AI and Design: Embrace Change, But Don’t Forget What Matters

AI and Design: Embrace Change, But Don’t Forget What Matters

AI is changing the product design landscape at a breakneck pace. It's important that we embrace these new tools, but don't sacrifice the quality of design for speed.


Will Sansbury
Will Sansbury
AI and Design: Embrace Change, But...

Most designers know the famous Double Diamond framework from the British Design Council. First, explore the problem. Then define it. Then explore solutions. Then refine. It’s not always linear, but the principle holds: you need time to explore before you commit.

This work by the Design Council is licensed under a CC BY 4.0 license.

In the early days of digital product design, we honored that. We sketched with Sharpies. We ran design charettes to generate ideas. We moved fast, threw things away, and stayed loose. Then came Photoshop, Fireworks, Sketch, and Figma. These tools gave us polish—but also made it easier to converge too soon. Once something looked “real,” it became harder to change. Stakeholders got attached. Designers got fixated. Exploration slowed. Premature convergence set in.

Participants at a Design Studio Workshop I taught in Atlanta in 2014 review the first round of divergent ideation.
Participants at a Design Studio Workshop I taught in Atlanta in 2014 review the first round of divergent ideation.

Now, we’re entering a new era—one where AI tools don’t just generate mockups, but actual front-end code. You type a prompt, and out comes a working UI. Not a sketch. Not a wireframe. Code. This is a leap in capability—and in risk. When a design is already functioning in code, it doesn’t just look finished—it is finished, at least to many stakeholders. And that makes it harder to step back, rethink, and explore alternatives.

This is how the creative process gets short-circuited. Teams skip the first diamond entirely—jumping to solutions without understanding the problem. They build interfaces that are functional but misaligned. Products become polished but shallow, fast but fragile. Design becomes reactive instead of reflective.

The damage isn’t always immediate. But over time, it compounds. You ship faster, but learn less. You optimize for delivery, not discovery. You stop asking “what if?” and start asking “how fast?” Eventually, you lose the space where real innovation happens.

AI tools aren’t the enemy. They’ll make great designers even better—especially those who can resist the gravitational pull of polish and code. But for teams without that discipline, or for stakeholders who equate working code with final product, these tools could quietly erode the very process that makes design valuable.

Without divergence, we don’t explore possibilities. We don’t test assumptions, challenge defaults, or uncover better paths. We don’t design with empathy—we just rush to solutions. And when that happens, we are shortchanging more than the process; we are shortchanging the people we’re designing for.

Design’s power has always been its focus on outcomes. If we reduce the value of design to visible output, we give away its superpower.

Speed at the cost of value is no bargain.

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