Top AI Tools Used by UX Professionals
Summary: A survey of UX professionals found them using 93 different AI tools. The giant of the lot is ChatGPT, used by 83%, after which usage numbers drop quickly for more specialized tools. 12 UX-specific AI tools were fairly popular. The overlap in popular AI tools between UX professionals and the general public is low, due to specialized use cases when employing AI to assist in UX work.
Now that we’re in Year 2 of the AI revolution, enough user experience professionals have experience with using AI in their work that it makes sense to document what tools they use. To find out, I surveyed my newsletter subscribers and social media followers in March 2024. This recruiting method would be biased for many other purposes, but for this project, my sampling works well since I want to discover what UX professionals currently use. The findings won’t generalize to business professionals or knowledge workers in general.
Of course, Year 2 is still early in the game, and new tools appear literally every day. I would not be surprised if the outcome of a similar study next year — let alone in a decade — were to be different. But for now, this is the state of AI in UX.
There’s a profusion of AI tools, with more appearing every day. But which ones are used for UX work? Let’s find out! (Midjourney)
If you are still not using AI in your work, don’t despair. Yes, it would have been better to start last year when I wrote that UX needs a sense of urgency about AI. If you started using AI last year, then you would have accrued a year’s experience by now and been qualified for a higher-class job. (Currently, tech jobs with an AI component offer about 15-20% higher salaries than jobs in the same field without an AI component.)
Read the article on how to get started using AI for UX. Note my slogan: Start small, start now.
Start small, start now. This beats planning out a grandiose project and then being paralyzed with fear of the consequences of doing something wrong. Expect to make mistakes in the beginning. That’s OK, especially when testing AI out on something small. Start today. You can always scale up to higher ambitions in a week or a month when you have gained some experience. (Dall-E)
Average Use = 2.5 AI Tools
158 respondents completed my survey. Thank you!
3% of respondents indicated a main professional focus other than user experience, whereas 97% of respondents were UX professionals. Given the small number of people with a main job focus on something else, I have not analyzed their responses separately.
The UX people were divided roughly evenly between designers (28%), researchers (22%), and generalists (26%). 15% were UX managers or executives, and a few percent focused on UX writing or other specialties.
In total, the respondents mentioned that they used 396 AI tools in their work, or an average of 2.5 tools per person. The true average is probably marginally higher, because the survey instrument only asked for information about up to 5 tools per person. Thus, anybody who uses 6 or 7 AI tools would not have named their last tools.
Using 2-3 AI tools is the norm for most UX professionals who responded. (Midjourney)
However, only 9% of respondents listed 5 tools, compared with 21% who listed 4 tools. So I suspect that the drop from 5 to 6 tools would also have been large, meaning that very few UX people use more than 5 tools.
People are likely to have experimented with many more AI tools than 2.5, which is the average number of AI tools in regular professional use. Sadly, many of the new AI tools that launch during the current gold rush period are not that useful, so people often try them once without adding them to their regular toolkit.
I hope that the AI toolkit will expand in the future, as we get better and more useful options.
Top Tools: 1 Giant, Many Dwarves
In total, respondents mentioned using 93 AI tools. But only 15 tools were used by at least 2.5% of the respondents. They are shown in the following bar chart:
These 15 AI tools were used by at least 2.5% of the UX professionals in the survey.
It’s obvious from the chart that ChatGPT is a giant among AI dwarves. It’s immensely bigger than anything else. This conclusion holds even stronger when we consider that Microsoft Copilot uses GPT as its main AI foundation model and that Dall-E is mostly used as a feature within the ChatGPT user interface.
Midjourney and Perplexity won silver and bronze, respectively.
ChatGPT is the one and only giant in the AI field, in terms of usage by UX professionals. It was used by a whopping 83% of respondents — five times as much as the second-rated AI tool for UX. (Midjourney)
As a general AI foundation model, ChatGPT is being used for an extremely wide range of tasks within UX work:
Writing and editing: Many professionals use ChatGPT for copywriting, polishing written content, generating summaries, and improving the overall quality of their writing, especially when working in non-native languages.
