Overview
The Nio user experience needed a design system reset as its new AI automation feature was being integrated.Because I signed on under a Non-Disclosure Agreement, I cannot discuss the details of said new feature, but its capabilities drastically changed the flow of the product.
Said changes needed to be accommodated with new design for the most seamless and scalable user experience.
Problems
The pre-existing design system came with its own set of issues autonomous of the new feature. Additionally, designing for the new feature came with its own challenges.
High number of feature capabilities, high cognitive load
The product vision included both traditional tasks of an EMR with our session recording feature and AI automation feature worked in.
Poor scalability across interfaces
The product had several features that needed to be designed for both desktop and monitors, but also mobile for when professionals are on the fly. Most specifically, the Record feature.
Designing for clinicians and healthcare professionals
Many healthcare professionals are extremely busy and are already burdened with cumbersome software.
Putting new software into a design that feels familiar
The experience needed to introduce new capabilities without abandoning familiar interaction patterns that healthcare professionals already rely on.
Revamping the preexisting design system in a modern way that improved user experience, while still feeling familiar and similar to software that has defined the workflow of the healthcare industry.
Additionally, designing for and integrating a new AI feature that could potentially complicate and undermine the product if not done correctly.
Design principles
Encourage transparency, not mystery
AI-generated information should never feel mysterious or cause suspicion, especially within an industry where it's vital to be able to trust the tools we use. I designed the experience so users could easily understand where an insight came from.
Build trust through evidence
Rather than asking users to simply accept an AI-generated conclusion, the interface keeps supporting evidence close at hand. Clear relationships between insights and sources help users validate information themselves.
Reduce complexity without removing depth
The feature needed to surface large amounts of information without overwhelming the user. I used progressive disclosure, information hierarchy, and contextual interactions to keep the experience focused.
Make tools that use AI collaborative with the user
The goal was not to make AI a source of authority, but to make it a tool for exploration. The experience helps users identify patterns, surface relevant information, and investigate connections while leaving interpretation and decision-making with the professionals.
Outcome
The final design transformed a clunky and overcrowded design system into a sleek and intuitive experience automating cumbersome tasks for healthcare professionals.
The feature redesign established a transparent relationship between AI output, supporting evidence, user interpretation, and patient background.
Effectively transforming insights from isolated outputs into an evidence-backed system trusted by several healthcare professionals and clinics in Canada and the United States.