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5th AI Symposium Sessions

Education Fifth AI Symposium 5th AI Symposium Sessions

Event Schedule

Time & Location Session Title & Presenter(s) Track & Session Description Learning Objectives Prerequisites
9:00-10:15 AM
Trianon Ballroom, 3rd Floor		 Keynote - Beyond the Algorithm: Leading the Human Future of AI in Research Administration - Presented by: AUBRIA, Jahidul Arafat & Bhuvaneshwari Bodakuntla, Auburn University Artificial intelligence is rapidly reshaping the research enterprise, but its greatest impact will not come from technology alone. It will come from the professionals who understand how to apply it responsibly.  In this historic keynote, delivered by AUBRIA, Auburn University's student built AI keynote speaker system, attendees will explore how the conversation around AI has evolved from curiosity to practical implementation and institutional leadership. Through the lens of research administration, the keynote examines where AI can meaningfully reduce administrative burden, where human judgment remains indispensable, and how research administrators are uniquely positioned to guide responsible AI adoption.  Rather than focusing on AI as a replacement for expertise, this session highlights AI as a strategic partner that enables research administrators to spend more time advising researchers, strengthening compliance, improving institutional processes, and advancing the research mission. Participants will leave with a renewed appreciation for the profession's leadership role in shaping trustworthy, ethical, and human-centered AI practices across the research enterprise. In this session, participants will:
Describe how artificial intelligence is transforming the practice of research administration and identify opportunities where AI can enhance efficiency while preserving human expertise. Recognize the critical role of research administrators in establishing responsible AI governance through sound judgment, oversight, privacy protection, and institutional stewardship. Evaluate how AI can support strategic leadership by enabling research administrators to focus on advising, collaboration, innovation, and mission-driven decision-making rather than routine administrative tasks.		  
10:30-11:45 AM
Rendezvous, 3rd Floor		 Operationalizing Responsible AI: Governance, Risk, and Compliance in Research Administration - Presented by: Kathleen Halley-Octa, Attain Partners & Gayle Sherwood, California State University-Monterey Bay Track: AI Governance and Responsible Adoption
As artificial intelligence becomes increasingly embedded in research administration, institutions face growing pressure to ensure its use aligns with regulatory requirements, ethical standards, and institutional risk tolerance. The challenge is no longer simply adopting AI tools but operationalizing responsible AI in environments shaped by federal funding rules, data governance constraints, and evolving compliance expectations. This session provides a practical framework for designing and implementing AI governance in research administration. Attendees will explore how to identify and mitigate risks related to data privacy, security, bias, auditability, and appropriate use, while enabling innovation and operational efficiency. We’ll examine how to align AI use with existing compliance structures, including research security, human subjects protections, financial oversight, and proposal development practices. Grounded in real-world scenarios, the session will also address how to establish policies, review processes, and monitoring mechanisms that scale with institutional adoption. Participants will leave with actionable approaches to embedding responsible AI practices into their organizations without slowing progress or overburdening teams.		 In this session, participants will:
1. Establish a Governance Framework for Responsible AI - Design governance structures that define roles, responsibilities, and decision rights for AI use in research administration, aligned with institutional policies and regulatory expectations.
2. Identify and Mitigate AI-Related Risks Across the Research Lifecycle - Assess key risk domains—including data privacy, security, bias, compliance, authorship, and auditability—and apply practical strategies to mitigate them across activities such as proposal development and human subjects research.
3. Integrate AI Oversight into Proposal Development, and Compliance Processes - Align AI governance with established institutional frameworks (e.g., IRB review, proposal development, research compliance, IT security, and data governance) to enable scalable oversight, appropriate disclosure, and sustainable adoption.		 Basic
10:30-11:45 AM
Petit Trianon, 3rd Floor		 From Manual to Magical: Using Copilot to Build a CPOS Tracker-to-XML Generator for SciENcv - Presented by: Rochelle Hubbart, University of Colorado Anschutz Medical Campus & Holly Heilman, University of Colorado Anschutz Track: AI in the Research Administration
Preparing Current and Pending Other Support (CPOS) documents for SciENcv can be a time-consuming and error-prone process—particularly when data is entered manually. This session demonstrates how Microsoft 365 Copilot can be leveraged as a tool development partner.  Attendees will be guided through the creation of an Excel-based CPOS tracking template that transforms structured data into XML and integrates with a Power Automate workflow to generate SciENcv-compatible XML files ready for upload. The session will cover AI ethics, effective prompt strategies for working with Copilot, key design considerations for structuring CPOS data, and practical approaches for connecting Excel outputs to automated workflows.		 In this session, participants will:
1. Identify key ethical considerations when incorporating AI tools into research administration processes, such as Other Support reporting.
