Design Systems in the Age of AI: Five Working Hypotheses — UX Design Research

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Design Systems in the Age of AI: Five Working Hypotheses

When I started designing a new comprehensive design system, I expected the main challenge to be designing components, defining rules, and writing documentation. It turned out, however, that the real challenges lay elsewhere. In particular, once AI becomes a significant consumer of such a design system, some of the fundamental assumptions on which today's design systems are built begin to lose their validity. At the same time, entirely new blind spots emerge—areas for which no underlying assumptions have ever been defined.

This article presents five working hypotheses that emerged during the design of a new generation of design system. It does not attempt to propose a finished theory or a new standard. Its primary goal is to open a discussion about whether today's design systems are designed for a world in which humans are no longer their only users—and whether the time has come for a fundamental shift in some of the paradigms we have taken for granted.

Design Systems

Design systems have become a standard part of digital product development over the past few years. Although they differ in scope and quality, most of them are built on a similar assumption: their primary users are people. Designers, developers, testers, and product managers. Today, that assumption is no longer self-evident.

AI is gradually becoming an active participant in product design, implementation, and governance. It is increasingly used to design interfaces, write code, create components, check consistency, and explain the rules of a design system. This leads us to ask a simple question:

Are today's design systems designed for a world in which humans are no longer their only users?

Artificial Intelligence in Design

We often hear the same observation repeated: AI is changing this or that, AI has taken jobs away from one profession or another, AI has destroyed one industry after another. I do not believe that artificial intelligence is destroying anything. It is certainly changing things—but not necessarily in a destructive way.

AI is not a monster. It is simply a new tool. One that can be remarkably useful when we know how to work with it, use it for the tasks it does well, and provide it with data it can understand. In more exact disciplines, such as engineering or software development, this has become fairly obvious, and effective methods for integrating AI into existing workflows have evolved very quickly.

Things become more complicated in less formal and more creative disciplines. AI is already capable of generating large amounts of content, including user interface designs, but much of it is still based on relatively routine and repetitive recombinations of familiar patterns. An experienced eye can often tell that a piece of text, an image, or a UI was generated by AI. The reason, however, is not that AI agents are inherently incapable. Rather, it is that we have not yet learned how to teach them more of the creative process or provide them with better knowledge structures for producing richer and more innovative designs.

AI Reveals Previously Invisible Weaknesses

Working with AI exposes the limitations of the current UX design model. The hesitation and repetitive behaviour we often observe when AI designs user interfaces reveal that design systems have been built on assumptions that are no longer universally valid. They were created primarily for people—as a way for designers to communicate knowledge and outcomes to developers, users, managers, and other stakeholders. Both their content and their form reflect that purpose.

Neither the form nor the content, however, is optimal for AI. And if AI is to become another—perhaps even the primary—consumer of design systems, then not only their form and content may need to change, but possibly the very concept of what a design system is.

Hypothesis 1

A Design System Is No Longer a Component Library. It Becomes a Knowledge Model of the Product

Today, a design system is often equated with a component library accompanied by documentation. Components, however, are only one implementation of a much broader and more complex model.

At first glance, it may seem that the primary value of a design system lies in its precise description of how a button or a dialog should look and behave, and how developers are expected to implement it. But that is only the outer layer. What really matters lies beneath it: knowledge . The knowledge of why a component exists in the first place, when it should be used, which problems it solves, and how it relates to the rest of the product.

If this perspective proves to be correct, we will need to stop thinking of a design system as a catalogue of UI elements and begin to understand it as a formalized model of a product's user interface.

Hypothesis 2

The Real Value of a Design System Lies in Rules,...