Winners of the College of Pharmacy 2026 Staff AI Challenge
Earlier this year, the College of Pharmacy launched the Staff AI Challenge to identify practical ways artificial intelligence could improve efficiency, reduce administrative burden and enhance how work is done at the College of Pharmacy. Staff members were invited to submit implementation-ready ideas with the potential to make a meaningful impact. Ultimately, several proposals were recognized.
The Staff AI Challenge winners are:
Top Awards
Ren Leaflight, Senior Business Intel Analyst
Ren’s "Budget Variance & Reconciliation with Copilot" proposal would use existing Microsoft AI tools to automate and streamline routine financial review processes across the College of Pharmacy. By identifying exceptions, generating variance explanations, drafting communications and supporting account reconciliations, the solution would reduce administrative workload, improve consistency and free staff to focus on strategic analysis and decision-making.
Kristian Easter, Administrative Assistant
Kristian proposed creating a secure "AI Operations Assistant" using an approved platform such as Microsoft 365 Copilot or ChatGPT Enterprise/Education. The assistant would serve as a centralized hub for institutional knowledge, approved documentation and AI-powered workflows, providing staff with a single, searchable resource. By delivering trusted information, automating routine tasks and guiding users through university systems and processes, it would improve efficiency, reduce duplication of effort and promote more consistent operations across the college.
Lauren Granchie, Research Associate
Lauren proposed using Google Gemini and Google Apps Script to send quarterly updates in an effort to keep research lab websites up to date by listing out the latest publications that are missing from the website, compiling data from the most recent publications to better fit the current focus of lab research, and listing recent news articles published online that highlight lab and lab member accomplishments.
Shen Wang, Postdoctoral Researcher
Shen proposed "Auto-Research," a researcher-directed AI platform designed to support long-term scientific discovery. The platform organizes knowledge into a dynamic graph of interconnected research questions, with supporting publications and findings linked to each node. Four specialized AI agents continuously collaborate to generate questions, break down complex problems, search and review literature, extract evidence, and compile answers. The system generates new research questions as knowledge gaps are identified, enabling the graph to expand over time. Researchers can query the accumulated knowledge using natural language and receive evidence-based, cited responses while maintaining control over research direction, priorities and interpretation.
Honorable Mentions
Mary Higginbotham, Resource Planning Specialist
Mary proposed an "On-Demand AI Upskilling and Knowledge-Sharing Framework" that empowers College of Pharmacy staff to become active learners and problem solvers. Using university-approved tools such as Copilot and Gemini as real-time tutors and troubleshooting partners, staff build skills and solve challenges while remaining fully engaged in the work. The framework emphasizes keeping humans in the loop while fostering continuous learning, effective execution and long-term capability development.
Tanya Bomsta, Curriculum Project Manager
Tanya proposed encouraging faculty and staff to create custom Generative Pre-trained Transformers (GPTs), such as Gemini Gems or Microsoft Copilot Agents, to support recurring work tasks. These specialized AI assistants can be configured with specific instructions, examples, rubrics and workflows, enabling users to complete tasks consistently without having to recreate prompts for each new conversation. Agents can be used individually or shared across teams to improve efficiency, streamline workflows and promote best practices.
Each of these staff members will receive a cash award and will be invited to share their ideas at future faculty meetings, staff meetings and/or town halls.