The top 9 AI tools for UX design in 2026 and how to use it

Do you want to accelerate, streamline and improve your UX design workflow? Discover the most important AI tools for UX and how to use them.

AI is no longer a novelty in UX design. It’s now embedded across the entire workflow, from research and synthesis to interface design, usability testing and accessibility.

But with so many tools available, which ones should you actually be using?

In this guide, we’ve rounded up nine of the best AI tools for UX. Whether you’re just starting out or refining your professional toolkit, these tools show how AI can enhance efficiency and insight while keeping human judgement at the centre of the design process.

What are the top AI tools for UX in 2026?

Dovetail: AI-powered research synthesis and insight management
Maze: AI-assisted usability testing and prototype validation
Miro: AI-powered synthesis and collaborative sense-making
Notion: AI-powered documentation and knowledge management for UX teams
Figma: Embedded AI for interface design and rapid iteration
ChatGPT: AI-powered ideation, synthesis and UX writing support
Stark: AI-powered accessibility testing for inclusive UX
Attention Insight: AI-driven visual attention and layout validation
Hotjar: AI-enhanced behavioural analytics and user feedback

Now let’s take a closer look at what these AI tools for UX have to offer.

1. Dovetail: AI-powered research synthesis and insight management

Dovetail at a glance:

Used for: Analysing qualitative research, tagging interviews, clustering themes and managing research repositories
Price: Free plan available; custom paid plans available on request.
Learn more: dovetail.com

What is Dovetail?

Dovetail is a research repository and insight management platform built for UX and product teams. It centralises research data such as interview transcripts, usability test recordings, survey responses and customer feedback.

Its AI features help automate time-consuming tasks like transcription, tagging, summarising and theme clustering. Instead of manually coding hours of qualitative data, you can use AI to surface patterns and organise insights more efficiently.

How to use Dovetail AI for UX

Here’s how to make the most of Dovetail AI:

Use AI-generated transcripts to analyse interviews faster: Automatically transcribe research sessions and make them searchable, enabling quicker review and pattern detection.
Apply AI tagging to detect themes across participants: Let Dovetail’s AI suggest tags and highlight recurring topics, helping you identify trends without manually coding every response.
Generate AI summaries of research findings: Create structured summaries of interviews or usability tests to quickly share key insights with stakeholders.
Surface patterns across multiple studies: Use AI to cluster insights across different projects, supporting evidence-based design decisions at scale.

In short: Dovetail’s AI features help to reduce admin while keeping interpretation and strategic decision-making in the hands of the designer.

2. Maze: AI-assisted usability testing and prototype validation

Maze at a glance:

Used for: Running usability tests, analysing prototype performance and generating AI-powered research summaries
Price: Free plan available; custom pricing for enterprise plans
Learn more: maze.co

What is Maze?

Maze is a product research and usability testing platform that enables UX teams to validate prototypes, concepts and live products with real users. Designers can run unmoderated usability tests, collect task-based feedback and measure performance metrics such as completion rates and time on task.

Its AI capabilities help streamline analysis by summarising test results, surfacing friction points and generating structured reports. This reduces the time spent manually reviewing responses and compiling findings.

How to use Maze AI for UX

You can use Maze AI to:

Generate AI summaries of usability tests: Automatically condense participant responses and performance data into structured insights that are easier to interpret and share.
Identify friction points in prototypes: Use AI-assisted analysis to detect where users struggle, drop off or hesitate during task flows.
Create shareable research reports quickly: Turn raw usability data into stakeholder-ready summaries without manually compiling slide decks.
Validate design decisions before development: Test prototypes early and use AI-supported insights to refine navigation, layout and interaction patterns before investing in build.

In short: Maze’s AI features help UX designers move from prototype to validated insight faster, while still grounding decisions in real user behaviour.In summary: how to leverage AI tools for better UX

When leveraged correctly, AI tools can help to streamline the UX process, boost efficiency, spark creativity, and foster more user-centric products and experiences. From automating repetitive tasks to mining rich insights from user data, and even generating fully-fledged designs—AI is a powerful UX assistant.

However, it’s essential to use AI tools with care—and not as a replacement for human creativity, expertise, and emotional intelligence. AI can augment and accelerate certain aspects of the UX design process, but it can’t replace the critical thinking, empathy, and intuition that designers bring to the table.

So: embrace AI tools as your ally in the UX design process. Use them to work more efficiently, complement your own skills, and unlock new opportunities for impactful, user-friendly design.

3. Miro: AI-powered synthesis and collaboration

Miro at a glance:

Used for: Clustering research insights, generating diagrams and journey maps and summarising collaborative workshops
Price: Free plan available; paid plans starting at €8/month per member
Learn more: miro.com

What is Miro?

Miro is a collaborative whiteboard platform widely used by UX and product teams for workshops, journey mapping, affinity mapping and strategic planning. It enables distributed teams to brainstorm, organise ideas and visualise complex systems together.

