Research Analytics Summit 2024
Archived
This content is available here strictly for research, reference, and/or recordkeeping and as such it may not be fully accessible. If you work or study at University of Kentucky and would like to request an accessible version, please use the SensusAccess Document Converter.
Document Type
Presentation
Abstract
Explore the transformative potential of generative AI in university-research administration. As universities strive to enhance research capabilities and support a culture of innovation, the need for efficient and effective management of sponsored programs has become paramount. This presentation will share lessons from deploying a sponsored programs’ Large Language Model Chatbot and how it optimizes research administration operations and unlocks opportunities. By harnessing the power of GenAI, a university office of sponsored programs chatbot can develop training materials, policies and SOPs. It can offer immediate support and guidance by analyzing queries and providing real-time responses, empowering staff members to overcome challenges and reducing time on tasks. It can enhance productivity and job satisfaction. An OSP Chat will allow research administrators to focus on higher-value activities, such as strategic planning, relationship building and facilitating research collaboration resulting in improved operational effectiveness and increased capacity to support research excellence. This improves the quality of research administration services. This presentation will highlight the collaboration of AI experts, research administrators and stakeholders to tailor LLM to the research administration's needs, maximizing staff benefits and optimizing research support.
DOI
https://doi.org/10.13023/8BCB-Y784
Publication Date
2024
Recommended Citation
Wilson, Lisa A.; Yisrael, Tubal; and Wagner, Alex, "Unlocking Opportunities: Leveraging Generative AI in University-Sponsored Programs Operations" (2024). Research Analytics Summit 2024. 36.
https://uknowledge.uky.edu/research_events2/36
