In a webinar series this week hosted by the American Association of Colleges and Universities (AAC&U), AI facilitators at institutions of varying sizes and focus areas said that, ultimately, institutions will need to blend the two. However, different factors in an institution’s culture and governance structure can determine which starting point works best.
TOP DOWN
At institutions like the University of North Carolina (UNC), Charlotte, and Albizu University in Puerto Rico, AI adoption began with executive-level framing and coordination.
At UNC Charlotte, senior leadership explicitly positioned AI as a strategic priority as early as 2022. Kiran Budhani, director of teaching and learning innovation at UNC Charlotte, said a memo from the chancellor and provost framed AI as “acceptable” and necessary for workforce preparation. That signal enabled a sequence of structured initiatives: a formal AI task force including nearly 400 campus participants, followed by the creation of a standing leadership body charged with implementing recommendations.
The university has since moved into large-scale curricular redesign, including two new undergraduate and graduate degrees in AI and multiple minors.
Albizu University followed a similar top-down trajectory, as its board of trustees issued an initial AI policy and convened a committee. Chief Academic Officer Berta Rios said these efforts were baby steps, and the real change happened when the university gathered more input and started to plan. The university went on to host faculty forums, gather input and apply for funding for 50 special projects to advance AI implementation. Though they didn’t receive funding, Rios said the applications helped the university develop a plan and understand the required budget for each step.
AAC&U’s webinar panelists said an institution’s approach to AI implementation should reflect its goals. For example, Mid-State Technical College, a career-oriented college in Wisconsin, approached integration through workforce alignment. This began by establishing AI as a priority in the institution’s strategic plan.
“We really made sure that we had clear institutional AI policy and ethics structure that guided our future decisions,” said Desiah Melby, an instructor and chair of the college’s AI in teaching and learning group.
Relying on faculty feedback from an ongoing committee, as well as feedback from workforce partners, Mid-State went on to provide syllabus language and grading rubrics that signal levels of AI use allowed. AI is now embedded as an employability skill across programs, Melby said.
“As you can well imagine, trying to create something that works for cosmetology, diesel mechanics and general education is a wide variety of areas to hit,” she said.
BOTTOM UP
By contrast, institutions like Berry College and Gettysburg College began with faculty-led exploration and gradual institutionalization.
At Berry, a history faculty member convened informal gatherings to discuss AI with peers before the college had shared any institutional guidance, according to Provost David Slade. From that starting point, the college defined four goals: develop training resources for faculty and staff, articulate student learning goals related to AI, support shared policies, and approach academic integrity in developmental, rather than punitive, ways.
Slade said implementation has been deliberately incremental — about one-third of faculty members have participated in discussions and studies to date, part of the AI training goal.
“We really tried to weave these operational and pedagogical conversations together, and also let them both have the space that they need,” he said.
Berry College faculty are now required to include AI guidance in their syllabuses, and the college provides grants to support course-level implementation. Parallel to the academic work, Berry’s chief information officer launched operational AI projects, Slade said.
Gettysburg College similarly prioritized conversation. Michelle Schmidt, the college’s associate provost for faculty affairs, said the initial focus was on academic integrity, with discussions between faculty and student government groups about how AI intersects with the school’s honor code. From there, the institution created multiple arenas to gather feedback: faculty discussion circles, student forums involving about 50 participants each, and hands-on demonstrations of how to use AI tools.
Schmidt said what started as conversations about cheating evolved into conversations about workforce preparation.
“We began to engage in more conversation about those questions related to what students need when they graduate, so that we could inform what we’re doing here on campus based on what’s going on outside of campus,” she said.
Gettysburg College is now moving into a three-year initiative, with year 1 focusing on exploration and learning, supported by a newly appointed faculty director and AI coordinators at the department and division levels. Schmidt said later phases will define institutional philosophy and the college’s overall approach.
In Nebraska, Creighton University tried to accelerate the process of moving changes up the ladder as much as possible, according to Guy McHendry, director of Creighton’s undergraduate core curriculum. Leaders embedded generative AI learning goals into general education and moved through a full faculty governance process — including curriculum committees, college-level approvals and provost sign-off — within a single academic year.
Now, students encounter AI in a first-year advising course, a required communication class in partnership with the library, and finally a discipline-specific course embedded into their major. McHendry said that prior to these updates, the general education curriculum had not seen major changes in 15 years.
“We have started to think of AI as a change management problem,” he said. “If you don’t put resources into faculty development, your efforts are going to fail, and it doesn’t mean you spend lavishly, but you can’t pretend that your campus can pivot for free.”
