Google introduces Generative UI: What is it and why it matters

Google Generative UI

Google has launched generative UI, a new capability that allows its AI models to generate interactive interfaces based on any user prompt. Unlike static responses that present text or predefined layouts, generative UI produces dynamic environments that adapt to the intent of the request. The company is introducing this system through experiments in the Gemini app and through AI Mode in Google Search.

How generative UI works

Generative UI functions by creating a full user experience on the fly. When a user submits a prompt, the AI model builds a tailored interface that can include tools, simulations or structured layouts designed for exploration, learning or task completion. Google’s implementation relies on three components: access to tools such as image generation and web search, detailed system instructions that guide layout and coding, and post-processing steps that refine the output before delivery.

Evaluations conducted by Google show that, when ignoring generation speed, users prefer generative UI outputs over standard text or markdown responses. The system interprets intent and constructs interfaces suited to different use cases, ranging from educational content to planning workflows.

Availability across Google products

The Gemini app now supports generative UI through dynamic view and visual layout. Dynamic view uses the model’s coding abilities to build a unique interface for each prompt. This allows the system to adjust the experience depending on context, such as explaining scientific topics to different age groups or generating content layouts for business use.

Google Search is also integrating generative UI through AI Mode. Users can request interactive explanations or visual breakdowns, and the system generates tools or simulations built specifically for that query. This capability is rolling out initially for Google AI Pro and Ultra subscribers in the United States.

Why generative UI matters

Generative UI introduces a shift in how users interact with AI. Instead of receiving information in fixed formats, users get environments that support deeper comprehension and more effective task execution. Google views this as an early stage of development, noting that improvements are still needed in generation time and accuracy. The company expects future versions to expand to more scenarios, incorporate additional context and feedback, and support a wider range of tasks.