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
🤖 Curious about how AI tools like ChatGPT are affecting the UX research industry? The 2023 AI in UX Research Report (based on a survey of 1,000+ researchers!) is full of great data and insights about how researchers are currently using artificial intelligence, which tools they’re experienced with, and what they think about AI’s strengths and limitations.
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
“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.
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:
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.
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.
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.
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.
This AI tool helps generate user testing insights through eye-tracking. VisualEyes simulates eye-tracking studies and preference tests with 93% accurate predictive technology.
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.
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.
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.
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.
Stunning vector illustrations from text prompts. Create website illustrations, logos and icons in seconds with this advanced generative AI design tool.
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.
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.
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.
HeyMarvin is a qualitative user research platform for product design, research, and consulting teams to collect user research and analyze user interviews.
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.
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.
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.
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.
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
🧰 There’s so much UXR software on the market, it can be difficult to choose. Discover the tools your fellow researchers use in the 2023 UX Research Software Report (based on a survey of 900+ researchers!).
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.
Rachell is a (former) Content Marketing Manager at User Interviews. Content writer. Marketing enthusiast. INFJ. Inspired by humans and their stories. She spends ridiculous amounts of time on Duolingo and cooking new recipes.