Month: January 2026

Key Takeaways: Nuventive’s tenth webinar in our AI series examines what is and isn’t working as higher education leaders move from AI experimentation toward adoption.

Webinar Details

Exploring What Is (and Isn’t) Working: Executive Perspectives on AI in Higher Education

Listen to the audio replay now
Recorded: September 4, 2025

Featured Speakers:
Dr. José-Marie Griffiths, President, Dakota State University
Dr. Rick Burnette, Sr. Vice Provost & Chief Strategy Officer, Florida State University
Tracy Woods, Director, Azure Cloud & AI Platform Solution Engineering, US SLED, Microsoft

Moderated by:
Dr. David Raney, CEO, Nuventive

Each week, we distill key takeaways from conversations with presidents, provosts, and leaders in institutional research, assessment, and technology—translating complex topics into practical insights that support data-informed improvement.

In this discussion, panelists examined where institutions are seeing progress, where challenges remain, and how leaders are balancing innovation, governance, and human impact.

As AI becomes more integrated into daily academic and administrative work, it is increasingly experienced as more than a traditional tool. Its ability to interact, respond, and adapt is influencing how people engage with technology, make decisions, and learn.

Beyond questions of capability or risk, this human dimension invites thoughtful leadership and intentional decision-making. For institutional leaders, it presents an opportunity to guide how AI complements human judgment, supports learning, and reinforces the values that shape campus life as technology continues to evolve.

Panelists emphasized that their early AI efforts focused on experimentation and shared learning, supported by intentional leadership.

At Dakota State University, AI was already embedded in the curriculum when generative AI entered public use. Faculty expertise allowed the institution to move quickly, integrating AI into general education and introductory courses and preparing students to apply it within their disciplines. As AI evolved rapidly, leaders considered how institutions could balance responsiveness with existing academic planning cycles.

“We have to recognize that we’re constantly going to have to adapt and adjust to this environment as it evolves,” Dr. Griffiths said.

At Florida State University, faculty were positioned as partners in shaping AI adoption through exploration, shared learning, and cross-disciplinary collaboration. Panelists emphasized alignment and shared ownership as key drivers of progress.

As AI adoption evolves, institutions are thoughtfully balancing innovation with responsibility, particularly as policy frameworks adapt alongside technological change.

Leaders are focusing on creating guardrails where risk is highest, while allowing flexibility elsewhere. This has meant emphasizing education over enforcement, offering model syllabus guidance rather than mandates, and separating innovation conversations from academic integrity processes.

Most guardrails center on data security, intellectual property, and student privacy. Rather than restricting use, institutions are steering faculty and staff toward approved environments that protect data while supporting experimentation.

“Creating those guardrails and making it safe for them to use the tools and giving them permission to use the tools is the most important thing,” Woods said.

Challenges often highlight opportunities to strengthen critical thinking and reinforce the role of human judgment alongside AI.

Early AI use cases are demonstrating how thoughtfully applied technology can support institutional goals and elevate everyday work. Across campuses, AI is helping reduce friction in administrative processes, enabling staff to spend more time on high-value, human-centered work.

Within academic and student-support environments, AI is contributing to more connected and personalized learning experiences—supporting student pathways, informing course planning, and extending faculty-led innovation through tools designed around approved materials and local context.

Dr. Burnette posed the question, “If we’re a campus of 43,000 students, can we personalize the education for all of them?”

Meaningful impact has come from intentional applications aligned with clear priorities—using AI not as a blanket solution, but as a focused tool in service of learning, access, and effectiveness.

As institutions continue their AI journeys, success is increasingly defined by impact rather than adoption alone. Leaders are looking beyond whether AI is being used to how it strengthens learning, prepares students for the workforce, and advances institutional goals.

Workforce readiness remains a clear indicator—ensuring graduates are equipped to work thoughtfully alongside AI in evolving professional environments. At the same time, leaders are paying close attention to cultural signals that suggest this impact is taking hold, including growing acceptance, curiosity, and engagement among faculty and students.

“One of the measurements has really been acceptance and actually enthusiasm from faculty and students in terms of using it, playing with it, and sharing successes,” Dr. Griffiths said.

While productivity gains and time savings are measurable, these cultural indicators reinforce a broader focus on institutional effectiveness and the student and faculty experience as the outcomes that matter most.

Building on these measures of success, leaders are also considering how AI is shaping the broader student experience. Across disciplines, AI skills are increasingly viewed as foundational, prompting institutions to integrate AI concepts across curricula rather than confining them to standalone programs.

At the same time, leaders are engaging thoughtfully with the human dimension of AI. As interactions become more sophisticated, institutions are reinforcing balance—using AI to support learning while continuing to prioritize human connection, well-being, and community.

“The answer is to make sure that our students don’t isolate themselves,” Dr. Griffiths said.

Through literacy, intentional design, and continued emphasis on human-to-human engagement, institutions are preparing students not only to work alongside AI, but to thrive in environments where judgment and connection remain essential.

Throughout the discussion, two themes emerged: progress accelerates when institutions learn from one another, and leadership matters most in shaping how AI supports people. As AI becomes more embedded across higher education, its value will be defined not just by capability, but by how well it strengthens human judgment, connection, and institutional effectiveness.

---

As this series concludes, the focus turns to how institutions use evidence to guide action. Our next blog series will explore data-informed improvement—examining how higher education leaders connect data, strategy, and continuous improvement to support better decisions across the institution.

To view the full Human Factor of AI in Higher Education webinar series, including all sessions and replays, visit:
https://go.nuventive.com/human-factor-of-ai-in-higher-ed

Interested in learning more about the Nuventive Improvement Platform?