The key to building your UX toolstack is to be flexible and grow with your tools. As new tools like AI tools improve and change, your UX toolstack should also evolve to match your growing needs.
AI tools for UX research or design should be supplements, not replacements. They won’t replace designers or researchers, but artificial intelligence-based tools can help streamline brainless tasks and cross-functional collaboration. If you’re a researcher or someone who does lightweight research (like product managers or designers), it’s exciting to explore AI tools for automation and streamlining work.
According to our 2023 State of User Research report, a fifth of researchers are currently using AI in their research, and an additional 38% plan to incorporate it in the future. With AI's increased use and popularity, it’s important to be mindful of the extent to which you rely on these new tools.
Whether you’re for or against AI, the smart thing to do is to understand what AI can do for user experiences and what it cannot do. We’ve compiled a list of over 20 powerful AI tools that can aid UX professionals at every step of a project, from start to finish.
In this article, you’ll find:
- How AI is used in UX research and design
- A list of 20+ best AI tools for UX research and design
- Guardrails for using AI tools
- What AI can (and cannot) do for UX
How AI is used in UX research, design, and product teams
AI has touched many industries, from research to healthcare—and across industries, people's concerns about AI are pretty similar: "Are AI tools going to take my job?"
Not necessarily. As Curtis Langlotz, Stanford University radiologist, says....
“AI won’t replace radiologists, but radiologists who use AI will replace radiologists who don’t.”
We can apply a similar idea to UX researchers. While AI won’t replace UX researchers, researchers who understand how to use AI effectively (and ethically) have the potential to replace researchers who have no experience with this growing technology.
AI has the potential to shape the future of user experiences through hyper-personalization and automation. Researchers who understand how to effectively use new tools and technology like AI are able to demonstrate their flexibility to change and adapt quickly.
As users’ expectations change, your UX research toolkit should also grow and evolve to meet changing needs. Modern teams that don’t interact with any AI tools are missing out on the opportunity to upgrade your UX toolstack with a little boost from AI.
So how is AI used in UX? Here are some examples of how AI tools can help UX research teams, design, and product management.👇
In UX research, AI can be used to:
- Identify the most common user problems in your niche
- Provide a list of your direct competitors
- Identify users and their behaviors
- Automate session recording, note-taking, and text analysis
- Organize your research data into a repository
- Streamline research project management
- Analyze quantitative and qualitative data
In UX design, AI can be used to:
- Gather design requirements
- Generate potential feature sets
- Ideate for new designs
- Validate designs
But the real question is… Will AI replace UX designers?
While we can’t deny the underlying anxiety that designers might have about AI taking over designers’ jobs in the coming years, AI tools won’t replace designers. We can think of AI tools for UX design as just that—tools.
Using AI for UX is still new, and with new technology come many limitations and opportunities for improvement. We won’t go too deep into the possibility of AI replacing designers, but for now it’s important to start thinking about:
- The potential for AI to increasingly become integrated into the design process
- Small tasks that designers can automate with AI for now
In product management, AI can be used to:
- Summarize the product vision
- Generate product decision pros and cons lists
- Generate product roadmap ideas
- Develop questions to uncover jobs-to-be-done (JTBD)
Here are some great resources that list some of the different uses of ChatGPT for UX research, design, and product teams:
- Using ChatGPT for User Research
- 25 ChatGPT Prompts for UX Design Use-Cases
- 45 ChatGPT Use Cases for Product Managers
According to a study evaluating ChatGPT vs UX researchers,
“It’s too early to judge the extent to which the work of UX researchers will be affected by tools like ChatGPT.”
We don’t know how much AI will affect us in the future, but we do know that it will play some kind of role in user experiences. For now, we can explore the different AI tools that are available.
MIT lecturer George Whitfield shares his strategy to safely and effectively use AI in qual analysis. Listen now.
20+ AI tools to power your UX toolstack
ChatGPT isn’t the only AI tool out there. As artificial intelligence becomes more prominent in everyday software solutions, there’s an entire range of different AI-based tools for various use cases.
We won’t be able to cover every single AI tool out there—especially since AI software is continuously improving and new ones keep popping up. We will, however, cover AI-based tools that seem the most relevant and useful for UX toolstacks today.
Here are some of the different types of AI tools for UX we’ll get into:
- Versatile AI UX tools with various use cases
- AI tools for UX research sessions
- Tools with AI for UX project management
- AI UX design tools
- Qualitative UX data analysis AI software
Versatile AI tools with many use cases
1. ChatGPT
Use cases include:
- Generate ideas and responses
- Summarize text
- Generate questions or ideas for questions
- Identify patterns and themes from data
- Literature reviews
We can’t talk about AI without mentioning ChatGPT: the ultimate AI tool for all types of creative work. You can use it to improve your workflow by streamlining repetitive, time-consuming tasks. Rather than listing out all the different possibilities you can use ChatGPT, it’s probably best to try it out for yourself and see what the hype is all about.
