AI in UX design: What designers need to know now

As a UX designer tasked with creating a user-centric product and experiences, your job is never truly finished. Notes from stakeholder meetings, aligning UX strategies with product decisions, building prototypes, and validating designs are all part of your day-to-day.

While there’s nothing better than seeing your designs come to life and solve user problems, with that comes countless hours of painstaking research, repetitive tasks, and complex workflows.

So, how can AI tools for UX design help lighten this load?

From streamlining processes to speeding up the creation of prototypes and user personas, AI can make the UX design process altogether more efficient, convenient, and economical.

Here’s how.

No, it won’t.

AI makes the jobs of UX researchers and UX designers easier, but it doesn't handle the process from start to finish. It doesn’t (currently) recruit research participants or communicate key insights with specific teams, and it can’t action the uncovered insights to turn them into informed product development.

UX design is and will always be a deeply human experience that requires human designers. AI can take the data and analyze trends, but it's ultimately up to the product developers, researchers, and designers to piece the puzzle together with human needs and empathy at heart.

AI is impacting UX design by reducing repetitive work and expanding what UX teams can create. It’s shifting where UX designers spend their energy—from execution to strategy:

Plus, AI presents great opportunities for the future of UX design, too. For example, it’s already become proficient in removing and adding content through Photoshop’s ‘generative fill’ feature. In the future, we’re‌ looking at AI-powered tools that could provide advanced image manipulation and data-based recommendations to fine-tune design and UX choices instantly.

AI’s most immediate impact for teams is in UX research and prototyping, where speed to insight can make or break design decisions.

Our 2025 Future of User Research Report shows adoption is rising fast: 58% of product professionals now use AI in their research, up 32% from 2024, with many applying it to:

Here’s what it looks like in practice:

Maze AI integrates these advantages directly into the UX research workflow. With automated themes, AI-powered interview moderation and analysis, and bias detection in survey questions, it helps UX teams move faster from data collection to decisions—while keeping judgment and empathy in human hands.

From faster workflows to more inclusive design, AI brings clear advantages. At the same time, it introduces challenges around trust, accuracy, and the evolving role of designers. Understanding both sides helps teams adopt AI responsibly.

So, how does AI actually fit into your design workflow? Here are seven ways to make it work for you.

Now, let’s cover some of the distinct applications of AI in UX design.

One area AI can be beneficial is creating user personas. User personas help you ensure you’re making decisions with customers in mind—but creating them can be a tricky task.

AI can help create user personas using your prompts by looking at existing information relating to products and their users. You can then use these AI-built personas as a foundation for creating personas that are specific to your product and audience.

Interviews and usability tests are essential, but planning, running, and analyzing them takes time. AI tools like ChatGPT, Claude AI, and Google Bard can generate tailored questions and tasks from your prompts, giving you a quick starting point that you can refine for your study. This alone cuts down prep work and helps teams move faster.

Maze adds AI into the process itself. Maze’s AI moderator runs adaptive interviews across 20+ languages, asking context-aware follow-ups and producing transcripts, summaries, and highlights automatically. For survey and task design, Maze’s Perfect Question and Dynamic Follow-Up features identify and rephrase questions with biases, illegibility, and grammar issues, offering polished alternatives to gather better user insights.

Many designers and product managers are faced with brainstorming innovative approaches toward solving points of friction. Coming up with actionable solutions takes some originality—AI can help you get those creative juices flowing.

Much like they can help when it comes to writing interview questions and tasks, language AI models can generate potential ideas from your specific prompts and follow-up questions. While you may not be able to copy and paste these ideas off the bat, they can spark discussion, inspiration, and new ideas for the early stages of the UX design process.

With the right customer insights, product teams can create products that precisely meet users' needs in less time, without costly mistakes and reworks. But getting those insights can often involve spending hours sifting through user data—be it from UX surveys, interviews, customer success conversations, and more.

