Design systems teams are leveraging AI tools to improve efficiency and accuracy in their workflows. Traditional methods often result in a significant lag, with documentation delays and mismatches between design and code. In contrast, teams using integrated AI can generate components in just two minutes, update documentation automatically, and conduct design audits in five minutes. This swift turnaround is achieved by moving from static prototyping in Figma to using real code in a local environment, enabling rapid iterations and real interactions. Setting up a local sandbox with a Next.js dev server and connected design tokens allows teams to generate working code from Figma designs quickly. The process involves feeding AI tools like Claude or Cursor specific design details, which results in functional components. By using existing design system components, teams ensure consistency and reduce maintenance. Documentation becomes AI-friendly when it’s stored in markdown, allowing AI to reference guidelines without manual input. This streamlines the development process, making it easier for AI to generate components that adhere to established patterns. AI can automate documentation updates based on changes in Figma, allowing real-time access to current information. This eliminates the lag that often hampers design systems, ensuring everyone works from the latest data. Other AI applications include generating UX copy consistent with the team’s voice, creating internal tools like design token generators, and syncing Figma with code. These innovations lead to significant time savings and a reduction in design-code drift, drastically improving the overall workflow for design system teams.