25 game-changing AI tools for UX research

AI tools are becoming more sophisticated, and UX researchers and designers can use them to find innovative ways to enhance their work.

Let’s explore the strengths and limitations of AI tools so that you can unlock their potential and create incredible solutions for your customers.

The exciting thing about modern AI tools is their versatility. UX researchers can incorporate them into their workflows to better understand user needs and behaviors.

AI has long been used to identify patterns in user behavior and help create more personalized user experiences—but these tools are becoming more advanced. Meanwhile, large language models (LLMs) and their customer tooling help quickly and easily process data from user interviews, surveys, and behavioral analytics.

AI-powered tools are quickly evolving, meaning new categories of solutions are constantly emerging. We can generally group these tools into two categories:

1. Insight generators

2. Collaborators

Here’s how they fit into the UX workflow:

Insight generators

These tools process and analyze large amounts of user data to uncover patterns and trends. They include:

• Natural language processing (NLP) systems that analyze user feedback and reviews

• Behavioral analytics platforms that track and interpret user interactions

• Sentiment analysis tools that gauge users’ emotional responses

• Pattern recognition systems that identify common user paths and pain points

• Automated survey analysis tools that process qualitative feedback at scale

Collaborators

AI collaborators function as team members, reducing the workload of UX professionals. Here are some examples:

• AI-powered design assistants that generate UI variations

• Automated testing tools that simulate user interactions

• Research planning tools that help structure studies and generate interview questions

• Transcription and analysis tools for user interviews

• Collaborative platforms that facilitate remote user research sessions

Here’s a look at some of the top AI tools for UX research.

Miro

Teams can use Miro, an AI-powered collaboration platform, to organize and synthesize information on digital whiteboards.

The tool can automatically arrange sticky notes into logical groupings, suggest categories for affinity mapping, refine rough sketches, and help generate user journey maps. It can also summarize the results of a brainstorming session and turn them into actionable insights.

Dovetail

Dovetail is a powerful customer insights hub supercharged with AI tools.

UX researchers and designers can use Dovetail to automatically transcribe user interviews, identify key themes across research sessions, and tag and categorize findings.

Powered by AI, Dovetail can perform sentiment analysis on user feedback, instantly uncover insights hidden in complex customer data, accurately transcribe customer feedback in over 40 languages, summarize and highlight key moments in customer feedback, and generate digestible reports for stakeholders.

Maze

User research platform Maze integrates with your favorite design tools to help with prototype testing. Its AI-powered functionality also aids user testing, speeding up the process by writing effective questions and insightful follow-up questions.

Maze’s AI tools make searching through customer insights easy, as they can quickly find patterns in data from open-ended questions. This can help your UX team quickly discover and solve usability issues.

Notably

Notably is a research repository and analysis platform that helps teams organize and glean insights from user research data.

Its AI features transcribe user interviews automatically and generate smart tags from research sessions. The platform can also analyze sets of interviews to identify patterns, summarize research findings, and highlight relevant connections between studies. Notably combines all these insights into reports that stakeholders can use to quickly get up to speed.

QoQo

QoQo is an all-in-one user research platform for remote user testing and feedback collection. Its AI features enable you to automate participant screening and recruitment, matching studies with ideal participants based on demographic and behavioral data.

It can analyze participant responses in real time with its natural language capabilities, identifying inconsistent answers and high-quality participants. QoQo can then help generate initial insights and categorize findings thematically.

ChatGPT

ChatGPT has become a versatile tool for UX professionals. It can help create user personas, write survey questions, and brainstorm user scenarios. With its deep contextual understanding, it can rapidly prototype content variations and generate realistic placeholder content for wireframes.

Researchers frequently use ChatGPT to help analyze qualitative data and find patterns in user feedback.

UserDoc

Document management platform UserDoc helps businesses create user-facing documentation and knowledge bases.

