The 12 top AI tools transforming user research

Great research drives great products, but the process is often a bottleneck.

AI tools automate the tedious work of transcribing, tagging, and thematic mapping, allowing you to focus on strategic ‘aha’ moments and deliver high-quality insights while the project momentum is still high.

In this guide, we list the 12 best AI tools for UX research based on their specific research capabilities, pricing structures, and user feedback. We prioritized platforms that integrate seamlessly into your existing workflows and offer the highest accuracy for qualitative analysis.

AI is speeding up processes across a wide variety of product development practices—and UX research is no exception.

According to our 2025 Future of User Research Report, UX professionals use AI for:

And for good reason: teams integrating AI into their workflows are seeing measurable benefits. They’re handling large datasets faster, delivering research findings more quickly, and scaling their efforts without increasing headcount. Plus, AI is also helping teams personalize user experiences more effectively by processing and responding to user behavior at scale.

In practice, most teams lean on a few core types of AI tools:

Adding some user research AI tools to your research process can make a big difference—whether it's taking care of repetitive tasks or digging deeper into user behavior. Here are our top 12 AI-assisted tools for UX research, and what they’re best for.

Maze is an AI-first user research platform that empowers teams to conduct in-depth, remote user research with a comprehensive suite of research methods. Alongside these research methods, Maze facilitates research with various AI capabilities and solutions.

Maze’s AI moderator automates user interviews at scale. You set the goals, target audience, and the questions you want to ask. The moderator uses that guide to talk to participants one-on-one, asks follow-ups when answers are vague or too short, runs multiple interviews in parallel across time zones, and gives you a clean transcript and recordings to review.

Maze AI also speeds up the research analysis process. It summarizes sessions and extracts key insights so you can move faster from raw input to clear findings and recommendations.

Maze offers pricing options for organizations and product teams of all sizes. There’s a Free plan for individuals looking to kickstart user research and testing, and Enterprise options for teams looking to scale research.

The Enterprise plan provides added features for greater flexibility, including custom study quantities, additional research solutions—like interview studies, card sorting, and tree testing—and access to mobile testing through the Maze Participate app.

QoQo is a Figma-based discovery assistant that helps you get from a blank canvas to a structured research plan. It analyzes your product idea to flag possible friction or accessibility risks, turns messy FigJam/Figma notes into affinity-mapped themes, and generates contextual interview scripts based on the user personas it builds with you.

QoQo uses OpenAI-based, knowledge-retrieval AI trained on common behaviors, industry patterns, and UX best practices. So it’s ideal for early discovery, briefing, and de-risking concepts before you start primary research.

QoQo offers a suite of user experience tools, including persona generation and journey mapping, for $7 per month for one user.

Synthetic Users is an agentic research platform that lets you run simulated user interviews with AI research participants modeled on your target segments. You define the audience, upload your own domain data, and Synthetic Users generates participants with consistent personalities, vocabularies, and pain points.

It’s best used to pressure-test ideas, messages, and flows before you spend time and budget on real recruitment, and to explore ‘what if’ scenarios you’d never get to run at scale with human users.

Synthetic Users costs roughly $2–27 per simulated user, with an additional $5 per synthetic user if you want to enrich the simulation with your own data via RAG.

UX Pilot is an AI-first user research assistant that sits across the entire UX workflow, from early discovery to validation. It helps teams generate targeted interview and survey questions in seconds, synthesize and cluster qualitative inputs, and translate messy feedback into clear patterns and design opportunities.

UserBit is a research repository and analysis tool to convert hours of raw video and text into a structured knowledge base. It uses AI to generate a transcript that can handle overlapping speakers and background noise, and it will often reconstruct words that are partially cut off.

You can ask AI to "highlight all feature requests" or “find pain points in this project,” and it’ll scan notes, survey responses, and transcripts, create the right tags, and apply them to the exact snippets for you. Plus, UserBit can generate starter persona templates from your project inputs and turn everything in a project into a shareable case-study style report.

