The Pulse of Higher Ed

By Stacy Chiaramonte

The UPCEA AI Study Group pilot confirmed something we heard consistently from participants: institutions are ready to move beyond simply exploring AI and toward building practical, responsible approaches for putting it to work.

Across the pilot, participants discussed AI implementation, governance, institutional readiness, use cases, change management, student support, faculty development, and the practical work required to move AI from possibility to implementation. One of the strongest themes was that AI adoption is not simply a technology challenge but rather it is a leadership, organizational, and change-management challenge.

Participant feedback also reinforced the value of learning alongside peers. In the post-pilot survey, 80% of respondents rated the Study Group as valuable or very valuable, and participants most often pointed to peer learning, institutional examples, and the opportunity to hear how others are navigating similar challenges. Confidence also increased substantially: after the Study Group, 90% of respondents rated their confidence in advancing AI work or building a plan as somewhat high or very high.

What We Learned from the Pilot

Several themes from the pilot are shaping the next iteration of the AI Study Groups.

• Start with the problem, not the tool.
  Some of the most productive conversations centered on clearly defining an institutional or unit-level challenge before selecting an AI solution. Participants saw that meaningful AI implementation often begins with a specific problem, a defined audience, and a manageable scope and not with a particular technology.
• Move from experimentation to intentional implementation.
  The pilot reinforced the value of a “crawl, walk, run” approach: start with a contained use case, build trust and understanding, demonstrate value, and scale thoughtfully. Participants also explored the distinction between what is possible, plausible, and probable when considering AI initiatives.
• People and processes matter as much as technology.
  Governance, communication, staff capacity, trust, training, workflow design, and institutional alignment repeatedly surfaced as critical components of implementation. As participants noted throughout the pilot, the hardest barriers to AI adoption are often cultural and organizational rather than technical.
• Peer learning accelerates progress.
  Perhaps the clearest lesson from the pilot was the value of bringing members together to compare approaches, share challenges, and learn from real institutional examples. Participants left the pilot with either a specific workflow or use case to pursue or a clearer direction and next steps.

A New Four-Week Format for the AI Study Groups

Based on participant feedback, we are refining the next series of AI Study Groups into a more focused four-week experience.

The new participant journey is designed to move members from assessment to action, grounded in the Capstone Framework.

Assess current AI maturity → identify a priority business need → build an action roadmap → test, refine, and communicate the plan.

Participants may develop a roadmap for their institution, division, or functional unit, depending on their role and level of influence. The experience will be grounded in the UPCEA AI Maturity Index and will combine peer discussion, practical application, and roadmap development.

Over four sessions, participants will:

• Week 1: Set the Stage
  Establish a common framework for understanding the current AI landscape, institutional opportunities and risks, and where AI fits within their broader higher education strategy. Participants will begin considering institutional AI maturity and readiness.
• Week 2: Define What Is Possible, Plausible, and Probable
  Explore current challenges and opportunities, consider potential AI tools and approaches, and identify a specific business need that could benefit from AI adoption or expansion.
• Week 3: Build an Institutional AI Action Roadmap
  Translate ideas into short- and long-term actions, consider the people and processes necessary for implementation, and use peer feedback to strengthen the roadmap.
• Week 4: Finalize the Plan
  Test the plan with colleagues, refine the roadmap and how it will be communicated, and identify practical next steps for moving the work forward.

The goal is not for participants to leave with every AI question answered but to leave with greater clarity about where their institution or unit is today, what problem they are trying to solve, and what practical steps can move the work forward.

Join an upcoming AI Study Group

UPCEA is offering four upcoming AI Study Group cohorts:

• October 8, 15, 23 & 29 | 2:00 p.m. ET
• January 19 & 26; February 2 & 9 | 3:00 p.m. ET
• April 22 & 29; May 6 & 13 | 3:00 p.m. ET
• June 8, 15, 22 & 29 | 12:00 p.m. ET

Registration for the October cohort is now open. Registration for subsequent cohorts will open approximately two months before each Study Group begins.

As AI continues to evolve, institutions will need more than information about the latest tools. They will need frameworks for making decisions, opportunities to learn from peers, and practical ways to translate experimentation into responsible action.

That is what the next generation of UPCEA AI Study Groups is designed to provide.

Register for the October Study Group

Stacy Chiaramonte is the Senior Vice President of Operations and Strategy for UPCEA’s Research & Consulting division. Prior to joining UPCEA, she spent 13 years at Worcester Polytechnic Institute, most recently as the Associate Vice President of Graduate and Professional Studies. To learn more about UPCEA, contact [email protected]. 

Content for this resource was refined with the assistance of AI. All text has been thoroughly reviewed, edited, and approved by UPCEA staff with subject matter expertise. References and links have been verified for accuracy and reliability.