Ideation and brainstorming: ChatGPT is frequently used as a tool to stimulate creative thinking, generate ideas, explore concepts, and provide inspiration for various UX-related tasks, such as design, feature development, and problem-solving.
Research and analysis: UX professionals leverage ChatGPT to aid in user research, such as generating interview questions, removing potential bias and ensuring questions are worded effectively, analyzing qualitative data (e.g., survey responses, user feedback), and identifying themes and patterns. In fact, I developed this very list in this way.
Content creation: ChatGPT is utilized to generate placeholder text for prototypes, create personas, user scenarios, and journey maps, and draft UX-related documents like research plans, reports, and presentations.
Communication and collaboration: Some professionals use ChatGPT to draft emails, prepare for meetings and workshops, and facilitate communication with stakeholders and team members.
Some respondents found other ways to incorporate ChatGPT into their work. For instance, a few practitioners have experimented with using ChatGPT to extract text from complex images, such as tables filled with data, to aid in the redesign of intricate user interfaces.
Some professionals even create custom GPT models to serve as UX design coaches or assistants, providing targeted advice and guidance. These specialized applications demonstrate the versatility and potential of AI in enhancing even more aspects of the UX process.
The sentiment among UX professionals regarding ChatGPT is generally positive, with many acknowledging its potential to save time, enhance productivity, and provide valuable assistance in various aspects of their work. However, there are some concerns and limitations:
Accuracy and reliability: Some professionals question the accuracy of ChatGPT’s outputs and emphasize the need to validate information independently.
Generic or verbose responses: ChatGPT's responses can sometimes be overly generic, wordy, or lack the desired specificity and depth.
Lack of contextual understanding: ChatGPT may struggle to fully grasp the nuances and context of certain UX-related inquiries, leading to less relevant or applicable suggestions.
Iterative process: Achieving the desired results often requires users to refine their prompts and engage in an iterative process with the tool.
Despite these limitations, respondents generally viewed ChatGPT as a valuable addition to their UX toolkit, providing assistance, inspiration, and efficiency gains in their daily work.
There’s a big drop from the top tool to the second-most popular, Midjourney, which was used by 17% of respondents. (This image, as most other images in this article, was made with Midjourney itself.)
As a specialized image-generation tool, Midjourney is used much more narrowly than ChatGPT, but still has a range of applications:
Creating mood boards and visual inspiration for brainstorming and ideation
Generating illustrations and graphics for user interfaces, such as fun and positive feedback elements
Producing images for presentations, slide decks, and marketing collateral
Blending real-life product photos with AI-generated images to create stylized visuals
Generating persona images and visuals for storytelling
Rendering high-quality images for various purposes
Assisting in logo creation and initial concept brainstorming for architectural ideas
UX professionals appreciate Midjourney's ability to quickly generate rough concepts and its potential to save time compared to searching through stock imagery. They also praise the tool’s ability to generate images that accurately convey nuanced situations and its impressive results when prompts are well-written.
However, some challenges and concerns were also mentioned, such as the need for trial and error to achieve desired results, the lack of specific controls for adjusting images, and the difficulty in creating consistent images even for experienced users.
UX professionals leverage Midjourney to exercise their imagination, explore creative possibilities, and generate visually appealing content to support their design processes and presentations. AI-powered image generation is a valuable addition to the UX toolkit, enabling designers to quickly create and iterate on visual concepts and enhance their overall design workflows.
Maybe the biggest surprise is that Perplexity took the bronze medal, being used by 13% of respondents. See my article about why custom-written answers optimized for the individual user are beating old-school search engines. (Midjourney)
Perplexity is being used as a research and information-gathering tool in user experience work. The primary applications include:
Conducting initial research and gaining general knowledge about a domain before stakeholder interviews or after receiving a client briefing
Answering complex questions related to software patterns, workflows, and unfamiliar terms used by clients
Performing competitor analysis and quick research on various topics
Generating summaries and providing context for previous conversations
Creating checklists and ensuring completeness of information
Replacing or enhancing traditional web search engines like Google
UX professionals appreciate Perplexity for its ability to provide concise answers, cite sources, and suggest follow-up questions.