The tool can read your documentation, find gaps in coverage, and pinpoint potential improvements for clarity. It can help generate clearer explanations for complex concepts and flag areas of the documentation that users may struggle with.

UserDoc can also look at the source code of software products and generate first drafts of documentation.

Grain.co

Grain is a collaborative video research platform for capturing, organizing, and sharing insights from user interviews and customer conversations. Its AI tools automatically transcribe conversations and generate highlights based on key moments, emotions, and topics. It can work across interviews, identifying patterns that emerge from multiple customers.

Grain’s AI can quickly search through hundreds of hours of recordings to find specific moments, making it easier to build compelling research narratives and share findings.

Otter.ai

Otter.ai’s AI meeting assistant integrates with your workflow to convert speech to text in real time. It transcribes meetings, generates summaries, and extracts meaningful insights from the transcriptions.

While this functionality is helpful in your business’s day-to-day operations, it can also help UX teams specifically. They can use Otter.ai to detect meaningful moments during customer interviews or focus group discussions, extract trends, and suggest potential insights by analyzing multiple meetings.

Neurons

Formerly known as VisualEyes, Neurons is a powerful AI-vision platform that enables UX teams to make better design decisions.

The tool provides feedback on your visual designs and generates an attention map, highlighting areas likely to draw the user’s attention. It evaluates color schemes, typography, layout, and other visual elements to provide insights and predict likely emotional responses and interaction behaviors.

The tool can give meaningful feedback on accessibility, brand consistency, and potential usability issues, allowing teams to optimize designs earlier, minimizing the need for extensive A/B testing.

SciSpace Copilot

SciSpace Copilot is a browser extension that reads complex research papers and technical documentation, summarizing them to make them more digestible.

UX designers can use the tool to parse academic papers about user behavior, cognitive psychology, and other industry-related fields. SciSpace Copilot’s plain-language summaries accurately highlight methodological insights and suggest practical applications, allowing you to make informed UX choices.

Mem

Mem is a next-generation note-taking app built to take advantage of LLMs. It draws knowledge from your notes to function as a custom chatbot, finding answers, summarizing insights, and drafting relevant content.

UX designers can use Mem with notes from user interviews or research. It can provide insights into user experiences, tag and categorize notes, create interview summaries, and find relevant insights from past research to inform current projects.

Notion AI

Notion is a popular workspace platform with an integrated AI assistant that provides sophisticated document creation and management capabilities. It can help create research plans, generate user personas, and summarize feedback sessions.

Notion AI can detect any weak spots in your UX documentation, suggesting improvements that upgrade the user experience. As the number of participants and projects grows, the tool can help keep things organized by bringing together related items.

Recraft.ai

Recraft.ai is a specialized AI design tool that uses text-to-image AI to bring visual design elements to life from simple descriptions. UX designers can quickly mock up multiple variations of prototypes for rapid iteration and A/B testing. The platform enables you to create logos, icons, characters, ads, and even stock photos for use on websites and other media.

Adobe Firefly

Adobe has added a family of creative generative AI models to their Creative Cloud applications. UX designers can use Adobe Firefly to quickly generate UI assets, textures, and design variations, maintaining brand consistency.

The tool is ideal for quickly prototyping different visual directions, creating custom icons and illustrations, or generating placeholder text for mockups.

Fronty

Fronty is a specialized AI tool that transforms screenshots or images of websites into clean, production-ready HTML and CSS code. UX designers can use it to transform a design mockup into a functioning website quickly. The tool analyzes the visual layout in the screenshot and generates quality, responsive code that follows modern web development best practices.

Illustroke

Illustroke is another text-to-image generative AI tool. It creates scalable vector graphic (SVG) illustrations rather than raster images.

The tool can quickly generate custom vector graphics and icons that match any project’s style. Its SVGs are easily modifiable, meaning you can create consistent visual elements across various user interfaces with minimal effort.

Huemint

Huemint is an AI-powered color palette generator that helps UX designers create harmonious, attractive color schemes.