2. UserDoc
Use cases include:
- User stories
- Personas
- User journeys
Use UserDoc AI to generate unique user stories, acceptance criteria, personas, and user journeys. UserDoc captures what should be built, the motivations behind it, along with the various user flows through the system—acting as a source of truth for requirements.
3. Notably.ai
Use cases include:
- User interviews
- Usability tests
- Focus groups
- Note-taking
- Video transcription
- Cluster analysis
You can use Notably to create a research repository, transcribe videos, conduct cluster analysis and more.
📘Want to explore more research management tools? Explore this list of 17 Research Recruiting and Panel Management Tools
AI tools for research sessions
4. LoopPanel
Use cases include:
- Note-taking for user interviews
- Transcription
- Live shareable video clips
This tool takes notes for user interviews and categorizes them in your discussion guide. LoopPanel offers high-quality transcription and note-taking tools so you can make sure you’re capturing all of the important moments and insights from your research sessions.
5. Grain.co
Use cases include:
- Note-taking
- Record-keeping
- Insight capture from meeting recordings
Grain is an AI-powered recording tool that comes with note-taking, record-keeping, and insight capture. Learn how Grain is applying AI in research in this podcast episode with Mike Adams, the CEO of Grain: 🎙️ The dangers and opportunities of AI in research.
6. Otter.ai
Use cases include:
- Automate meeting notes
- Record meetings
- Generate meeting summaries
Otter is an AI meeting assistant that records audio, writes notes, automatically captures slides, and generates summaries.
7. VisualEyes
Use cases include:
- Eye tracking for user testing
- Preference testing
This AI tool helps generate user testing insights through eye-tracking. VisualEyes simulates eye-tracking studies and preference tests with 93% accurate predictive technology.
8. SciSpace Copilot browser extension
Use cases include:
- Literature reviews
- Desk research
- Data summarization
This browser extension helps you browse through research articles more quickly and efficiently. You can use SciSpace Copilot to generate easy-to-understand explanations of long, technical text in research articles or find context for huge data sets or data tables in articles.
AI tools for UX project management
9. Mem
Use cases include:
- Data and task organization
- Project management
Mem is an AI-powered workspace management tool for creators. It allows you to easily keep your notes, feedback, ideas, and tasks organized in one place. It works just like a note-taking or task-management app. But what makes it special is its AI that automatically organizes your notes, tasks, and data in appropriate folders and groups.
10. Notion AI
Use cases include:
- Note-taking
- Project management
- Text summarization
With Notion AI, you can analyze meeting notes to analyze next steps, generate summaries of long text, and surface key takeaways.
AI tools for UX design
11. Recraft.ai
Use cases include:
- Generative AI design
- Edit vector art
- Create icons and 3D images
Recraft is an infinite AI artboard, where you can generate and edit vector art, icons, 3d images and illustrations in a wide range of styles suitable for websites, print and marketing. It is free for everyone, and allows commercial use of the generated images.
12. Adobe Firefly
Use cases include:
- Generative AI design
- Text-to-image prompts
Only Photoshop has Generative Fill (beta), a mind-blowing generative AI tool that will activate your creative superpowers. Add, extend, and remove content from your images with simple text prompts. Then make it pixel-perfect, all in Photoshop.
13. Fronty
Use cases include:
- Building websites
- Image to HTML converter
Front is an AI-powered tool to create a website in a few minutes. Converts image to HTML converter. Get the HTML CSS code of your project in no time.
14. Illustroke
Use cases include:
- Generative AI design
- Website illustration
- Logos
- Icons
Stunning vector illustrations from text prompts. Create website illustrations, logos and icons in seconds with this advanced generative AI design tool.
15. Huemint
Use cases include:
- Color palette generation
Huemint is a color palette generator that uses machine learning to create unique color schemes for your brand, website, or graphic. It understands which colors are meant to be used in the final design and generates recommendations to help you apply them correctly.
16. Fontjoy
Use cases include:
- Font combo generation
A lot of designers already use Fontjoy, the AI-based font combination generator. Fontjoy follows a mapped out formula for pairing fonts together to find the best font combinations.
17. Jasper.ai
Use cases include:
- AI writing and design
- Illustration generation
- Copy generation
Jasper is a suite of AI tools available for creators and designers. One of the tools available on the platform is an AI art generator. Use Jasper to easily generate illustrations, backgrounds, and placeholder images for your design projects. It’s also useful for testing out concepts and ideas as well as finding inspiration for your designs.
“Big qual” AI data analysis tools
18. HeyMarvin
Use cases include:
- Qualitative research repository
- User interview data analysis
HeyMarvin is a qualitative user research platform for product design, research, and consulting teams to collect user research and analyze user interviews.
