Intelligent Design For
Artificial Intelligence

Recently, Microsoft developed a powerful set of enterprise-grade tools that clients could use to build conversational AI experiences into their own products and services. To drive successful adoption and market growth of this product line among technology innovators, the experience of using the toolset itself needed to be just as smooth, smart, and self-explanatory as those it was designed to create.

Lacking the in-house expertise and operational bandwidth to tackle this challenge on their own, the product team at Microsoft turned to Filter for help.

Filter collaborated with the client to assess their needs, then designed a process and built a veteran UX team to achieve their vision.

That process began with Filter UX researchers planning and conducting focus group studies, capturing usability data, analyzing industry trends, and carrying out a heuristic evaluation of products to provide expert review feedback to our UX and visual designers. They in turn leveraged these findings to formulate an AI platform redesign, building mood boards, wireframes, storyboards, design briefs, pattern studies, visual language guidelines, motion studies, and other deliverables to help develop and evolve user experience designs.

They also reworked the content strategy and messaging, and honed the iconography and typography styles to bring more consistency and intelligence to the visual library, setting a clearer style guide template for future expandability. Throughout the process, Filter’s program manager for the team worked in parallel with the Microsoft lead in overseeing the details and schedule of the deliverables, providing performance reporting and issue management, and ensuring overall program success.

Filter’s UX work was integrated into the client’s AI product line and launched as part of Microsoft’s product version release/upgrade program. The more clear, consistent, and efficient user experience we developed helped to accelerate platform adoption and lowered user abandonment rates.

The smooth success of this program ultimately led to three additional projects across the Microsoft AI platform to adopt the same process framework that our team designed for this program.