Top 3 UX-Specific Tools: FigJam, Wondering, and Miro
The top-3 AI tools for UX work are all generalist tools that are widely used outside the UX field. There’s a big drop in usage numbers from the big-3 to UX-specific AI tools which are not as widely used yet.
FigJam is commonly employed for collaboration, brainstorming, ideation, and planning. Many respondents utilize FigJam for clustering data, creating templates, and organizing workshops and meetings. The AI-powered features, such as JamAI and JamBot, are used to generate layouts, charts, and flow diagrams, which can save time and provide a starting point for further refinement.
Some respondents find FigJam’s AI-generated outputs helpful for synthesizing and grouping data, while others note that the results can be hit or miss, requiring manual corrections. FigJam is also used for research data analysis and categorization. While some users find FigJam to be a powerful tool for expediting work and enhancing collaboration, others note that its adoption is primarily limited to design and technology teams.
Wondering is being used as a tool to streamline and accelerate various aspects of user research and testing. The AI-powered platform is employed to conduct semi-structured user interviews, saving time and resources that would otherwise be spent on scheduling and interviewing users manually. UX researchers use Wondering to test new designs and concepts, gather user feedback quickly, and iterate on their work without the need for building full prototypes. The tool’s ability to generate studies based on AI prompts and analyze results is appreciated, although some users note that the automatic analysis feature needs improvement.
Wondering’s AI also enables user interviews to be conducted in different languages, making it valuable for companies that operate across multiple markets. The in-product integration allows for targeted studies based on user behavior and actions within the product. Overall, Wondering is seen as a cost-effective and time-saving solution for UX professionals looking to scale their user research efforts, with a responsive support team and a focus on continuously evolving the tool to meet the needs of the product community.
The AI features of Miro are primarily used to support data synthesis, analysis, and organization in user experience work. Respondents employ these AI capabilities to streamline the process of affinity mapping, clustering, and thematic analysis of user research data, such as interview transcripts and workshop feedback. The AI functionality helps in quickly categorizing topics, identifying trends, and organizing insights, which can significantly speed up the analysis process.
However, many respondents emphasized the importance of carefully reviewing the AI-generated output, as it may miss nuances in meaning and intent. Despite this limitation, the AI features are generally considered helpful in providing a solid starting point for further refinement. The AI capabilities of Miro are valued by UX professionals for their ability to enhance efficiency and support key aspects of the research process, such as synthesis and analysis.
UX Professionals’ AI Tools vs. the General Public
The venture capital firm A16Z has published a list of the top 50 AI products, ranked by unique monthly visits to their website. This metric is obviously dominated by the general public, so it’s interesting to see how it compares with my new data about UX professionals’ top AI tools.
The following table compares the top 20 AI tools for the general public with their popularity among UX professionals for work use:
Top 20 AI tools for the general public in January 2024, according to A16Z, together with the rank for those same products for use in UX work.
We can see that out of the 20 most popular AI products for the general public, only a third (7) were popular for UX work. The two most striking differences are:
Midjourney is the second-most popular tool for UX work, but only number 14 for the general public. This makes sense since UX professionals do much more design than average people and also use images for many other purposes, such as storyboards and persona documents.
Character.AI is the third-most-popular tool for the general public but is not used at all for UX work. This also makes sense, since it’s an AI companion with applications such as “virtual girlfriend” and “virtual fitness trainer,” which are currently less useful for professional purposes.
9 Use Cases for AI in UX Work
Respondents were asked to briefly describe their use cases for AI. Here are the 9 main categories, sorted by frequency. Are you using AI for all of these things? If not, take inspiration from the respondent quotes and start cracking. (You can still apply my motto to “start small, start now” by initially picking a small task in whatever category you’re currently not using AI for.)
