AI for Analytics – Chatting with Institutional Data

University research offices are under constant pressure to deliver fast, accurate insights—whether answering ad hoc questions about proposals, awards, and expenditures or producing topic based rollups and trend analyses for institutional leadership. Many of these requests still require hours of manual effort across multiple systems, limiting scalability and consistency.

In this session, we will demonstrate how AI driven approaches can transform access to institutional data through natural language interaction. We will explore how a robust, well structured research data environment enables conversational analytics. Attendees will see how users can “chat” with a live research data warehouse—asking plain English questions about proposals, awards, and expenditures—and receive immediate, trustworthy results. The system translates natural language into SQL, runs queries against live data, and returns results that can be explored, refined through follow up questions, or exported for further analysis.