Its built-in AI features help structure unorganised content, summarise boards and generate visual artefacts based on existing inputs. This is especially useful when working with large volumes of sticky notes, research findings or workshop outputs.

How to use Miro AI for UX

You can use Miro AI to:

Automatically cluster sticky notes and research insights: Use AI to group related ideas and detect patterns after workshops or research sessions, speeding up affinity mapping.
Summarise workshop outputs: Generate concise summaries of brainstorming sessions to quickly align stakeholders on key themes and action points.
Create journey maps and diagrams from existing content: Turn raw notes into structured visualisations such as user journey maps, mind maps or process flows.
Generate starting points for ideation sessions: Use prompts to create initial frameworks, templates or discussion prompts when facilitating collaborative workshops.

In short: Miro’s AI features help UX teams move from messy boards to structured insights more efficiently, supporting clearer communication and faster alignment.

4. Notion: AI-powered documentation and knowledge management for UX teams

Notion at a glance:

Used for: Documenting research, managing UX knowledge bases, writing product briefs and generating AI-assisted summaries
Price: Free plan available; paid plans starting at €9.50 per member / month
Learn more: notion.com

What is Notion?

Notion is a flexible workspace tool used for documentation, collaboration and knowledge management. Many UX and product teams use it to store research findings, design decisions, roadmaps and internal guidelines.

Its built-in AI features support writing, summarising, editing and structuring content. This makes it easier to turn raw research notes and meeting transcripts into organised, shareable documentation.

How to use Notion AI for UX

You can use Notion AI to:

Summarise research notes and meetings: Automatically condense long interview notes, workshop outputs or stakeholder meetings into clear summaries.
Draft product briefs and research plans: Generate structured outlines for usability tests, discovery sessions or feature proposals.
Refine UX documentation: Improve clarity, tone and structure in design system documentation, research reports or case studies.
Maintain a searchable UX knowledge base: Use AI to organise and retrieve insights across projects, helping teams avoid duplicated research and inconsistent decisions.

In short: Notion’s AI features help UX teams document their thinking more clearly and keep knowledge accessible across projects and stakeholders.

5. Figma: embedded AI for interface design and rapid iteration

Figma AI at a glance:

Used for: Generating interface layouts, rewriting UI copy, creating design variations and accelerating production workflows
Price: Free starter plan available; paid plans starting at €3/month per seat
Learn more: figma.com

What is Figma AI?

Figma is one of the most popular interface design tools for UX and product teams. Its AI features are now built directly into the platform, enabling designers to generate layouts, edit content and iterate on designs without leaving their workflow.

Instead of relying on standalone AI design generators, Figma AI integrates directly into production files. This makes AI a natural extension of the design process rather than a separate experimentation tool.

How to use Figma AI for UX

You can use Figma AI to:

Generate interface layouts from prompts: Create starting points for screens by describing the type of interface you want, then refine the output to match your design system.
Rewrite and refine UI copy: Adjust tone, simplify language or generate alternative microcopy options directly within your design file.
Create rapid design variations: Generate multiple layout or content variations to explore alternatives before committing to a final direction.
Streamline repetitive design tasks: Use AI to reorganise layouts, suggest improvements or accelerate component-based workflows.

In short: Figma AI helps UX designers move from concept to iteration faster while keeping full control over structure, usability and visual hierarchy.

6. ChatGPT: AI-powered ideation, synthesis and UX writing support

ChatGPT at a glance:

Used for: Generating research questions, synthesising insights, drafting UX copy and structuring design thinking
Price: Free plan available; paid plans offer access to more advanced models and features
Learn more: chat.openai.com

What is ChatGPT?

ChatGPT is a conversational AI tool developed by OpenAI. It can generate text-based outputs in response to prompts, making it useful for writing, ideation and research support.

For UX designers, ChatGPT works best as a thinking partner. It doesn’t replace research or user testing, but it can accelerate preparation, synthesis and documentation across the design process.

How to use ChatGPT for UX

You can use ChatGPT to:

Draft interview and usability testing scripts: Generate structured question sets for user interviews, refine prompts and tailor scripts to different user segments.
Support research synthesis: Paste anonymised research notes and ask for theme clustering, pattern identification or structured summaries to speed up early-stage analysis.
Generate and refine microcopy: Create multiple variations of button labels, error messages, onboarding instructions or empty states, then refine tone and clarity.
Explore edge cases and user scenarios: Ask ChatGPT to simulate potential user behaviours, objections or failure points to strengthen interaction design.

In short: ChatGPT helps UX designers think more broadly and move faster, while keeping validation and decision-making grounded in real user data.

7. Stark: AI-powered accessibility testing for inclusive UX

Stark at a glance:

Used for: Testing colour contrast, identifying accessibility issues and supporting WCAG compliance within design workflows
Price: Free starter plan available; paid plans starting at $21 per month (around €18)
Learn more: getstark.co

What is Stark?