1. Content Generation and Writing (48 respondents)
UX professionals use AI for various writing tasks, including copywriting, editing, summarizing, and generating content for different purposes.
"Writing emails, case studies, dummy copy, brainstorming"
"Copywriting and ideation/brainstorming"
"Expediting content tasks like generating summaries, finding gaps, and helping improve content with plain language."
2. Research and Analysis (40 respondents)
AI tools are used to assist in research tasks, such as data analysis, transcript analysis, and desk research.
“Generating project and research outlines, generating first drafts of discussion guides, getting it to analyze transcripts and more“
“Aid in analysis of large unstructured data sets. Ex. transcripts, open end responses when n>10.“
“Good for research data cleaning: It can convert raw data into formatted databases for further analysis”
3. Ideation and Brainstorming (35 respondents)
UX professionals leverage AI for generating ideas, brainstorming, and conceptualizing solutions.
"Brainstorming and planning"
"Ideate workshop/meeting structure/agenda, summarise meeting insights"
"Quick ideation, creation of wireframes, generating alternative UI solutions"
4. Image Generation and Manipulation (32 respondents)
AI tools are used for creating, editing, and manipulating images for various UX purposes, such as mockups, prototypes, and presentations.
"Image generation for slides, presentations, illustrations for journey maps, concepts and storyboards"
"Persona images, illustrations for storyboarding"
"Creating visual content"
5. General Assistance and Support (27 respondents)
UX professionals use AI as a general-purpose assistant for various tasks, such as answering questions, providing advice, and offering support.
"Assistance of all kinds. Synthesize user interview raw notes, think of potential roadblocks for features, help with fleshing out personas. Helps with ideation and sparking thoughts even if I'm not actually using what it comes up with."
"Ask it anything about essential basics but confusing and/or difficult things, and it often provides instant and accurate information. This is while traditional search gives confusing and misleading results."
"A good General UX tool that has a lot of case study knowledge embedded. Provides useful UX advice and feedback."
6. Planning and Organization (14 respondents)
AI tools are used for planning projects, organizing tasks, and structuring information.
"Define activities and planning strategy"
"Help me plan research projects and creating outlines for research reports and general questions I have about research"
"Planning and scheduling"
7. Prototyping and Wireframing (11 respondents)
UX professionals use AI for creating quick prototypes, wireframes, and mockups.
"Quick wireframe mockups. I put in a basic feature description and get quick wireframe to use as inspiration or for talking points."
"I used it to generate low fidelity wireframes with their "sketch" functionality."
"For wireframing lo-fi and architecture"
8. Collaboration and Workshops (9 respondents)
AI tools are used to facilitate collaboration, workshops, and co-creation sessions.
"Collaboration, management"
"Collaboration, team management, research repository"
"Workshops, Customer Journeys, Product Designs, collaboration"
9. Transcription and Translation (6 respondents)
UX professionals use AI for transcribing interviews, meetings, and translating content.
"Transcribing calls, getting notes, analyzing interviews quickly."
"Transcripts, meeting recaps"
"Translation and writing messages. I also used it to better understand concepts that I'm not familiar with"
Miscellaneous (14 respondents)
Various other use cases that do not fit into the above categories, such as personal use, job search, and experimentation.
"Personal stuff travel plans"
"looking for work"
"Playing and exercising my imagination."
Top UX-Specific Tools
Many of the most popular tools for UX work are general AI tools that are not specific to design or UX work. Tools like ChatGPT, Midjourney, Perplexity, Gemini, Dall-E, Claude, Grammarly, Photoshop, and Leonardo have many more uses than user experience. And yet, they are among the most popular tools for UX work, showing the benefits of applying the top generalized tools for specialized purposes.
The usefulness of general AI tools is especially apparent for the top AI use for UX professionals, content generation/writing, and also for the number 3 and 4 uses, ideation and image generation.
