A user experience (UX) designer creates thoughtful, effective, human-centered, and accessible digital experiences for web or mobile platforms. They collaborate with product managers and engineers to advocate for users and deliver design assets that engineers can build upon. How will AI tools change the nature of their jobs?
First, it’s important to understand UX design on a tactical level. The role involves understanding user needs, creating wireframes and prototypes, conducting user testing, and iterating on designs based on feedback.
A designer may even work with UX researchers at the start of a project to identify behavioral insights needed to create design concepts. From there, those designs and concepts evolve into digital prototypes and other assets that developers use to code the final solution.
The chief goal of a UX designer is to create intuitive and enjoyable experiences that meet both user and business needs. At every stage of their workflow, there’s the potential for AI to fundamentally change the process.
How AI Can Help
According to Lisa Jackson, vice president of UX and design at CNH, there are different stages throughout the design process in which AI is extremely useful: “UX designers face a significant hurdle when synthesizing mountains of data—from user interviews and surveys to competitive benchmarks—into clear, actionable insights.”
In theory, AI makes that process much easier, as it can surface useful insights for the designer. And when it comes to producing design work, AI tools (such as Figma, one of the most popular tools for UX designers) can convert work into AI-powered prototypes.
“These tools help to eliminate the busywork that designers traditionally had to do so they can now focus on creative content and more mentally demanding aspects of the job,” Jackson said.
Greg Fuller, vice president of Codecademy Enterprise, noted AI can assist UX designers in various tasks, such as generating first drafts of client interview questions, creating authentic placeholder text, and summarizing findings from design tests.
“AI tools can also analyze user behavior data to identify patterns and insights, automate repetitive tasks, and provide design suggestions based on best practices,” he said. “This allows designers to focus more on creative and strategic aspects of their work.”
The hyper-personalization of design is also made easier with AI. Color schemes, layouts, and brand elements can be automatically adjusted through these tools to perfectly fit the specific context or user. “This allows for a highly personalized experience where digital designs change dynamically to cater to different customers and brand,” Jackson said.
Essential Understanding
Fuller said UX designers need to understand that AI is not a replacement for their expertise and requires human oversight: “While AI can offer significant benefits, it can also produce errors or poor design decisions if not properly supervised.”
He recommended designers verify AI outputs with their research, knowledge, and experience. Additionally, they must practice safe data-handling, especially when dealing with sensitive user information.
UX designers should start by identifying specific areas in their workflow where AI can add value, using their organization’s rules and guidelines as a starting point. “If those guidelines aren’t put in place yet, practice responsible usage, document the processes, and work with technology, innovation, and transformation leaders to find what works best for your organization,” he said.
Starting small (such as integrating AI tools into a single project) and gradually expanding your use as you become more comfortable is a practical approach. It’s also important to regularly review and refine your approach based on feedback, with an eye toward a successful balance of AI skills within your overall workflow.
Jackson suggested that AI tools are changing rapidly. To keep up, designers must constantly experiment with different tools to understand how to create value. “To harness the full potential of AI in UX, designers must actively experiment with new tools and engage in open dialogue with their peers, fostering a community of shared learning and rapid iteration,” she said.
AI Training: Where to Go
Digital learning courses, especially those providing multi-modal, blended formats that accommodate individual learning preferences, are ideal for AI training.
LinkedIn Learning and others have courses for UX designers on using AI tools. While relevant and interesting courses are readily available for those who need them, hands-on AI experience will continue to be the best way for UX designers to become comfortable using this emerging technology.
“The number one objective for UX designers should be to build something themselves using AI tools,” Jackson said. “If you’re looking for a job in UX design, you need to be able to show that you have first-hand experience using AI tools.”
Interaction Design Foundation: AI for Designers
The certified course equips participants with the skills to integrate AI into the design process, from research and prototyping to ethical application and portfolio building. The course covers key AI concepts, tools for workflow enhancement, and strategies for creating innovative, AI-driven design solutions.
Uxcel: AI in UX/UI Design
This course focuses on the use of AI for creative innovation, efficient content creation, and data-driven design decisions, covering AI tools for enhancing creativity, streamlining user research, and analyzing data to optimize user experiences.
Udemy: AI in UX Design
The course explores AI’s role in ideation, UX writing, and user research, teaching participants to integrate AI into the design process and leverage free tools for usability testing and focuses on the limitations of the technology.
Designlab: AI for Visual Design
The four-week-long, $799 course includes instruction on how to use AI tools including Midjourney, ChatGPT, and DALL-E, with weekly video lectures led by GenAI expert Sachin Kamath, along with hands-on project work and peer group sessions and mentor feedback.
Fuller suggested UX designers pursue training that covers the basics of AI, including ethics, prompt engineering, and current capabilities. It’s critical
Jackson suggested connecting with researchers and developers within your company—natural partners who are also interested in using AI. “This technology's value extends far beyond individual designers,” she explained.
Fostering collaboration across all departments involved in product development will translate into better use of AI, as well as consistent processes and training on an organizational level.
Securing Executive Buy-In for Upskilling
Jackson recommends UX designers proactively seek budget for pilot projects, incorporate AI skill development into performance goals, and explicitly communicate a commitment to mastering these tools to higher-ups: “It will be crucial for any UX designer to have this training and knowledge, so there is no reason not to hold yourself accountable for it.”
Fuller noted AI tools can significantly increase efficiency by automating repetitive tasks, allowing designers to focus on high-level design challenges. Demonstrating these benefits and discussing potential drawbacks honestly can help secure executive buy-in.
“When approaching higher-ups, focus on concrete examples of how AI skills will benefit the company, such as reducing time spent on user research or improving the quality of user insights,” he said.
Be specific about what support is needed, whether it’s time for training, funding for courses, or access to AI tools. Documenting and sharing the positive impact of AI integration can help build a strong case for continued investment in upskilling.”
It’s important to demonstrate the value of AI to your organization by developing a project brief that highlights its potential to solve business challenges and drive growth. This clear outline of benefits will be key to securing management investment.”
For example, AI implementation might mean you can develop products faster or help ensure greater market share due to better customer experience. “Use the business value and ROI calculations to show why AI is important and then talk about how your company is leveraging AI to drive business value,” Jackson said. “AI for the sake of AI is not a strategy.”