2. Explain prompt engineering techniques to guide Copilot in generating formulas, logic, automation components, and conditional formatting.
3. Learn how to design a structured Excel-based CPOS tracking template that supports conversion into XML format for SciENcv.
4. Explain how Excel outputs can be integrated with Power Automate to generate SciENcv-compatible XML files.		 Advanced: Familiarity with Current & Pending (Other) Support document
10:30-11:45 AM
Trianon Ballroom, 3rd Floor		 Beyond the Prompt: AI + Automation for Research Administration - Presented by: Nathan Wiggins, Southern Utah University Track: AI Tools, Demonstrations, and Case Studies
Artificial intelligence is rapidly transforming research administration, but its greatest value comes when AI is combined with automation to streamline repetitive, high-volume workflows. This interactive session introduces practical strategies for integrating AI into everyday research development and administrative processes using Microsoft Power Automate and SharePoint. Participants will learn how to identify automation opportunities, design simple workflows without programming experience, and maintain appropriate human oversight for research operations. Attendees will leave with practical ideas they can implement immediately to reduce manual effort, improve consistency, and create more time for the strategic work that requires human expertise. 		In this session, participants will:
1. Differentiate between artificial intelligence and automation and understand how they complement one another.
2. Identify opportunities to integrate AI and automation into research administration workflows.
3. Explore practical AI and automation tools that support research development and administrative processes.
4. Design a simple automated workflow that addresses a common research administration task. 		Basic
12:45-1:15 PM
Trianon Ballroom, 3rd Floor		 Huron - Transforming Award Management with AI: Huron AI Awards + Solutions - Presented by: Chris Steele & Sonia Singh Sponsored Demos
See a demo of Huron's AI award accelerator tool, which interprets documents, extracts key system information based on tailored prompts, and outputs this information in a format that streamlines manual workflows. This ensures that every necessary detail is captured, validated, consistent, and ready for use in award setup or other steps throughout the pre-award and post-award lifecycle.		 In this demo, participants will:
Explore the role of AI in supporting key pre/post award processes, data cleanup, and reporting.		  
1:30-2:00 PM
Petit Trianon, 3rd Floor		 Atom Grants: An AI Teammate for Research Development - Presented by: Raphael Bernier Sponsored Demos
Research development and pre-award offices are being asked to do more with the same team: more faculty to support, more proposals to review, and less visibility into where funding is moving. In this session, Atom Grants will demo an AI platform built specifically for research development, one that finds relevant grants for every researcher, checks eligibility automatically, surfaces collaborators, and helps draft and review proposals before submission.		 In this demo, participants will:
1. Identify the operational pressures facing research development and pre-award offices, and where AI can reduce that burden without adding headcount.
2. See a live demonstration of an AI platform that automates grant discovery, eligibility checks, collaborator identification, and proposal guidance.
3. Learn how peer institutions are using AI tools to increase faculty engagement and proposal submission volume.		  
1:30-2:00 PM
Trianon Ballroom, 3rd Floor		 Kuali - Presented by: Amanda Sidoti Sponsored Demos    
1:30-2:00 PM
Rendezvous, 3rd Floor		 Origami Grants - "Do More With Less" in Proposal Development - Presented by: Karthik Kumar Sponsored Demos
It is clear that Research Offices across the country need to do more with less. Solicitations are more complex, bespoke, and collaborative - all while offices have less time, staff, and precedent to follow. We also know that somehow, AI is supposed to help with all of the above, but ChatGPT and other DIY solutions have only gotten us so far.In this software demo, we introduce Origami (Beta), a new AI-powered approach to proposal development, built in collaboration with leading US research universities. We will demonstrate how Origami can help with checklist creation, project management, and pre-submission reviews - saving time and increasing capacity.		 In this demo, participants will:
1. How dynamic grant checklists can help align PIs and administrators right from intake.
2. How AI-driven reviews can stop last-minute submissions from ruining your weekend.
3. Common limitations when using general purpose AI tools for proposal development.		  
2:15–3:30 PM
Rendezvous, 3rd Floor		 Demonstrating AI-Driven Award Data Extraction, Reconciliation, and Setup - Presented by: Chris Steele, Huron & Mary Catherine Gaisbauer & Pam Cabrera, University of California - Santa Barbara Track: AI Tools, Demonstrations, and Case Studies
Award setup is still largely a manual, document-driven process, whether institutions are in the middle of a system conversion or just trying to keep up with daily intake. In this session, we will walk through an AI-enabled award extraction tool that the University of California Santa Barbara used during its Oracle implementation. This will include the process used and what can be done with current solutions to support successful conversions. We will also focus on how the new tool can be used with day-to-day award setup. The session will focus on showing how the tool actually works in practice. We will demonstrate how research administrators use it to upload award documents, extract key award demographics and terms, and review the results directly alongside the source language. The goal is not to eliminate human review, but to reduce re-keying, speed up validation, and surface issues earlier in the award setup process. We will also show how the same tool was used during UCSB’s Oracle conversation.		 In this session, participants will:
