Ambient AI

Defining the logic for proactive software that senses user intent. As the designer for the Contextual Layer, I developed a framework that translates system signals into human needs, moving enterprise tools from reactive menus toward anticipatory partners that protect user flow.

Team

IBM Research / Advanced UX

Timeline

8 weeks

Role

Interaction Designer

Background
Background

Overview

I was responsible for the Contextual Layer of an internal Ambient Intelligence framework. My work explored how software can move from being a reactive tool to a proactive partner. Using watsonx.data as a strategic sandbox, I mapped technical system signals like task complexity and cognitive load to specific system responses. By standardizing these signal-to-action rules, I established a foundational North Star for how multiple product teams can build consistent, trust-based AI experiences that adapt to the user’s environment.


The full framework and implementation details are under NDA, but I'm happy to walk through my process and thinking in conversation.

Overview

I was responsible for the Contextual Layer of an internal Ambient Intelligence framework. My work explored how software can move from being a reactive tool to a proactive partner. Using watsonx.data as a strategic sandbox, I mapped technical system signals like task complexity and cognitive load to specific system responses. By standardizing these signal-to-action rules, I established a foundational North Star for how multiple product teams can build consistent, trust-based AI experiences that adapt to the user’s environment.


The full framework and implementation details are under NDA, but I'm happy to walk through my process and thinking in conversation.

Other Cases

Other Cases