Key Takeaways: Nuventive’s seventh webinar in our 10-part artificial intelligence series explores how AI is reshaping, enhancing, and accelerating the work of Institutional Research teams.
Webinar Details: Artificial Intelligence for Institutional Research: New Tools, New Strategies, New Questions
Featured Speakers:
• Dr. Jason Simon, Former Associate Vice President – Data, Analytics, and Institutional Research, University of North Texas
• Dr. Eric Zeglen, Executive Director of Institutional Research, Assessment and Planning, Shippensburg University of Pennsylvania
Moderated by:
Dr. Randy Swing, Advisor to Nuventive
Each week, we distill key takeaways and share short clips from our conversations with presidents, provosts, and leaders in institutional research, assessment, and technology—turning big ideas into practical steps for improvement.
This week, we look at how leaders in Institutional Research are adopting and implementing AI.
Understanding AI Maturity in IR Offices
Building the foundation for thoughtful, long-term AI adoption
Survey results from a poll conducted by the Association for Institutional Research (AIR) show many IR offices describing AI maturity as “not occurring” or “reactive,” but this does not reflect a lack of progress.
Dr. Eric Zeglen explained, IR teams often operate within complex environments shaped by system implementations, resource considerations, and institutional priorities—all of which influence how quickly new technologies can be adopted.
Even so, IR offices are laying essential groundwork: strengthening data structures, developing governance, and using generative AI in targeted ways such as communication, summarization, and workflow support.
AI’s Role in Institutional Research
Amplifying—not replacing—the value of IR professionals
Both Dr. Zeglin and Dr. Simon emphasized that AI alone is not a threat to IR roles. The concerns echo earlier reactions when statistical software became widely available, yet IR remained essential in interpreting results responsibly.
AI automates repetitive tasks but enhances the strategic contribution of IR, enabling teams to devote more time on student success questions, program effectiveness, and institutional strategy.
Opportunities for IR Offices to Improve with AI
Communication, efficiency, and workflow acceleration lead the way
According to Dr. Zeglen, communication represents one of the most immediate opportunities. AI helps IR teams create clearer summaries, translate dashboards into digestible narratives, and tailor insights for different audiences—cabinet, deans, faculty, deans, advisors, and more.
Dr. Simon highlighted efficiency as another major advantage. AI reduces friction in tasks such as qualitative analysis, code generation, drafting communications, and producing visual representations—enabling IR professionals to focus on deeper analysis and meaning.
Priorities in AI for IR Offices
Data protection and responsible use are foundational
Data privacy and governance are central to AI adoption. Dr. Simon emphasized the need for strict protocols to prevent sensitive institutional data from entering public AI tools. His campus created a generative AI task force to develop guidelines for faculty, staff, and administrators, including secure workflows and recommended syllabus language.
Dr. Zeglen added that IR professionals must fully understand system stability and data architecture before implementing advanced AI solutions. IR plays a critical leadership role in guiding ethical use and helping campus partners understand both the opportunities and limitations of AI.
AI, Professional Development, and Capacity in the IR Role
Curiosity, shared learning, and gradual skill-building
Professional development begins with mindset. Dr. Simon described how he used ChatGPT to create self-guided learning, then expanded into structured resources such as like LinkedIn Learning, Coursera, and Google’s AI certificates. Even brief, consistent learning—reading an article or watching a short video—builds momentum.
“The first critical acknowledgment you have to make is: do you have the mindset, and the interest, and the desire to want to learn? I would encourage us all in the field to be really curious. If you don’t learn, someone else is going to learn, and you never want to be left behind,” Dr. Simon explained.
Closing Advice from the IR Experts
Start small. Stay curious. Build responsibly.
Dr. Simon encourages IR teams to begin with small, manageable applications—drafting emails, analyzing comments, generating visuals. Experimentation builds comfort, and curiosity keeps IR professionals current in a rapidly evolving landscape.
Dr. Zeglen recommends a thoughtful, patient approach centered on governance, communication, and scalability. Small wins compound over time. AI is here to support IR—not replace it—and thoughtful adoption ensures long-term success.
Looking Forward
Next in the series
Up next in our AI webinar series, we turn to the role of artificial intelligence in documenting student learning and institutional achievement.
Documenting Achievement: Is There a Role for AI in Higher Education Assessment?
In this session, our panelists explore how AI can support meaningful assessment practices without compromising academic integrity, faculty ownership, or the nuance required to understand student learning. Stay tuned as we distill the key insights in next week’s blog.
Featuring:
Dr. Jenn Klein, Director, Institutional Assessment Systems, Gonzaga University
Dr. Jessica Cannon, Associate Professor of History, University of Central Missouri
Moderated by:
Dr. Jim Moran, Advisor to Nuventive
Recorded: April 4, 2024
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