Google and OpenAI Unveil Competing Visions for Dynamic AI-Generated UIs

Google has announced Project A2UI, an initiative focused on dynamically AI-generated user interfaces, aiming to enhance interactions with AI agents for tasks like reservations. The core problem A2UI addresses is the inefficiency of back-and-forth chatbot conversations when completing structured tasks. Google’s proposed solution involves third-party services (e.g., restaurant reservation systems) sending JSON data that describes UI components (such as text fields, date/time inputs, or buttons) rather than full HTML. The AI host application (like Google’s Gemini) then translates this JSON into its native UI components, leveraging its own component catalog. This approach ensures brand consistency with the AI agent’s interface, eliminates security risks associated with rendering untrusted third-party HTML, and maintains compatibility with the external service’s data requirements. The goal is to create purpose-built UI snippets that integrate fluidly into AI applications.

This development comes as OpenAI has already ventured into a similar space with its Apps SDK, released in October. The Apps SDK is designed to help third-party services build HTML widgets and JavaScript components that can be rendered within ChatGPT. Unlike A2UI’s JSON-based, host-rendered UI, OpenAI’s solution renders service-defined HTML in a sandboxed iframe, allowing the third-party service to control the styling. The underlying MCP (Model-Controller-Provider) standard is also evolving to support a more generalized approach for exposing these HTML widgets to various AI agents. Both Google and OpenAI share the broader ambition of transforming their AI platforms into a new kind of ‘app store,’ where users can accomplish diverse tasks without leaving the chatbot environment. However, the adoption landscape for service providers remains uncertain; while services like reservation platforms may benefit from increased reach, others that directly charge users (e.g., creative tools) might face challenges related to feature limitations, loss of direct customer engagement, and commission structures, mirroring dynamics observed in mobile app ecosystems.