Service

AI UX Design Services

Design the parts of an AI product that decide whether people trust it. We design the conversations, the confidence cues, and the failure states that make AI features feel usable, not just clever.

4–8 weeks
Duration
Teams shipping an AI feature that users do not trust or understand yet
Ideal for
Why this matters
70%

of AI features are abandoned within the first session because users do not trust the output

A model can be accurate and still get ignored if the product never explains itself. People do not trust a black box, and they do not stick around to find out if it works. AI UX design closes that gap. It shows users what the AI is doing, how confident it is, and what to do when it is wrong — so the feature gets adopted instead of switched off. A confidence score and a short 'why am I seeing this?' explanation on each suggestion is often the difference between a feature used daily and one quietly disabled in settings.

What's included

Inside AI UX Design

AI UX design is the practice of designing how people actually interact with an AI feature, not just the screens around it. It covers conversational flows, how the product shows confidence and uncertainty, what happens when the model gets something wrong, and how users build trust in an output they did not write themselves. A strong AI feature with bad UX gets ignored. We design the layer that gets it used.

Conversational UX design — we design the dialogue flows, prompts, and response patterns for chat and voice interfaces so they feel natural, not scripted.

Trust and confidence design — we design how the product signals certainty, shows sources, and flags when an answer should be double-checked.

Failure state design — we design what users see when the AI is wrong, unsure, or cannot help, so a bad answer does not end the session.

Onboarding and expectation-setting — we design the first interaction so users understand what the AI can and cannot do before they rely on it.

Human-in-the-loop flows — we design the moments where a person should review, edit, or override an AI output before it goes anywhere important.

Usability testing — we test real flows with real users and fix the friction points before launch, not after the support tickets arrive.

Who it's for

Is this right for you?

This service fits best when you recognise yourself below.

01

Product teams shipping a chatbot, copilot, or AI assistant that users are not adopting.

02

Teams whose AI feature works technically but gets switched off or ignored in practice.

03

Organizations adding AI to an existing product and worried about breaking user trust.

04

Design teams who need conversational and trust patterns they have not built before.

Challenges we solve

The problems behind the brief

Users do not trust the output

An answer with no context reads as a guess. We design confidence cues and sourcing so users know when to rely on it.

Conversations that feel robotic

Generic chatbot flows frustrate people fast. We design dialogue that matches how your users actually talk and think.

No good way to handle a wrong answer

Most AI products dead-end when the model is wrong. We design recovery paths that keep the session going.

Users expect too much, too soon

Without expectation-setting, one bad answer kills trust for good. We design onboarding that sets the right bar early.

Nobody tested it with real users

Internal demos hide the friction real users hit. We run usability testing before launch, not as damage control after.

How we deliver

A clear, repeatable process

No mystery. You always know what happens this week and what comes next.

Weeks 1–2
Research

We study how users currently complete the task, where AI can help, and what would make them trust an AI-generated answer.

Weeks 3–5
Design

We design the conversational flows, confidence states, and failure paths, and build prototypes you can react to.

Weeks 6–7
Test

We run usability testing on the prototypes, watch where users hesitate or distrust the output, and refine the design.

Week 8
Handover

We deliver production-ready UI specs and a pattern library your team can extend to future AI features.

What you receive

Deliverables

Concrete outputs you keep — not just a conversation.

User research findings and trust-driver analysis
Conversational UX flows and dialogue scripts
Confidence and uncertainty UI patterns
Failure state and recovery flow designs
Onboarding and expectation-setting screens
Interactive prototypes for usability testing
Usability test findings and design revisions
Production-ready UI specs and AI design pattern library
How we measure success

What good looks like

Higher session completion on the AI feature, not just higher traffic to it.

Fewer users abandoning the flow after the first AI response.

Usability test scores that improve across rounds of testing, not just opinions.

A reusable pattern library your team applies to the next AI feature without starting over.

Tools & frameworks

The stack behind the work

We pick tools to fit your needs, never vendor relationships.

Design

  • Figma
  • Design Systems
  • Storybook

Prototyping

  • Figma Prototyping

Conversational Design

  • Conversational UX Patterns
  • Voiceflow

Usability Testing

  • Maze
  • UserTesting
FAQ

Common questions about AI UX Design

Straight answers to the questions we hear most.

Still have questions? Talk to our team

What comes next

The natural next step

Good AI UX needs a product worth designing for. If the application itself is not built yet, Custom AI Applications covers the engineering side. If you are still narrowing down what to build, Product Discovery & Scoping shapes the problem first.

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