The new role of the designer in the age of artificial intelligence

For years we have talked about the need for designers to learn to code in order to better understand the digital product. Today, artificial intelligence is changing the rules of the game and, with them, the way we understand the role of the designer should change too. AI is making it far more accessible to develop an application: generating code, creating components, building interfaces, connecting services or catching bugs are tasks that can increasingly be done with ease using these tools. The barrier to entry for building software is dropping considerably, and here an interesting paradox appears: the easier it is to build software, the more important it becomes to know which software is worth building.

Code is becoming a medium

Using AI in development is no longer experimental. According to the 2025 Stack Overflow survey, 84% of the developers surveyed use or plan to use AI tools in their development process. However, 46% say they distrust the accuracy of the results, and 66% point to solutions that are "almost right" as their main frustration. This shows something important: generating code is getting easier all the time, but deciding whether the result is good still takes human judgment.

An AI can build a perfectly functional interface and still make it hard to use, barely accessible, or unable to properly solve the user's problem. An application can be technically well built and still be a bad experience. And that is where the designer takes on a new dimension.

Designing is much more than designing screens

The value of a product designer has never been only knowing how to use Figma. A good designer has to understand the problem, know their users, structure information, design flows, anticipate errors and make an experience understandable, accessible and pleasant. That means mastering disciplines such as information architecture, usability, accessibility, interaction design, visual hierarchy, responsive design and the consistency of design systems.

The W3C itself includes within UX aspects such as user journeys, information architecture, wireframes and prototypes, and treats accessibility as something that should be part of the design process, not just a technical check at the end. That is why, when we can ask an AI to build an application for us, the truly important question should not only be how to build it, but what experience it should offer and what problem it should solve.

The designer as orchestrator

Traditionally, the process of creating a digital product could be summed up as problem, design, development and product. With the new AI tools, the process can evolve into a model in which the designer defines the strategy, designs the solution, sets its rules and uses AI to generate a first implementation that is then tested, evaluated and improved iteratively.

Their value is not necessarily in writing every line of code, but in knowing how to steer the process towards a good solution. This opens a possibility that was much harder a few years ago: a designer with a solid grasp of product can take an idea all the way to a working application without mastering all the languages and frameworks traditionally needed to develop it. AI is, to a certain extent, democratizing the ability to build software and allowing designers to take a much more direct part in bringing their ideas to life.

Development knowledge as a multiplier

This does not mean designers no longer need to learn development. On the contrary, I believe that understanding technology can become an even bigger advantage. A designer who understands HTML, CSS, JavaScript, components, APIs, databases, architecture or the limitations of a technology has an advantage over someone who uses AI as a black box. They don't need to become the best programmer on the team, but they do need to understand the medium they are working in well enough.

That knowledge lets them design technically more viable solutions, spot errors in AI-generated implementations, write more precise instructions, critically evaluate technical decisions, prototype faster and communicate better with developers when the project needs specialists. That is why I don't believe the future is a competition between designers and developers, or that AI will make the latter unnecessary. The real opportunity lies in expanding the capabilities of both profiles and using technology to work better.

When building is cheap, judgment gets expensive

For a long time, one of the great barriers to turning an idea into a digital product was the technical ability needed to build it. Today that barrier is shrinking, and a person with product and design knowledge can have a building capacity that would previously have required a much larger team. However, this also means it will be easier and easier to create mediocre applications.

When anyone can generate an interface, write code and build a prototype, differentiation is no longer only about who can do it, but about who knows what to build and how to build it well. AI can generate code, components and interfaces and even propose solutions, but someone has to decide which one makes sense, understand the user, spot a confusing interaction, question a decision, take accessibility into account and recognize which elements are surplus. That someone can be the designer.

From interface designers to product builders

Perhaps we are entering a stage in which the designer stops being only the person who designs and hands over specifications, and also becomes a builder and orchestrator of digital products. A designer can imagine a solution, design it, use AI to build a first version, test it, spot problems and iterate again. The distance between having an idea and having something working that can be tested is shrinking enormously.

In this context, a designer without deep development knowledge can use AI to build much more than they could before. But a designer who also understands development can better grasp the possibilities, spot the limitations and steer what the AI produces more precisely. Technical knowledge does not disappear: it becomes a multiplier of the designer's capability.

That is why I don't believe artificial intelligence is reducing the value of design, but changing where that value lies. When producing software gets cheaper, judgment becomes more important. And when building an application is within reach of more people, knowing what to build, for whom, why and how to make it really work can become one of the most valuable skills in digital product.

Perhaps the future of design is not only about designing and handing over, but about imagining, defining, building, testing, learning and building again. In that scenario, the designer does not lose relevance: they widen their field of action.