Dovetail’s AI automatically classifies qualitative feedback into themes, identifies emerging issues, and groups similar comments, making it ideal for quickly analyzing large volumes of data. Teams can then visualize these themes alongside business metrics, generate insight-driven docs and PRDs, and even chat with their data to move from research findings to product decisions in hours.

Condens AI centralizes notes, transcripts, and clips from interviews or tests in one place, then uses AI to propose tags, group related observations, and generate summaries at the session, theme, and project level. By combining these AI workflows with a research repository, Condens AI lets product and UX teams quickly surface past evidence and patterns, keep their insight library consistent over time, and support product decisions with well-organized qualitative research.

Outset is an AI-moderated research platform built for teams that want qualitative depth at quantitative speed. You define the research guide with questions, probing rules, and skip logic—and Outset’s AI interviewer runs hundreds of sessions in parallel over video, voice, or text, in multiple languages.

Outset does not publicly disclose specific pricing figures on its website. However, according to third-party comparison sites, basic plans potentially start around $200 per month, with Pro plans around $400 per month, and Enterprise plans are typically custom quoted based on scope and usage. These plans are unverified estimates that should be treated as indicative only.

HeyMarvin (Marvin) is a qualitative research repository. It gives you an AI note-taker you can trigger during live sessions to ensure key moments and quotes are captured. Then it runs thematic, sentiment, and trend analysis over your repository to surface patterns. Plus, the ‘Ask AI’ chat lets you query your own research data directly and get answers grounded in your existing calls, notes, and documents.

UXPin Merge AIhelps UX teams instantly turn ideas or prompts into interactive prototypes built from real, coded components that follow an existing design system. Because these prototypes are powered by production-ready React and HTML components, they behave much closer to the final product, which makes usability tests and concept validation sessions more realistic and reliable than static mocks.

UXPin Merge AI is available on the Merge AI plan at $49 per month. Higher-tier plans like Growth ($69 per month) and Enterprise (custom pricing) offer additional capabilities like Storybook integration, Component Manager, and advanced security controls.

Sprig is a product experience research platform with AI built into both setup and analysis. You can run long-form and in-product surveys, collect always-on feedback, and capture replays and heatmaps.

Sprig AI clusters responses, surfaces pain points, and generates summaries. The AI Study Creator also helps non-researchers get started. You describe the product goal, and Sprig suggests study types, questions, and targeting to collect the right data at the right point in your product.

Sprig no longer lists pricing publicly on its website. However, historical data from 2024 indicates the following tiers:

Userlytics is a remote user testing platform with a global panel and a dedicated AI UX Analysis layer for video-based studies. You run moderated or unmoderated tests as usual, and the AI analyzes the session transcripts to summarize key themes and actionable insights.

It’s built to help teams scale the number of qualitative video sessions they can launch and analyze, reduce some of the human bias that creeps into manual note-taking, and sit alongside existing analytics, like ULX Score and sentiment analysis.

AI tools help user research teams move faster, work at larger scale, and reuse what they already know instead of starting from scratch every time.

AI tools act as amplifiers: they can strengthen good research practice or magnify weak foundations. The goal is to use AI to accelerate analysis and scale your reach while keeping humans in charge of judgment and ethics.

Here are some actionable best practices to ensure you’re maximizing the potential of AI tools without compromising on research quality:

So, with all these options, how do you find the right tool for you and your team?

Here are some key considerations to keep in mind when making your decision:

Maze’s AI functionalities ensure that each step in your research process complements your UX/UI design tools, usability testing tools, and product discovery tools. With smart features like bias-free question drafting, theme clustering, and auto-generated summaries, Maze speeds up your research process and helps you make sense of the data.

Plus, you get access to 50+ pre-built research templates and integrations with popular wireframe and design tools like Figma, and AI prototyping tools like Figma Make, Bolt, and Loveable.

Maze helps your team make data-driven decisions confidently.