UX Perspectives: Junior UX staff and AI-enhanced workflows

AI can now speed up research, collate data, spot patterns, mock up draft prototypes and plot out journey maps. Those are many of the tasks junior UX designers have traditionally completed.

We asked UX professionals: if AI does the work juniors used to do to develop on the job, how do you help them learn and where do they add value?

Viktoriia Androshchuk RGD, Product Designer at Vailent

AI shifts the junior designer's focus from “pixel pushing” to "critical curation". Since AI can generate 10 wireframes in seconds, the junior's main job is no longer to draw them, but to evaluate which one actually solves the user's problem. We must train juniors to be editors and strategists, not just executors. If they blindly accept AI outputs, we get fast but generic, unusable products.

To put them to good use, we need to change how we mentor. Instead of spending weeks teaching them basic UI patterns, we can let AI handle the initial drafts and focus our coaching on systems thinking and user empathy. My goal is to teach them to ask better questions, spot where AI lacks real-world context and validate AI's assumptions against actual user research. They need to learn that AI is a powerful starting point, but human judgement is still the final filter for a great product experience.

Olatunde Ayilara RGD, Founder at WhoCleanedIt

I teach them to see AI as a partner and not to delegate every activity to it. AI is most useful for research, such as gathering information and understanding trends. When it comes to actual decision-making, you have to find the solution yourself. If you hit a creative block, it's okay to use AI, but it's also easy to spot something that's human-made versus AI-made. You also want to take full credit for your deliverables. It's so easy to spot a UI created with the help of AI.

Samiksha Makhijani RGD, Lead Product Designer at Zero Hash

The lines between UX research, content, design systems, visual design and product design are blurring really fast. For junior designers that means becoming more of a generalist while still building a few skills they're really strong at. You could be a well-rounded product designer, for example, but have a great eye for visual design. 

AI is also making the traditional design process faster and much less rigid. Junior designers should embrace that shift. Try new tools, read case studies, see how other designers are using AI and keep a running list of use cases where it can actually save you time or help you do better work.

It's not about knowing every AI tool. It's about understanding where AI can make you more effective, while continuing to build the judgement and craft that make you a strong designer.

Daniela Manov RGD, Product Designer at Microsoft

AI changes what junior UX work looks like, shifting the emphasis from producing the work to judging it, but juniors still need to learn the craft by doing it. Research synthesis, pattern-finding, journey maps and early prototypes are exactly the work that trains the eye, the mind and the taste. It's like learning to write essays: AI can write one in seconds, but you can only judge whether it's any good if you've learned what a good essay is and how one is built. A junior who has synthesized research “by hand” will notice what an AI summary flattened, invented or missed. One who hasn't may pass on a confident but wrong insight without knowing it.

That doesn't mean keeping AI away from juniors, but being deliberate about which repetitions matter. Transcribing interviews or reformatting a deck builds little, and I'd happily hand those to AI. The work that builds judgement is synthesizing what people said, framing the problem and deciding what to prototype and why. Those are the reps I'd protect.

Where juniors add the most value now is as the people who validate and challenge what AI produces (a first line of defence) and in the work AI can't do. In practice, I'd have them do a first pass themselves, then use AI to extend it, challenge it or compare against it. Critiquing AI output becomes part of their training: what did it get wrong, what did it make up, what doesn't fit our users?

I'd also put them in front of real people early, sitting in on interviews, watching usability tests and presenting findings—it's where empathy and intuition are built. And I'd pair them with a senior who reviews their thinking, not just their deliverables.

Aaron Neilson-Belman RGD, Manager, UX & Brand Strategy at Brafton Inc.

While AI is arguably one of the most disruptive shifts we've seen in digital tech, I don't think it fundamentally changes how we mentor junior UX professionals. Working in digital media has always required us to adapt, continuously learn and figure out how to best leverage emerging tech.

AI is increasingly taking on repetitive, production-oriented tasks traditionally assigned to juniors, freeing them to apply their education, creativity and critical thinking to more meaningful challenges earlier in their careers. This shifts our role as mentors to helping juniors develop foundational skills through critical evaluation, hands-on problem-solving and understanding the reasoning behind their work. That means holding juniors accountable for their work, encouraging them to challenge assumptions, explain their decisions and understand why a solution works, not just how to produce one.

Juniors also bring fresh perspectives and familiarity with emerging tools, creating opportunities for reciprocal learning. Ultimately, our role is to build on their strengths, encourage experimentation and help them become thoughtful, capable practitioners.

Sean Archie Urriza RGD, Senior Production Designer at DIRTT

I think about this a lot, because yes, the tasks AI is best at are the ones juniors used to learn on. You don't build instincts by reading a tidy summary of an interview you weren't in. So I'd keep juniors in the room with users: moderating, taking their own notes, sitting through the awkward pauses where people finally say the useful thing.

Let AI clean up transcripts and take a first pass at clustering, but the junior has to defend those themes against the raw quotes and tell me which ones the model got wrong. Seniors and mentors matter more than ever here, because they're the ones reminding a junior that yes, you can prompt your way to almost anything, and it still has to be backed by user research. The user stays at the centre of it, and that part gets learned from a person, not a tool.