over a vague “Processing…”. Apple HIG: Generative AI
People often see within a few lines that the answer is off track. Stopping should keep what was generated so far.
NN/g recommends keeping the scroll position at the start of a response so people read it from the beginning. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
Status changes should be announced without moving focus (WCAG 4.1.3). Announcing each token as it streams makes the page unusable with a screen reader. WCAG 2.2: Understanding Status Messages
NN/g recommends progressive disclosure to keep the conversation short and scannable. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
NN/g recommends images, not only links or text descriptions, for products and instructions. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
Apple recommends surfacing controls such as Edit, Undo, Retry or Adjust near generated content. Apple HIG: Generative AI
Apple suggests offering alternative versions where choice helps bridge the gap between the model's interpretation and what someone wants. Apple HIG: Generative AI
Sources and verification
NN/g recommends placing sources directly next to the specific claim they support. NN/g: Explainable AI in Chat Interfaces
Checking a claim should take one click. NN/g suggests deep links to the referenced passage or a preview of the source. NN/g: AI Chatbots Discourage Error Checking
NN/g advises against vague link labels such as “Source”, and recommends styling citations distinctly from the answer. NN/g: Explainable AI in Chat Interfaces
NN/g recommends plain-language disclaimers paired with an action, placed near the input box and included in onboarding. NN/g: Explainable AI in Chat Interfaces
Feedback
Microsoft's G15: enable people to give feedback during regular interaction. Microsoft HAX: Guidelines for Human-AI Interaction
PAIR recommends feedback questions at a level of detail the team can actually use to improve the model. PAIR: Feedback + Control
PAIR suggests being specific about timing (now or later) and scope (just you or everyone) when acknowledging feedback. PAIR: Feedback + Control
People rate an answer without expecting their whole chat to be read. Apple asks for explicit permission when sensitive data is used for model improvement. Apple HIG: Generative AI
Memory, history and data
Microsoft's G12: remember recent interactions and let people refer back to them. Microsoft HAX: Guidelines for Human-AI Interaction
Microsoft's G17 calls for global controls over what the AI monitors and how it behaves; long-term memory is exactly that. Microsoft HAX: Guidelines for Human-AI Interaction
Without this, personalised answers look like the model guessed private details, which feels intrusive.
Delete should mean what people think it means, or say what it doesn't do.
People ask sensitive questions they don't want kept. Apple asks for the minimum data needed and a clear way to opt out. Apple HIG: Generative AI
NN/g recommends letting people email, download or share chat content worth keeping. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
NN/g recommends letting people resize the chat window. NN/g: 10 Guidelines for Designing Your Site's AI Chatbots
Sources
- NN/g: 10 Guidelines for Designing Your Site's AI Chatbots (Kenderova, Rosala, Kohler, 2026)
- NN/g: Prompt Suggestions (Moran, Neusesser, 2025)
- NN/g: Explainable AI in Chat Interfaces (Chan, 2025)
- NN/g: AI Chatbots Discourage Error Checking (Samsonov, 2025)
- Apple Human Interface Guidelines: Generative AI
- Microsoft HAX Toolkit: Guidelines for Human-AI Interaction
- Google PAIR: Feedback + Control
- W3C: Understanding WCAG 2.2 Success Criterion 4.1.3 Status Messages
- W3C WAI Forms Tutorial: Instructions
Checked against these sources on 3 October 2026. Spotted something out of date? Email hi[at]uxpickle.com.