AI and Design: A Revolution Challenging Certainties

A Disruption in the Design World

Eight months ago, questions began to emerge in meetings where a head of design was not supposed to be paying attention. Questions like “Can’t we just ask Figma AI to do it?” or “If AI can generate screens, why are we still hiring?” started to circulate. As head of design for a global technology platform dedicated to restaurants, and having built design teams at Walmart and Capital One, this executive has spent years advocating for the importance of design. Yet these questions, though painful, are not entirely unfounded.

For the past eight months, this design leader has faced versions of the same question. It hurts. But here is what no one wants to say out loud: they are not entirely wrong to ask. Not because design doesn’t matter. But because, for most of the last decade, a significant share of what design teams were actually producing (what designers were hired, evaluated and promoted for) was exactly the kind of work that AI can now do faster, cheaper, and without a Slack message.

The conditions for this were created. No one had simply thought that it was building a trap.

The Responsibility of Designers in This Transition

Design created the conditions for its own displacement starting in the 2010s, when design thinking enjoyed a major boom. By the time this leader joined his first corporate job, he was inheriting the wreckage of that boom: corporate hallways that saw design thinking as a workshop rather than as a way to shape the industry.

Design grew. Teams of ten became teams of hundreds. Salaries doubled. Org charts brought design closer to senior management, and it seemed, from the outside, that design had finally found its place. Designers had seats at tables from which they had been excluded for years.

But what was actually happening was narrower than that. Design was growing to support agile delivery. Every product team needed a designer. Every designer had to keep engineers unblocked. The greatest professional sin was being the bottleneck: the person who slowed down the sprint, the one whose work wasn’t ready, the designer who wanted to do more research before the product launched.

So designers became fast. Really fast. They learned to produce screens quickly, consistently and in volume. They built design systems so that no one had to make decisions twice. They shipped. They hit their speed targets. They were promoted for it.

And while all this was happening, something else was quietly leaving the building. Not design. Design was everywhere. It is the part of design that cannot be standardized: the judgment that examines a brief before a line of code is written and says this is going to fail, and here is how. The instinct that holds an entire system in your head while everyone else is looking at the feature in front of them. The willingness to say the uncomfortable thing in the room where the decision is actually made.

These capabilities did not disappear because organizations stopped valuing them. They atrophied because designers stopped practicing them. They were too busy shipping to develop the skills that would have made shipping meaningful.

Peter Merholtz recently wrote what many in design leadership think but dare not say out loud: design did not lose its strategic place because organizations took it away. Design traded it, gradually, for salary scales, delivery speed and the comfortable feeling of being needed, until that was no longer the case. He is right. This executive has been a design executive for more than a decade at Walmart, Capital One, and now Byte by Yum!, and has seen design leaders, himself included, make this trade without fully examining what they were giving up.

The Impact of AI on Design

AI automates what has the least value first. For design, that was the user interface (UI). Not because UI is easy. It is not. But because it is repeatable. Learnable. Describable enough to train a model. The things that made a designer valuable within an agile team (the ability to produce good enough material quickly, consistently, without slowing down the sprint) are exactly the things that translate easily into a prompt.

The problem is that a significant number of designers built their entire professional identity around this speed. Not because they were lazy. But because they were rewarded for it. Speed was the metric. Shipped screens were the proof of value. The designer who could produce ten high-fidelity mockups by Thursday was the one who got promoted, who got the raise, who was held up as the example. A profession was built that selected for output and was then surprised when output was automated.

This was observed from the inside. In performance reviews, the conversation was entirely about delivery. How many products did the team touch? How quickly did designs move to handoff? Was the design system used consistently enough to speed up the next sprint? Rarely did anyone ask: did we design the right thing? Did we anticipate what was going to happen before it shipped? Did we prevent anything?

There was no language for prevention. There was a language for production.

So when AI arrived and production became cheap, many designers did the only thing they knew how to do: they got faster. They learned the new tools. They optimized their prompts. They competed on the dimension that was being commoditized.

That is the wrong bet.

AI did not expose a weakness in design. It exposed a lie that designers told themselves to survive.

For thirty years, the field has said the same thing in every executive briefing, every conference keynote, every recruiting conversation where it tried to justify the budget: design is not how something looks. It is how something works.

They meant it. And they couldn’t fully prove it either, because the interface was always in their way.

The screen was the only thing that made the invisible visible. It was impossible to show a CEO how a system worked without first showing them what it looked like. It was impossible to align engineers on a concept without mocking it up. It was impossible to make stakeholders feel the experience without rendering it. So they rendered it. Constantly. The majority of professional hours went into producing the visual proof of a thought that lived somewhere deeper, because without the visual, no one could see the thought.

AI has simply made that part cheap.

And what becomes clear, now that the scaffolding is gone, is that for many people who called themselves designers, the scaffolding was the only skill the job ever asked them to develop.

Reevaluating the Value of Design

It is important to be precise here, because this is not an argument that UI is easy or that the people who do it well are somehow inferior. UI is hard. Doing it well requires a depth of skill that takes years to build: visual hierarchy, interaction logic, accessibility, the thousand little decisions that make something easy to use. That work matters. It has always mattered. But UI is the translation layer, not the thing itself.

What the last decade did, in its race for speed, was to quietly stop rewarding everything else. The job became: be fast at the main thing. Ship. Repeat. The T-shape that design education advocated flattened into a single vertical line.

But if someone spent the last decade learning to show the work without learning to do the work (if the mockup was the thought and not the artifact of the thought), then what AI took from that person was not a tool.

It was the thing they were hiding behind.

This is not said to be cruel. It is said because talented, hardworking designers are genuinely terrified right now, and the fear is specific. It is not that the tools are changing. It is that they do not know who they are without the tools.

That is the question the field must answer.

A New Era for Design

The market is reevaluating the value of design.

This is not a story about AI eliminating design. It is a story about companies being forced to change what they optimize for, and design has to change with that. Right now, in most organizations, optimization revolves around speed, risk reduction, margin and adaptability. The ability to move quickly without breaking things that cost a fortune to fix later.

In this environment, some work gets automated first. Not because it is unimportant, but because it is describable. Repeatable. Trainable. Production work. Visual execution. Variations at scale. Application of templates. The things designers used to spend 40 to 50% of their time on.

That work is now cheap. Which means competing on it makes you cheap.

When anyone can generate twenty concepts in ten minutes, concept generation is no longer premium. When any product manager can mock up a flow before the meeting, fidelity is no longer proof of expertise. When the tool does the production, the person using the tool is a cost.

What becomes scarce (and scarcity is where the leverage lies) is judgment.

What to pursue. What to kill. What not to build at all. When to move quickly and when going fast is the costliest decision in the room. How to approach a brief that says “use AI to improve trust” when no one in the room can define trust, and still move the work forward.

That kind of judgment cannot be asked for. It cannot be standardized. It does not get cheaper as models improve.

And it lies in four specific skills that design has always claimed to value, and has largely left underdeveloped.

• Tolerance for Ambiguity. The brief is incomplete. Stakeholders disagree. The problem is not yet defined well enough to be solved. You have to move forward anyway, not recklessly but deliberately. You have to define the thing that no one else wanted to define.