It features color palettes for brands, websites, dashboards, and more. Each features a mockup to easily visualize how the colors would look on your site or product. You can also upload an image of a design and have the software change the colors directly for even better visualization.

The tool can generate unlimited variations while maintaining brand consistency.

Fontjoy

Fontjoy does for fonts what Huemint does for colors. It uses machine learning to identify complementary typeface combinations. The algorithm understands typography principles, such as contract, rhythm, and visual hierarchy.

UX designers can use Fontjoy to get a quick start on their projects without the endless trial and error of finding the right combination of typefaces.

Jasper.ai

Jasper.ai is an AI writing assistant fine-tuned for marketing copy, content, and documentation. It can create messages that adhere to a specific brand voice, making it a great way for UX teams to create microcopy, error messages, onboarding flows, and more.

The tool is trained on successful UX copy patterns, allowing it to provide effective copy, whether creating new material or refining old work.

HeyMarvin

HeyMarvin is a dedicated UX research and design platform that brings all your user research together. Its AI tools scan the information to identify patterns and insights, generate summaries, and suggest follow-up questions for user interviews.

Machine learning is woven into the product, meaning it can categorize research findings, prioritize feature requests, and more.

Kraftful

Kraftful is a product optimization platform that helps UX design teams turn user feedback into actionable insights.

It collects data from sources like app reviews and support tickets, using AI to identify trends and priorities. The tool categorizes feedback, highlighting key requests and pain points, helping teams focus on impactful improvements.

Kraftful integrates with tools like Jira and Slack, streamlining workflows by converting insights into tasks. With multilingual support and auto-translation, Kraftful ensures accessibility for global teams.

Qualboard 4.0

Qualboard 4.0 is a digital platform for conducting long-term qualitative research studies and online focus groups. It analyzes participant responses in real time, providing actionable insights. The tool’s natural language capabilities enable it to identify emerging topics and generate suggested follow-up questions during user meetings.

Remesh

With Remesh, UX teams can obtain insights from questions in real time with audiences of up to 1,000 people.

Interviewers can use Remesh’s text-based tools to ask questions, receive votes, and analyze answers. The tool guides the conversation in a meaningful direction, enabling researchers to pivot in response to emerging insights.

Speak

Speak is an audio and video analysis platform originally designed for communication research and coaching. It has expanded to include many useful features for UX designers.

The platform’s AI meeting assistant can automatically record, transcribe, and analyze meetings in any language. It easily integrates with many popular meeting platforms, making it an easy addition to your workflow.

As AI becomes more ubiquitous, many businesses are rushing to implement it into their workflows. However, if you don’t integrate it thoughtfully, these tools could become more of a hindrance than a help.

Plan integrations carefully to get the most out of AI tools for UX research. Start by identifying repetitive tasks AI can automate, such as interview transcription and survey response analysis. Establish processes for validating AI-generated insights with human expertise and traditional research methods to ensure accurate and relevant results. This creates a feedback loop where AI tools complement rather than replace human decision-making.

Like any tool, the key to using AI effectively is understanding its limitations. AI tools excel at:

• Quickly processing vast amounts of data

• Identifying patterns and trends in user behavior

• Generating initial design concepts and variations

• Automating routine tasks and analysis

• Providing quantitative insights from qualitative data

However, right now, AI tools cannot:

• Understand complex human emotions and motivations

• Provide genuine empathy or emotional intelligence

• Make nuanced ethical decisions about research practices

• Replace human creativity and intuition

• Fully comprehend cultural context and subtleties

AI is an assistant, not a manager. Use it to supplement your work, other tools, and human input. Don’t outsource every decision to an AI tool.

Allow the AI to handle data-intensive tasks while still relying on humans for final interpretation and strategy. Importantly, this approach maintains a human connection with users. Building a genuine connection with them is still the best way to understand and adapt to their needs, but AI tools can help increase the speed at which that’s possible.