Carbon for AI

Source: IBM Carbon Design System (page last updated) · 2026-08-12

AI introduces a range of new responsibilities when designing experiences across our software, particularly regarding trust and transparency. Carbon for AI is the framework for identifying AI-generated content and delivering explainability in our products.

Transparency of AI presence is key to user trust. Having a consistent identity helps build awareness and anticipation of AI presence across our experiences.

This integration requires you to minimize distractions and show explanations only when needed or requested by the user.

Carbon for AI styling builds on the core Carbon library principles, using light as a metaphor to “illuminate” AI-generated content. This makes AI-generated or AI-recommended content distinctive and stands out for users. For IBMers only: To learn more about the Carbon for AI styling, see Design for AI: Style elements.

Carbon for AI uses light-inspired effects like brightness, glow, and gradients to emphasize AI instances across the experience.

Carbon for AI is designed to coexist alongside the Carbon themes but has its own unique visual characteristics that distinguishes it as AI while following the IBM Design Language DNA and principles.

Explainability is a set of processes and methods that make AI decisions more comprehensible to humans. For IBMers only: To learn more about explainability, see Design for AI: Explainability.

The AI label is the primary indicator to communicate that AI is present, and it’s how users can access explainability content.

The AI label is a component used as an indicator of AI instances in the UI. It is intended for any scenario where AI is generating content to reinforce AI transparency, accountability, and explainability at any interface level. It enables more effective recognition and recall of AI instances in a way that is identifiable across any IBM product.

The AI label is also the trigger for the explainability popover which serves as the first layer of explainability. It provides a consistent, up-front way to access explainability with the option to dig into more details if needed.

AI chat is a conversational framework between a user and an AI that can aid in creating tasks, finding insights, tracking documents, and more. For IBMers only: To learn more about chat, see Design for AI: Chat pattern.

The AI label is the primary indicator to communicate that AI is present. To ensure that the AI label remains accessible across light and dark themes, use the provided component.