Pioneering AI-Powered Research Operations
Overview
Role: UX Researcher & AI Implementation Lead
Company: UnitedHealth Group
Team Size: 4 Researchers
Timeline: Q2 2025
Impact: 40% efficiency gain in research synthesis
The Challenge
As a UX Researcher at UnitedHealth Group, I identified a critical opportunity to enhance our research team's efficiency and output quality. Our team of 4 researchers was handling an increasing volume of user interviews, data synthesis, and stakeholder reporting – often spending 60% of our time on manual documentation and synthesis tasks rather than strategic research activities.
Context:
Key Pain Points
Time-intensive synthesis: Researchers spent 15-20 hours weekly on interview transcription and initial analysis
Inconsistent documentation: Varying approaches to research documentation across team members
Delayed insights delivery: Average 5-7 days from data collection to actionable insights
Scalability challenges: Growing research demands without proportional team expansion
Opportunity
Microsoft Copilot's integration across our enterprise Microsoft 365 suite presented an untapped opportunity to revolutionize our research operations through AI-powered assistance.
My Approach
-
Stakeholder Alignment
Presented business case to leadership demonstrating potential ROI
Secured buy-in from IT security for Copilot usage with research data
Established success metrics aligned with department OKRs
Tool Evaluation
Conducted comprehensive audit of Copilot capabilities across Word, Excel, PowerPoint, and Teams
Mapped Copilot features to specific research workflow pain points
Developed use case matrix for different research methodologies
-
The Perfect Prompt Formula
I created a structured framework for consistent, high-quality AI outputs:
G.O.A.L Framework:
Goal: Define the specific research objective
Output: Specify desired format and structure
Audience: Identify stakeholder needs and context
Length: Set appropriate scope parameters
Research-Specific Prompt Library
Developed 25+ tested prompts covering:
User interview analysis
Persona development
Data synthesis reports
Stakeholder presentations
Survey analysis
-
Curriculum Development
Created comprehensive training materials including:
Interactive workshop presentations
Hands-on exercise workbooks
Quick reference guides
Video tutorials for asynchronous learning
Workshop Facilitation
Led three 90-minute training sessions:
Session 1: Copilot fundamentals and prompt engineering
Session 2: Research-specific applications and best practices
Session 3: Advanced techniques and workflow integration
Ongoing Support Structure
Established weekly "Copilot Office Hours" for troubleshooting
Created Slack channel for prompt sharing and peer learning
Developed a feedback loop for continuous improvement
The Solution
Phase 1:
Foundation (Week 1-2)
Set up Copilot access and permissions for the research team
Conducted baseline efficiency assessment
Introduced basic prompt engineering concepts
Phase 2:
Integration (Week 3-4)
Integrated Copilot into existing research workflows
Customized prompts for team-specific needs
Established quality assurance protocols
Phase 3:
Optimization (Week 5-6)
Refined prompt library based on team feedback
Automated recurring research tasks
Scaled successful practices across broader UX team
Key Innovations
Research Synthesis Accelerator
Developed a standardized Copilot workflow that reduced interview analysis time from 45 to 15 minutes per session:
Input: Raw interview transcripts
Process: Custom Copilot prompts for thematic analysis
Output: Structured insights with quotes and frequency counts
Dynamic Persona Generator
Created prompt templates that transform research data into rich, actionable personas in under 30 minutes:
Demographics and psychographics
Jobs-to-be-done framework integration
Pain points with severity rankings
Opportunity mapping
Stakeholder Report Automation
Built a Copilot-powered reporting system that generates executive summaries from research findings:
Key insights extraction
Data visualization recommendations
Actionable next steps
Impact prioritization matrix
Results & Impact
-
Quantitative Metrics
Efficiency Gains
40% reduction in research documentation time
60% faster insight delivery (from 5-7 days to 2-3 days)
3x increase in research output volume
25 hours/week saved across the team (6+ hours per researcher)
-
Qualitative Outcomes
Team Empowerment
Researchers shifted focus from documentation to strategic analysis
Increased confidence in handling larger research projects
Enhanced collaboration through standardized processes
-
Success Stories
Case Example: Navigation Study
Before Copilot: 2 weeks from interviews to final report
With Copilot: 4 days end-to-end, with richer insights
Business Impact: Enabled faster iteration on critical UX improvements
"Camilla's leadership in bringing Copilot to our research practice has been transformative. We're delivering insights faster while actually improving quality – something I didn't think was possible."
~ Stephanie, Senior UX Designer
Conclusion:
This initiative demonstrates my ability to identify strategic opportunities, lead technological transformation, and deliver measurable business value through innovation. By successfully implementing Copilot across our UX research practice, I not only improved team efficiency by 40% but also positioned our department as pioneers in AI-powered research operations.
The framework and training program I developed have become organizational assets, scalable beyond our immediate team and adaptable to evolving AI capabilities. This project showcases my unique blend of research expertise, technical acumen, and leadership skills – positioning me as an ideal candidate for roles requiring innovation, strategic thinking, and the ability to drive meaningful change.
View Presentation Materials
Download Original Training Presentation
Access Prompt Library
Watch Training Videos