Stark is an accessibility tool that integrates with design platforms such as Figma, enabling UX designers to test and improve the accessibility of their interfaces. It helps teams identify issues related to colour contrast, visual clarity and compliance with accessibility standards.

Its AI-assisted features support faster detection of potential accessibility risks, allowing you to address issues earlier in the design process rather than after development. With regulations like the European Accessibility Act now in force, this is more important than ever.

How to use Stark for UX

You can use Stark to:

Check colour contrast automatically: Test text and background combinations against accessibility standards to ensure sufficient readability for users with visual impairments.
Scan designs for accessibility issues: Identify potential usability barriers early, reducing the need for costly revisions later in development.
Validate inclusive design decisions: Use accessibility insights to support design choices with measurable criteria rather than assumptions.
Embed accessibility into your workflow: Integrate testing directly into your design process instead of treating accessibility as a final checklist item.

In short: Stark helps UX designers create more inclusive, compliant experiences while making accessibility testing a natural part of the design workflow.

8. Attention Insight: AI-driven visual attention and layout validation

Attention Insight at a glance:

Used for: Predicting user attention, generating AI-powered heatmaps and validating visual hierarchy
Price: Free trial available; paid plans starting at €29 per month
Learn more: attentioninsight.com

What is Attention Insight?

Attention Insight is a design validation tool that uses AI to simulate how users are likely to visually scan and focus on an interface. Instead of relying on live traffic or user testing, it predicts attention patterns based on trained models and behavioural data.

This makes it particularly useful in early design stages, when you want to validate layout decisions before investing in development or full usability testing.

How to use Attention Insight for UX

You can use Attention Insight to:

Generate predictive heatmaps for new designs: Upload mockups or prototypes and visualise which elements are likely to attract the most attention.
Test visual hierarchy before user testing: Validate whether key calls-to-action, headlines or navigation elements are positioned effectively.
Compare alternative design versions: Analyse multiple layout variations to identify which version is more likely to guide user attention appropriately.
Refine landing pages and conversion flows: Use attention data to optimise layouts where clarity and engagement are critical.

In short: Attention Insight helps UX designers evaluate visual hierarchy early, enabling faster iteration before conducting live user testing.

9. Hotjar (now part of Contentsquare): AI-enhanced behavioural analytics and user feedback

Hotjar at a glance:

Used for: Analysing real user behaviour through heatmaps, session recordings and feedback tools
Price: Free plan available; paid plans starting at €39 per month
Learn more: hotjar.com and contentsquare.com

What is Hotjar?

Hotjar is a behaviour analytics platform that helps UX and product teams understand how users interact with live websites and digital products. It combines heatmaps, session recordings, on-page surveys and feedback widgets to provide qualitative insight into real user behaviour.

Its AI-assisted features help summarise session data and surface patterns, making it easier to interpret large volumes of behavioural information.

Good to know: In 2025, Hotjar joined forces with Contentsquare, a digital experience analytics platform. Hotjar’s core tools such as heatmaps, session recordings and surveys remain the same. For UX designers, this means you can continue using Hotjar as before, with the potential for expanded analytics capabilities in the future.

How to use Hotjar for UX

You can use Hotjar to:

Analyse real user heatmaps: See where users click, scroll and spend time on live pages to evaluate layout effectiveness and content placement.
Review session recordings: Watch anonymised user sessions to identify friction points, navigation confusion or unexpected behaviours.
Collect in-context feedback: Use on-page surveys and feedback widgets to gather qualitative insights directly from users.
Surface behavioural patterns at scale: Use AI summaries to detect recurring issues or trends across multiple sessions, supporting data-informed design decisions.

In short: Hotjar helps UX designers move beyond assumptions by grounding improvements in observable, real-world user behaviour.

How to leverage these AI tools for better UX

However, it’s essential to use AI tools with care. No matter how advanced they become, they’re not a replacement for human creativity, expertise and emotional intelligence. AI can augment and accelerate certain aspects of the UX design process, but it can’t replace the critical thinking, empathy and intuition that designers bring to the table.

So: embrace AI tools as your ally in the UX design process. Use them to work more efficiently, complement your own skills, and unlock new opportunities for impactful, user-friendly design.


	
		
			
                
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Discover more AI tools and industry insights

If you’ve enjoyed learning about AI tools for UX design, check out the following resources for further tools and insights into how AI is shaping the UX design industry:

Emily Stevens • Writer for the UX Design Institute Blog

Emily is a professional writer and content strategist with an MSc in Psychology. She has 8+ years of experience in the tech industry, with a focus on UX and design thinking. A regular contributor to top design publications, she also authored a chapter in The UX Careers Handbook. Emily also holds a BA in French and German and is passionate about languages and continuous learning.

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