If an AI can produce a screen or an entire layout in a matter of seconds, what is actually left for a web designer, a UX designer, or a UI designer to do?
It is a legitimate question, yet it rests on a premise worth challenging, namely that the value of design coincides mainly with the production of visual output.
In our day-to-day experience, what is really changing is not the usefulness of digital design, but the point at which it generates value for a project and for the people who will use it. Artificial intelligence is shifting the center of gravity of the work: less time spent producing artifacts, more time devoted to understanding context, interpreting people's behavior, and making decisions that no algorithm can take on in our place.
What artificial intelligence can already do in design today?
Generative AI tools applied to web design, UX design, and UI design are already highly capable in a number of well-defined activities: they quickly generate wireframes and interface variants starting from a text prompt, automate the creation of design systems consistent with a brand's guidelines, transcribe and summarize user interviews by identifying recurring themes in a fraction of the time this used to take, and support UX writing by generating microcopy aligned with a company's tone of voice.
This represents a genuine productivity leap, one that drastically shortens the distance between an idea and a first testable design proposal. But shortening this time does not make it any easier to understand the context in which that solution will actually have to work, and this is precisely where the work that, at Moku, we continue to consider indispensable comes into play.
The designer's value shifts from production to interpretation
An artificial intelligence can generate a visually flawless checkout screen in a matter of seconds. It is far more complex to understand why people abandon their cart at that very checkout, which details generate uncertainty, and which levers truly influence a purchasing decision. This is why, well before designing an interface, a good designer still has to ask who they are designing for, what difficulties that person encounters along the way, and how these needs coexist with the company's business objectives: questions that call for direct observation and empathy, not a prompt.
Even in UX research, artificial intelligence significantly speeds up the collection and synthesis of information, but it does not automatically generate knowledge. Value often emerges from what falls outside expected patterns, such as a contradiction between what people say and what they actually do: attributing meaning to these signals remains work that requires experience and critical judgment
Designing for people who now also converse with artificial intelligence
There is a second level of change that concerns the way people use digital products: more and more often they converse with conversational systems to receive advice and make decisions, and this changes the expectations they bring to an interface. How is trust built in a system that can get things wrong? How is the level of certainty of an automatically generated answer communicated clearly? How is control over decisions kept in people's hands, preventing automation from replacing their critical thinking?
These are questions that concern the experience well before the technology, and this is why the role of the UX and UI designer is broadening: it no longer concerns only the design of interfaces, but increasingly the design of the relationships between people, automated systems, and decisions.
From producing solutions to orchestrating hybrid systems
We can read this evolution as a shift from producer of artifacts to orchestrator of a broader system, in which human capabilities and AI tools collaborate to build better experiences. It is no longer just a matter of designing a solution, but of asking the right questions, making sense of what emerges from research, and consciously deciding when to rely on AI and when the critical judgment of a person is needed. The most sought-after skills today, whether for those working as web designers or those working in UX or UI, therefore remain the ability to research and listen to people, systemic thinking applied to the entire product ecosystem, practical knowledge of generative AI tools used as targeted accelerators, and ethical sensitivity in designing systems that involve artificial intelligence.
At Moku we approach this change not as a threat to be contained, but as an opportunity to return to the essence of our craft: understanding people, interpreting their behavior, and guiding product decisions with responsibility. We continue to integrate the artificial intelligence tools that make us faster and more efficient, but we remain convinced that the human contribution, made of listening and experience, is what truly makes the difference between a well-made interface and an experience in which people recognize themselves.
