OpenAI

ChatGPT reached 100 million monthly active users within it's first two months of launch. As it grew into one of the most widely adopted consumer applications in history, OpenAI faced a design challenge that went far beyond visual polish. The product needed to feel clear, responsive, and trustworthy to an enormous and diverse audience, many of whom were interacting with AI for the first time.

To meet this challenge, OpenAI turned to motion. By using Lottielab, the OpenAI team were able to create micro-animations that made complex system behavior feel understandable and human. These small moments of motion became a core part of how ChatGPT communicates with its users at scale.

The challenge

ChatGPT’s interface is intentionally simple, but the system behind it is anything but. Every interaction involves processing, waiting, responding, and transitioning between states that are largely invisible to the user. Without clear feedback, these moments can feel uncertain or confusing.

OpenAI needed a way to communicate what the system was doing without adding more text, more instructions, or more cognitive load. At the same time, the product was evolving rapidly. Design and engineering teams were shipping improvements continuously, which made traditional motion design workflows difficult to sustain. Heavy tools, slow iteration cycles, and complex handoffs did not match the pace of the product.

Why animation?

In ChatGPT, micro-animations serve a functional purpose. They confirm that an action has been received, indicate that the system is working, and help users understand transitions between different states of the conversation. These subtle cues reduce uncertainty, make wait times feel shorter, and build trust through consistency.

Because ChatGPT is used millions of times every day, even the smallest improvements to clarity and feedback have an outsized impact. Motion became a way to quietly support users without demanding their attention.

Why Lottielab?

OpenAI adopted Lottielab as part of its product design workflow, treating motion not as a finishing touch but as a core system. Lottielab made it possible for teams to design and iterate on micro-animations quickly, with less friction between design and implementation.

Instead of relying on slow legacy software like After Effects, OpenAI could get started straight away. This quick turn around time meant they could quickly get their animations into production and refine motion directly for real product contexts. Animations were lightweight, production-ready, and easy to adjust as the interface evolved. This allowed motion design to keep pace with rapid product development rather than becoming a bottleneck.

Lottielab's quick learning curve, ease of use, and realtime collaboration features made it a natural fit for OpenAI's team. Designers could experiment with motion ideas quickly, share them with others for feedback, and then iterate based on real user interactions.

OpenAI's strategy was to focus on high-impact moments in the ChatGPT interface. These were places where users naturally pause, wait, or look for reassurance. Thoughtful micro-animations helped guide attention, signal progress, and confirm outcomes without distracting from the core conversation.

Over time, these animations became part of a shared motion language. Patterns could be reused and refined, creating consistency across the product while still allowing flexibility as new features were introduced. Lottielab’s workflow made it easy for teams to collaborate and improve these interactions continuously.

The impact

The result was not a louder or more animated interface, but a calmer and more legible one. With Lottielab, OpenAI was able to ship micro-animations faster, collaborate more effectively across teams, and maintain consistency even as ChatGPT scaled rapidly.

For users, this meant an experience that felt more responsive and reassuring. For the product team, it meant motion design that could grow with the product rather than slow it down.

AI products introduce new behaviors and expectations. Users are constantly forming mental models about what the system understands and how it responds. Micro-animations help shape those models by providing immediate, intuitive feedback.

By using Lottielab, OpenAI showed how small, well-considered moments of motion can make advanced technology feel approachable and human. At massive scale, these details matter. They help turn powerful AI into a product that feels accessible to everyone.