1. See how an AI award setup tool is used as part of normal, day-to-day research administration workflows.
2. Understand how AI-extracted award data can be reviewed and validated using clear source context.
3. Learn how the same tool can be applied to data reconciliation during a system conversion.
4. Take away practical lessons from UCSB’s experience that can be applied to award setup and data quality efforts at other institutions.		 Basic
2:15–3:30 PM
Trianon Ballroom, 3rd Floor		 Reducing Pre-Award Burden with AI: Smarter Matching, Stronger Proposals, Better Outcomes - Presented by: Christine Cline, Auburn University, Rob Ellis & Steve Pinchotti from Altum Track: AI in the Research Administration
Research administrators are under increasing pressure to support more faculty, manage complex sponsor requirements, and handle time-intensive tasks like opportunity searches and eligibility checks, all while delivering high-quality proposals with limited resources. Artificial intelligence is emerging as a practical way to reduce administrative burden. This session explores how AI can be integrated into core research administration workflows, with a focus on funding opportunity discovery, eligibility assessment, and proposal development. Attendees will learn how AI-powered tools can help match faculty and institutions to the most relevant opportunities, automate initial eligibility checks against sponsor requirements, and generate proposal content aligned to specific RFP requirements. The session will also highlight how these capabilities connect to broader innovations across the grants ecosystem, including AI-supported peer review analysis, overlap detection, and conversational tools, demonstrating a more unified, data-driven approach to research administration. Participants will gain practical insight into how platforms, such as ProposalCentral.ai and Altum Intelligence, are enabling institutions to better support faculty and accelerate the path from opportunity identification to submission. The discussion will also address responsible implementation, including strategies for safeguarding proprietary data and ensuring AI tools are used in alignment with institutional policies and sponsor expectations.		 In this session, participants will:
1. Identify common pre-award pain points (e.g., manual opportunity searches, repetitive eligibility checks, early-stage proposal drafting) and explain how AI can reduce administrative burden 2. Understand how AI-driven tools can improve funding opportunity discovery and eligibility matching for faculty and institutions 3. Describe how AI can support proposal development with tailored guidance aligned to sponsor requirements 4. Recognize how pre-award AI capabilities connect to broader innovations across the grants lifecycle, including review and compliance support 5. Evaluate key considerations for implementing AI solutions in a research administration setting, including data security, governance, and responsible use		 Intermediate: Participants should have a basic understanding of general grant and research administration workflows (i.e., pre-award processes, proposal development, or sponsored programs support)
2:15–3:30 PM
Petit Trianon, 3rd Floor		 What Research Administrators Actually Think About AI — And Why Leadership Should Listen - Presented by: Dan Harmon, University of Illinois at Urbana-Champaign & Nihal Sarikaya, Northern Arizona University Track: Future of Research Administration in the AI Era
Artificial intelligence is reshaping the landscape of research administration, but how well do institutional leaders understand what's happening on the ground? This session presents findings from multiple surveys conducted across the research administration community, synthesized and analyzed by the REACH AI Working Group — a collaborative body focused on data, analytics, and evaluation for research-focused institutions. Together, these datasets offer a rare, multi-institutional window into how research administrators are experiencing AI adoption firsthand: what they're using, what they're worried about, and where they feel unsupported. Rather than a top-down technology briefing, this session centers the voices of practitioners. Attendees will explore where meaningful gaps exist between administrator perspectives and institutional leadership priorities — across dimensions like governance, training investment, workload impact, and trust in AI outputs. REACH is supported by the U.S. National Science Foundation (grant number: 244978). Content of this session do not reflect the opinions or policies of the NSF.		 In this session, participants will:
1. Identify key themes and trends in AI adoption and sentiment among research administrators, drawn from multi-institutional survey data collected through the REACH AI Working Group.
2. Recognize common gaps between front line administrator experiences and institutional leadership priorities around AI governance, training, and implementation.
3. Apply a practical framework for assessing their own institution's alignment between staff-level AI experiences and leadership strategy.