Other top use cases may benefit more from specialized tools. Also, even though user interface design itself was not mentioned as a top use case, this may change as better tools are launched. A few current Generative UI tools were mentioned as infrequently-used tools:
Relume Site Builder (2.5%)
Galileo AI (1.9%)
UIzard (1.9%)
The other top UX-specific tools used by at least 1% of respondents were:
FigJam (9.5%), jump-start synthesis/grouping and summarize notes/activities
Wondering (7.6%), conduct user interviews
Miro (5.1%), affinity mapping and synthesis of user data
Dovetail (2.5%), transcribing, organizing, and analyzing user research sessions
Loopplanet (1.9%), user research
Notion AI (1.9%), summarizing work and planning
Frontitude (1.3%), guidelines
Mural (1.3%), collaboration and design thinking workshops
Otter.ai (1.3%), transcription
A very large number of specialized AI tools are employed for UX work, beyond the big general tools. (Midjourney)
What’s Good About AI Tools in UX Work
Respondents were asked what was particularly good about their AI tools. The 62 responses clustered as follows:
Time-saving and efficiency (21 statements)
Speeds up and automates various research tasks like survey question phrasing, data analysis, transcript analysis, card sorting, etc.
Frees up time to focus on more strategic work
“Huge time saver, great programming instruction, basic layout and design critiques.”
Useful starting point and ideation aid (17 statements)
Helpful for brainstorming, outlining, and generating initial drafts and ideas to iterate on
Provides a good foundation to build upon and refine
“Fast brainstorming for a feature idea.”
Quality and capability of outputs (10 statements)
Impressed with the overall quality, power and flexibility of the AI tools
Specific callouts for quality of images, transcriptions, summaries, writing
“Translates user interviews into different languages, so that we can interview users across different markets. It's been a game changer for us.”
Integration and ease of use (8 statements)
Many tools are easy to access, intuitive and user-friendly
Can be used in existing workflows and across apps
“I love it because I can use it almost in any app on my laptop.”
Helpful for specific use cases (6 statements)
Effective for particular tasks like image generation, user testing, organizing research data
Solves niche needs well
“Really good at extacting relevant parts of the call and summarizing it into digestible notes.”
What’s Bad About AI Tools in UX Work
Respondents were asked what was particularly bad about their AI tools. This prompted 55 responses, or slightly fewer than the positive comments. The negative comments clustered as follows:
Inconsistent or inaccurate outputs (19 statements)
Results can be hit or miss, obvious errors, lack of nuance
Requires human review and correction
“Sometimes answers are wrong, or in outer space.”
Lack of specificity and control (15 statements)
Difficult to get tailored, precise results even with specific prompts
Limited ability to fine-tune and direct the AI
“Hard to tailor specifically to what I want, usually requires multiple attempts.”
Usability issues with the AI tools (10 statements)
Interfaces can be confusing, glitchy or lack key features
Poor discoverability of full functionality
“The UI needs a lot of help.”
Generic or unoriginal outputs (6 statements)
Results can be cliché, repetitive or lack true creativity
Sounds like obvious AI rather than human-like
“Copy generated from "nothing" isn't good. It's better at improving or suggesting alternatives to copy that already exists”
Cost and usage limits (5 statements)
Some tools are expensive or require paid plans for full features
Free versions have usage caps
“It's expensive, and I can't afford another subscription, so I rarely use it.”
What UX Professionals Think About AI in UX
Several respondents provided general comments. Here are the main categories, sorted by frequency. Again, positive conclusions slightly outweighed negative perspectives:
Potential and Benefits (17 statements)
UX professionals see the potential and benefits of AI tools in their work, such as saving time, increasing efficiency, and assisting with various tasks.
"AI tools can save a designer a tremendous amount of time and speed up processes when used correctly"
"It's extremely useful as a tool. Not as a replacement for a technical author."
"For UX practitioners, artificial intelligence has the potential to dramatically improve our findings and give us more time to put those discoveries to use solving real-world problems."
Limitations and Concerns (12 statements)
UX professionals expressed concerns about the limitations of AI tools and their potential impact on the field.
