AI-Driven Code Generation: Why Tokenization Is The Backbone Of Figma-to-Code

Here’s the good news: recent advances in AI-powered workflows now make it possible to translate Figma designs into production-ready AEM components. This capability has the potential to transform how teams deliver digital experiences by accelerating timelines, reducing manual effort, and improving consistency.

To fully realize these benefits, there is one essential ingredient: a structured tokenized design system.

A design system is much more than a collection of visual assets. It is a set of principles, patterns, and reusable components that enable teams to create digital products efficiently and consistently. When maintained well, a design system reduces friction, minimizes errors, and creates a reliable foundation for scaling digital experiences across teams and platforms.

This value becomes even more apparent as automation advances. With AI-powered workflows and Figma-to-Code capabilities, the investment in a structured design system truly pays off. Automation can only deliver on its promise when it can rely on clear, consistent, and well-defined foundations.

Automation Needs A Solid Foundation: Why Design Systems Matter

With this kind of AI-driven automation, especially approaches like Figma-to-Code, one crucial truth often gets overlooked: automation is only as powerful as its underlying system. Instead of seeing Figma-to-Code as a magic button, we must see it as an accelerator, one that works best when the underlying design foundations are clearly defined and well maintained. The real foundation is not the tool itself, but the design system that supports it. More specifically, success depends on a design system built with smart, consistent, and scalable tokenization.

AI can only effectively automate what is clearly described. A robust design system provides the clarity needed to generate reliable, maintainable code at scale.

This includes:

• Tokenization: Clear definitions of colors, spacing, and typography as design tokens that can be mapped to code variables.
• Semantic Structure: Consistent naming conventions and hierarchies across components and patterns.
• Variants and States: Documented behaviors, such as hover, focus, disabled, must be clearly assigned so AI-generated components accurately reflect real interactions.

When these elements are in place, AI becomes a powerful enabler of speed and consistency. Furthermore, if they are not yet fully established, it presents a valuable opportunity to create the foundations that will support automation long term.

Why Tokenization Is The Backbone

Tokens are the smallest and most fundamental pieces of your design language, forming the DNA of your visual identity. A token can represent a color, a spacing value, a font size, or a state such as “hover” or “disabled.” A future-proof design system only earns this title once every relevant style or interaction is mapped to a clear and semantic value.

This matters because tokens form the bridge between design and development, as well as between today’s technology and the platforms of tomorrow. When you want to change a brand color, you no longer need to search through dozens or hundreds of hex codes and manual overrides. Changing the token once means the update appears everywhere it is referenced: across web, app, intranet, and even future products.

The connection to automation becomes especially important here. When your design system is fully tokenized, tools like Figma-to-Code can translate design decisions directly into code, without ambiguity or manual guesswork. Successful token system architecture is not just a set of values but provides system-independent building blocks. This makes it possible to scale your brand consistently across different technologies, including web, mobile, AEM, and native apps. Designers and developers can always speak the same visual language, which results in less duplication, fewer errors, and a design system that works for everyone.

What can go wrong with poor tokenization?

Designers:

• Different designers may interpret components in their own way, creating subtle variations that look similar but are not truly consistent.
• Updates often reach only new screens, so legacy products and designs remain outdated.

Developers:

• Developers end up implementing these unique designs as hardcoded, one-off solutions, which makes the codebase brittle and difficult to maintain.
• They spend unnecessary time searching for overrides and adjusting code for each new variation.
• Every new platform or channel demands another round of manual adaptation, slowing down releases.

QA:

• QA teams invest more time matching implemented screens to the latest mockups instead of focusing on the overall user experience.
• Inconsistencies are often discovered late, leading to costly fixes or issues that turn up in production.

Why A Well-Tokenized System Makes Figma-to-Code Actually Work

A solid token foundation enables Figma-to-Code automation to reach its full potential. The systematic work that designers do in Figma, using tokens for spacing, color, typography, and states, does not need to be re-implemented by developers. The structure is already in place, making automation truly effective.

To illustrate the difference, consider this scenario. Previously, designers created beautiful mockups, each one reflecting their individual vision of spacing, colors, and typography. When it came to implementation, developers had to inspect every pixel, reverse-engineer hex codes and spacing values, and reconstruct the font sizes. What should have been a simple build became a scavenger hunt through layers and annotations. Later changes, like updating a color, turned into major manual efforts because every occurrence had to be tracked down and replaced.

With a well-tokenized system, design individuality does not result in chaos during implementation. Unique spacings, one-off colors, and custom font choices become a thing of the past. Everything is clearly defined, and designers assemble creative solutions from well-designed elements, similar to working with Lego bricks that fit together seamlessly in many ways. Developers can immediately see which tokens were used and implement them directly. When changes are needed, a single token is updated, and the change flows automatically throughout the entire system. This approach saves time, reduces errors, and improves quality for everyone involved.

As a result, handoffs are smoother, implementation is faster, and teams can focus on innovation rather than troubleshooting. On the other hand, without tokens or with poorly managed ones, AI automation simply reproduces inconsistencies and manual errors at scale. Rather than accelerating quality, it multiplies technical debt.

How To Build A Token Architecture That Lasts

• Start by choosing semantic names, for example, “color-background-primary” instead of “blue-400”, so the token makes sense even when the underlying value changes.
• Build tokens modularly for different categories such as spacing, typography, color, interaction states, etc.
• Keep documentation clear, since tokens are only as effective as their documentation. Always make usage, scope, and relationships transparent.
• Plan for the future by ensuring tokens can support theming, new brands, channels, and accessibility standards.

A strong token architecture is not just a developer’s dream, but a real investment in your brand’s flexibility and quality.

Real-World Example: Evolving A Platform, Step By Step

At Cognizant Netcentric, we have guided teams through the journey of tokenizing entire platforms. Instead of rebuilding everything at once, we begin by introducing design tokens for core elements such as colors, spacing, and typography. These tokens are referenced directly in both design files like Figma and in code, replacing legacy values step-by-step.

One of the most satisfying moments is seeing a single change to a token ripple through not only design and code, but also the authoring environment for editors and content creators. This speeds up rebranding and accessibility improvements, and empowers product owners, designers, and developers to communicate and work together more efficiently.

What started with careful mapping and planning has become almost effortless. Today, updating a color across an entire platform is a minimal task. Changing a token takes only a few clicks, and the update appears instantly everywhere it is needed. By rolling out tokenization gradually, teams experience real progress and see immediate impact, even before a full redesign is complete.

The Moment To Invest Is Now

To truly benefit from Figma-to-Code and AI-driven automation, now is the time to upgrade, rethink, and future-proof your design system.

Well-structured tokens offer far more than efficiency for designers and developers. They allow automation tools to translate design intent directly into high-quality code. When your system is built on clear and semantic tokens, AI can connect the dots between design and implementation. This eliminates repetitive tasks and accelerates delivery in ways that manual workflows simply cannot match. AI-powered code generation is still evolving, but investing in a sophisticated token architecture today ensures your design system is ready for what’s next.
A strong design system is no longer a luxury; it is the engine of your brand’s agility and quality. The opportunity is not just to automate current processes, but to unlock greater speed and consistency. This shift allows teams to focus on creativity, strategy, and user experience. Automation is not about reducing headcount, but about increasing impact across your organization.

A Real Partnership Pays Off

At Cognizant Netcentric, we believe the best results come when designers and developers collaborate closely from the beginning. We have seen first-hand how a well-tokenized design system not only speeds up delivery but also creates empowered project teams and better outcomes for clients.

If you are ready to take your design system to the next level, let’s talk about how you can unlock the full potential of Figma-to-Code and prepare your design system for the future.