19. Kraftful
Use cases include:
- Summarizing user feedback for product teams
- Jira ticket writing
- Building to-do lists for product roadmaps
Known as “ChatGPT but for product research,” Kraftful gives you deep AI analysis of user feedback to learn what your users need and how to make your product delightful.
20. Research Qualboard 4.0
Use cases include:
- Qualitative research
- Response generation
- Automatic keyword extraction
- Concept identification
- Image tagging
One application in the new Qualboard 4.0 release is Smart Replies—a feature to help lighten the load for moderators. Just like messaging apps, it interprets the content of a post and suggests two or three likely follow-up responses or probes to save the moderator time when replying.
21. Dovetail
Use cases include:
- Qualitative research analysis
- Video transcription
- Sentiment analysis
- Structured data tagging
With Dovetail, you can upload anything—from customer interviews to product feedback—in any format. Tag key themes within data, uncover patterns, and capture insights—all within one tool.
22. Remesh
Use cases include:
- Qualitative text analysis
- Keyword extraction
- Text summaries
Remesh uses a range of AI techniques to manage, analyze and respond to large volumes of unstructured text data. Compared to a human moderator, using a tool like Remesh is much more efficient to help summarize content and extract keywords.
23. Speak.AI
Use cases include:
- Qualitative data analysis
- Transcription
- Audio, video, and text analysis
Speak.ai is an automated transcription service that also offers audio, video, and text analysis through ChatGPT-style prompts.
🌎✨ Want to explore the entire landscape of UX research tools? Visit the User Interviews 2022 UX Research Tools Map
Guardrails for using AI tools for user experiences
Whether you’re for or against AI tools, here are some guardrails to help you practice a healthy dose of reliance on AI tools. (And if you’re against using AI, hopefully these guardrails will help you feel more comfortable with the idea of AI tools!)👇
1. Don’t rely on only AI for data analysis.
AI can supplement your data analysis by summarizing notes you took during a qualitative user interview, but human judgment and understanding of social nuances of human behavior is necessary for true user insights.
2. Build a habit of questioning the validity of AI outputs.
AI is based on publicly available data sets, but UX research usually isn’t based on public data. Don’t rely on AI responses completely.
3. Don’t let AI make your work unoriginal.
AI can be cliche since it’s based on data that’s available to everyone. Use AI to automate brainless tasks so you can spend more time on the deep, creative work that requires original thinking.
4. Don’t let FOMO cloud your judgment when evaluating the value of AI tools for UX
Everyone is scrambling to make AI products or use AI tools. Is jumping on this bandwagon worth your time and money? Also, no technology is neutral. There are always second and third order consequences. Consider potential consequences before jumping all-in.
What AI tools can (and cannot!) do for UX research
There’s no denying that AI has its limitations. By recognizing these limitations for UX research, research teams can approach AI-based tools with a healthier dose of skepticism.
According to a study by NN/g that evaluates 4 different AI-powered UX research tools, AI insight generators severely lack:
- Context of research studies
- Citation and validation
- Performance and usability stability
- Detailed descriptions
Rather than replacing all parts of UX research with completely AI-reliant methods, use AI for the tasks that don’t require a researcher’s caliber of social understanding and empathy.
Here’s a brief overview of what AI tools can do for UX research and what they can’t do: 👇
In UX research, AI tools can:
- Help you find recent sources on your topic
- Summarize articles based on your needs
- Provide suggestions for UX research methods based on your goals
- Give suggestions on how to analyze data
- Streamline manual tasks like tagging, note-taking, project tracking, etc.
- Provide a general timeline for your UX research
In UX research, AI tools cannot:
- Summarize or analyze long bodies of text (limited)
- Detect and understand social nuances of human behavior
- Think like your users
- Generate new data
- Create an entire research plan
- Build your UX research methods for you
- Provide reliable, unbiased solution generation
- Understand the “why” of your research or design process
- Generate best practices
- Seek out user feedback and incorporate it into UX
Use AI tools for UX as supplements, not as a replacement.
The FOMO for AI tools is real, but it’s important to set guardrails for new tools that are constantly evolving and changing.
Instead of approaching AI tools for UX research with complete fear or dislike, it’s helpful to take the time to get familiar with AI and start incorporating it into your UX research practice in healthy doses.
Looking for a tool to automate your participant recruitment for UX research projects? User Interviews’s Recruit is the fastest and easiest way to recruit high-quality participants. With over 3 million participants in the User Interviews panel (and continuously growing 4.92% on average each month), you can get matched with your first participant in under 1 hour. Sign up for a free account to get started.
📕 Want to know the value of different UX research recruiting tools and methods? Dive into our recent ROI report: The ROI of User Research and Recruiting Tools: A Comparative Analysis
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