For the last decade we have leaned on responsive design and design systems to scale digital interfaces. Content lives in a CMS. Components and tokens live in a design system. Rules define how everything adapts across devices.
The system works, but it is manual. Designers and developers still have to define outputs for mobile, desktop, or voice.
Now imagine if the content was the source of truth, and an AI layer decided how to present it depending on the context.
Think about a sales report. On desktop it could show as a full interactive chart with filters. On mobile it might reduce to a highlight summary with expandable detail. On voice it could be delivered as spoken insights. On a TV dashboard it might render as a bold infographic with minimal text.
The AI is not reading a design system website to make that choice. It is using the actual building blocks from the system. Tokens, components, accessibility rules, interaction patterns. The documentation site is helpful for people, but the AI needs machine readable assets it can apply in real time.
That raises a key question. Who sets the style, and who applies it.
The brand expression layer still belongs to designers and engineers. Designers define the look and feel of the brand, capture it in tokens, and document the rules. Engineers code those tokens and components so they can be reused across products. This is the palette. These are the raw ingredients.
The AI sits on the assembly and adaptation layer. It does not invent brand styles from scratch. It applies the tokens and rules already defined. Its job is to select the right layout or component for the context. On mobile it might choose a compact card. On desktop it might expand to a grid. On voice it might simplify labels. On dashboards it might select a chart type that meets accessibility rules.
In practice this could look simple. A headless content source provides structured data, text, and media. A design system in code provides components like cards, charts, and media players, along with tokens for spacing, colour, and type. An AI layout engine, trained on patterns, selects which components to use and how to arrange them. A renderer maps that schema to the components and displays it in the right form for each device.
The page shell does not change. What changes is how the content and the controls are expressed.
We are not fully there yet. Most AI tools generate static layouts rather than adaptive experiences. Performance and consistency remain challenges. Accessibility and governance also need strong guardrails.
Still, the building blocks exist. Headless CMS. Design systems in code. Schema driven rendering. AI models that can output structured layouts.
If this becomes real it changes the role of designers and developers. Instead of hand crafting every variant, the work becomes defining the rules, tokens, and constraints. The AI assembles the experience. The result could be adaptive, future proof interfaces that scale across devices and new mediums we have not even imagined yet.
This is still theory. What is missing is a working prototype to prove the idea. I want to explore how we might build a version of this together, using headless content, a small set of coded components, and an AI layout engine that adapts to context.
If you are experimenting in this space, whether you are an engineer, designer, or researcher, I would like to connect. Maybe we can turn this idea into something real.