"AI is eliminating some previously time-consuming tasks; this trend will continue reducing the overall need for UX professionals."
"It's over-rated and seems like people are trying to cash in on a fad and misleading promises. How skilled will UX Designers be if they learn their craft through shortcuts using A.I. apps instead of really learning how to do something?"
"The slow process of certain research tasks, like transcribing an interview, is sometimes necessary to find the deepest insights. The brain needs time to digest the data and rethink the conversation—using AI to transcribe or speed up other tedious tasks risks losing those insights."
Personal Experiences and Usage (11 statements)
UX professionals shared personal experiences and how they use AI tools in their work.
"I am starting to use some plugins in Figma, but just testing. I am really interested in AI that allows to create low-fi design for teams alignment and stakeholders. I tried some but not very good at the end. I also miss tools that allow the analysis of research results in an accurate way and without having to try thousands of prompts (maybe they exist but I don´t know yet)."
"I have personally found AI helpful at overcoming bias in sorting through user research data. When Miro first introduced some AI functionality - I ran it on data I had manually sorted, and each time I did - it discovered things I had overlooked, and it made connections I hadn't thought of."
Need for Improvement and Collaboration (8 statements)
UX professionals expressed the need for AI tools to improve and for the design community to collaborate on their development.
"A human suggestion? haha...My thoughts are that we human designers and design educators should perhaps talk together within the design community — as to how it works and does not, what lacks and how to make AI tools better for everybody to fit our needs to help users."
"We need one that could be able to read results from different platforms and organize the info."
Adoption and Integration (5 statements)
UX professionals discussed the adoption and integration of AI tools into their workflows.
"I foresee a future where AI is integrated into every aspect of work, especially for more mundane tasks in UX work."
"Yep, AI is a tool just like the other ones.. it needs to be paid attention to and incorporated for 1st drafts, idea generation when by yourself, because some of it will replace many parts of what we do to some people.... the speed will overshadow the quality of results. So, pay attention and adapt to change."
Learning and Staying Updated (5 statements)
UX professionals expressed the need to learn and stay updated on AI tools and their applications in the field.
"Always on the lookout for the latest and greatest tools for UX. Can't wait to find out what other tools my colleagues out there are using. Thanks for the survey!"
"I think there must be some tools I miss, as it takes so long to research them and find uses."
"I would like to read more examples about specific tools and how to use them or integrate them into our workflow, it all seems like bits and pieces for now"
The AI-human partnership is the way forward for UX work. (Ideogram) How do you visualize that somebody is a designer in a simple cartoon? It’s almost as hard as visualizing an AI (which, by convention, is now almost always shown as a robot). Here, the UX designer is holding an oversized drawing pencil, which works better in this naïve style than some other physical design tools I tried.
About the Author
Jakob Nielsen, Ph.D., is a usability pioneer with 41 years experience in UX and the Founder of UX Tigers. He founded the discount usability movement for fast and cheap iterative design, including heuristic evaluation and the 10 usability heuristics. He formulated the eponymous Jakob’s Law of the Internet User Experience. Named “the king of usability” by Internet Magazine, “the guru of Web page usability” by The New York Times, and “the next best thing to a true time machine” by USA Today. Previously, Dr. Nielsen was a Sun Microsystems Distinguished Engineer and a Member of Research Staff at Bell Communications Research, the branch of Bell Labs owned by the Regional Bell Operating Companies. He is the author of 8 books, including the best-selling Designing Web Usability: The Practice of Simplicity (published in 22 languages), the foundational Usability Engineering (26,813 citations in Google Scholar), and the pioneering Hypertext and Hypermedia (published two years before the Web launched). Dr. Nielsen holds 79 United States patents, mainly on making the Internet easier to use. He received the Lifetime Achievement Award for Human–Computer Interaction Practice from ACM SIGCHI and was named a “Titan of Human Factors” by the Human Factors and Ergonomics Society.
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Thanks for featuring us at https://wondering.com Jakob!
I also recommend https://listenlabs.ai/