AI can quickly analyze large amounts of data to extract key themes, concepts, sentiments, and more. For example, Maze AI for Interview Studies analyzes large amounts of qualitative interview data, extracting useful feedback like sentiment analysis, critical takeaways, and summarizing whole interviews.

We've already discussed how AI won't replace UX design, and the same goes for UX writing—but it can nonetheless give it a significant boost. AI platforms like Jasper and other language-based models can create UX copy for you to build on.

A professional UX writer will be needed to make edits, but UX writing generated by AI still offers a general direction or can help break that writer’s block, making it easier to conceptualize the finished product.

Time constraints are a major challenge for UX designers, and automating repetitive tasks and processes helps speed things up. It could be as simple as using the native AI features within your project management software to automate the mundane, like populating databases or triggering workflows.

Let’s say you want to email all stakeholders once your UX report is in. You can easily set up an AI automation that triggers a notification when reports are uploaded, meaning you don’t need to manually notify the team with updates.

Accessibility is central to good UX, and AI offers practical tools to help. For example, voice-activated AI assistants help make sure your product is accessible to users with limited mobility and visual impairments. Similarly, AI-powered automated captioning and transcription ensure all of your content is accessible for users who are hard of hearing. It can even help when it comes to translating content for various audiences and languages.

Other examples include generating image descriptions, image enhancements, and color correction for color blindness. There are many ways to use AI to build more accessible experiences, and it’s one of the most compelling use cases on any list.

Excited? Already started planning how you can incorporate AI into your workflows? Good—this section’s for you.

The right AI tools can help you build better product experiences, but choosing the perfect virtual companion can be daunting. Here are the best AI tools to aid your UX design journey.

Alongside its existing user research methods, like concept validation, usability testing, content testing, and feedback collection, Maze provides UX designers with a suite of AI solutions. Maze AI is built directly into the Maze platform and focuses on automating repetitive research tasks, improving the research process, and turning raw feedback into shareable insights.

Some of these AI-powered solutions and features include:

Engaging copy and content are a big part of many UX designs. It helps users interact with the product correctly while reflecting your brand's values through voice and tone. Jasper is an AI writing assistant that helps UX teams generate both short and long-form content from simple prompts. The platform offers multiple templates and a Brand Voice feature, which scans existing assets to keep copy consistent with your tone and style. Jasper also supports image generation, useful for assets like ads or thumbnails.

Japer’s AI capabilities include:

Khroma is an AI-powered color palette generator built for designers and creatives. It learns your personal preferences through a quick training process, selecting around 50 favorite colors, and then generates unlimited palettes that align with your style. The tool runs in-browser, applies palettes to different contexts like typography or gradients, and even gives accessibility ratings to ensure color choices meet WCAG standards.

Khroma’s AI capabilities include:

We couldn’t talk about UX design without mentioning Figma. One of the most popular UI/UX tools out there, the design program has over four million users worldwide and is a staple in every UX designer's toolbox.

Figma has a wide variety of AI plug-ins to help facilitate the UX design process, such as:

As AI becomes a standard part of design and research, UX roles will evolve. Routine tasks are increasingly automated, which means the value of UX professionals will come from skills that AI can’t replicate: judgment, strategy, empathy, and ethics.

Here are a few quick tips to future-proof your career in UX:

UX careers are shifting toward high-value work that blends technical fluency with the human skills AI can’t replace.

AI has undoubtedly been changing the way designers and product teams approach UX design. But even as AI-driven tools simplify workflows, UX and UI design remain centered on people: empathy, inclusivity, and real-world usability are what make products succeed.

Maze brings these capabilities together—all in one platform. From Feedback Surveys and User Interviews to Prototype Testing, Live Website Testing, Card Sorting, and more, Maze empowers teams big and small to run decision-driving research initiatives. And with Maze AI, your team can benefit from the many applications of AI within UX—whether that’s when crafting your research questions or when analyzing your findings.

Whether you’re testing functionality, optimizing user flows, or refining copy, Maze makes it easy to embed research into every stage of your design workflow.