AI Use Case: Accelerating Qualitative Analysis and Persona Development with Copilot

In my industry role, I often face the familiar challenge of producing high‑quality user‑experience artifacts under tight timelines and with limited access to participants. During a recent project, I was tasked with creating a set of user personas after the primary research phase had already concluded. Because the participants had limited availability, I was unable to conduct the follow‑up interviews typically needed to develop research‑grounded personas. However, our organization’s Microsoft Copilot license provided access to internal documents, Teams messages, Teams meeting notes, and email exchanges related to the project—sources that collectively held a great deal of tacit knowledge about the users.

To begin, I outlined the characteristics, needs, and pain points I already knew for each of the six personas. I uploaded the persona template slide I planned to use and prompted Copilot with the scenario: I explained the project context, the type of personas I needed to create, and the specific individual each persona was loosely based on. I then asked Copilot to generate additional needs and pain points by drawing on any relevant internal files, documents, or communications it had access to. This step allowed me to validate my existing qualitative insights and surface patterns I might have overlooked.

Copilot produced draft persona content that aligned closely with my prior knowledge while also suggesting new considerations grounded in the internal communication data. I reviewed each output carefully, making adjustments to ensure accuracy, tone, and alignment with the project’s goals. Within a short timeframe, I was able to produce six well‑rounded, proto‑personas that reflected both my qualitative analysis and the broader organizational knowledge captured in our internal systems.

This workflow did not replace qualitative research, but it significantly accelerated the synthesis process and helped validate my findings. Copilot functioned as an analytical partner—one that could rapidly scan distributed organizational knowledge and surface insights that supported the creation of more robust personas under real‑world constraints.