4. Articulate evidence-based recommendations to leadership and stakeholders that reflect the workforce perspective on AI readiness and support needs.		 Basic
3:45–5:00 PM
Rendezvous, 3rd Floor		 AI4RA - Finding an Actionable On-Ramp for Implementing AI Solutions in Research Administration - Presented by: Parker Grimes, Southern Utah University, Nathan Layman, University of Idaho & Nathan Wiggins, Southern Utah University Track: AI Tools, Demonstrations, and Case Studies & Track: AI Skills for Research Administrators (Hands On)
This session is an interactive workshop, designed to equip Research Administrators with actionable strategies for implementing AI tools at their own institution. Participants will gain hands-on experience testing free open-source tools developed by the AI4RA team that they can readily adapt and deploy themselves, along with an overview on configuring a cost-effective server to host local AI models. Recognizing the value and challenges of working with IT teams, the session will also offer insight into securing approval, building support, and navigating internal processes for AI initiatives. Whether participants are actively deploying AI solutions or are still trying to find the right on-ramp, this immersive learning experience is designed to provide value that meets research administrators where they are - emphasizing active participation and plenty of hands-on sandbox time to experiment with AI tools, server setups, and implementation approaches.		 In this session, participants will:
1. Explore the intersection of AI and data science, including gaining access to open-access AI tools that have been developed specifically for research administration use-cases.
2. Learn how to set up a server for hosting local AI models and gain familiarity with server infrastructure.
3. Inherit strategies for coordinating with your institution's IT department to gain approvals and support in implementing AI solutions.		 Intermediate: None, Participants should plan on bringing a fully charged laptop to this session.
3:45–5:00 PM
Petit Trianon, 3rd Floor		 Ask Anything About Your Research Data: A GenAI Solution for Natural Language Queries on Tabular Datasets - Presented by: Chandni Mathur, University of Illinois Urbana-Champaign Track: AI Tools, Demonstrations, and Case Studies
Research administrators and institutional leaders frequently need timely insights into proposal volumes, department- and PI-level distributions, grant award trends, and detailed expenditure patterns across departments, PIs, and research areas. Traditional approaches rely on manual analysis, custom reports, or static PowerBI/Tableau dashboards. While effective for predefined metrics, these methods fall short when addressing ad-hoc or unexpected questions that arise during strategic discussions. This presentation introduces a practical Generative AI (GenAI) solution that functions as an intelligent, on-demand research data analyst. The chatbot has secure access to raw proposals, awards, and expenditure datasets. Using a multi-agent architecture, it intelligently routes queries to specialized agents (e.g., Proposal Agent, Awards Agent) or coordinates multiple agents as needed. For each question, the system dynamically generates and executes Python code to retrieve accurate answers directly from the source data. Unlike static reports or dashboards, this tool enables users to ask any natural language question in real time, delivering immediate, contextual responses without waiting for analysts or report generation. This significantly accelerates decision-making and empowers leadership with flexible data exploration. The session will include a live demonstration of the tool along with key implementation considerations such as data security, accuracy safeguards, and responsible AI governance.
Example queries include:
1. “Which department has the highest rate of grant awards?”
2. “Which agency is our institution’s highest sponsor?”
3. “Compare proposed versus actual expenditures by sponsor for the last fiscal year.”		 In this session, participants will:
1. Understand how a Generative AI (GenAI) multi-agent solution can transform access to research administration data by enabling natural language queries on tabular datasets (proposals, awards, and expenditures).
2. Explore the architecture and workflow of the tool, including specialized agents and dynamic Python code generation for accurate query responses.
3. Learn how to adapt and apply this GenAI framework to your own institutional use cases, data sources, and research administration needs.
4. Evaluate critical implementation considerations including data security, accuracy safeguards, and responsible AI governance.		 Intermediate: It is recommended but not required that attendees have some familiarity with programming languages, technical concepts, and a basic understanding of Large Language Models (LLMs).
3:45–5:00 PM
Trianon Ballroom, 3rd Floor		 Beyond AI Adoption: A Study of AI Readiness in Research Administration - Presented by: Emily Devereux, Lumi Bakos & Robert Wertz, University of South Carolina Track: Future of Research Administration in the AI Era
Artificial intelligence (AI) is rapidly reshaping higher education research administration, yet little empirical evidence exists regarding the factors that influence AI adoption among research administrators. To address this gap, we developed and validated an AI Adoption Readiness survey instrument specifically for university research administrators and research support professionals. The validated instrument measures multiple dimensions of AI adoption readiness, enabling institutions to assess workforce preparedness for responsible AI implementation. This session presents initial findings from a national survey of 329 university research administrators examining predictors of AI acceptance and adoption readiness. Participants will gain insight into the organizational and individual factors influencing AI readiness, discuss the implications of these findings for research administration practice, and learn how this work will inform the next phase of a longitudinal study of AI adoption across the profession.		 In this session, participants will:
1. Summarize the initial findings from a national study of AI adoption readiness among university research administrators.
2. Evaluate the role of organizational support, governance awareness, and perceived risk in shaping AI readiness.
3. Apply study findings to identify strategies for advancing AI readiness and responsible AI implementation within research administrators’ own institutions.