How UMGC Is Building Accountable AI Around Student Outcomes
UMGC’s AI strategy starts with governance
University of Maryland Global Campus is approaching AI adoption with a clear institutional principle: innovation only matters if it improves outcomes for students.
President Gregory Fowler describes a strategy built around governance, measurement, and practical implementation rather than experimentation for its own sake. The university has already implemented institution-wide AI training and established an AI Governance Board to ensure adoption remains aligned with institutional mission and student support goals.
The approach reflects a broader shift happening across higher education. Institutions are moving beyond curiosity about AI and focusing on how it can responsibly improve student success and operational effectiveness.
Why UMGC built a closed AI testing environment
UMGC launched nebulaONE as a controlled environment where faculty and staff can safely test AI tools, concepts, and workflows before wider deployment.
More than 300 team members are already using the platform.
The goal is not unrestricted experimentation, it is structured evaluation that allows the institution to identify where AI creates value, where it falls short, and how it can be implemented responsibly.
This type of infrastructure is becoming increasingly important as institutions look for ways to balance innovation with governance and accountability.
How AI is being applied to support students
UMGC is focusing AI adoption on practical student-facing applications.
Conversational AI is helping identify and support struggling learners earlier in the student journey. In the Registrar’s Office, transcript review processes that were previously manual are now partly automated, allowing staff to focus more attention on complex cases that require judgment and intervention.
Career Services has also integrated AI into resume review and mock interview preparation. These tools provide students with more opportunities for practice and faster feedback than traditional one-on-one support models alone can provide at scale.
The focus throughout is operational support that strengthens human-centered services rather than replacing them.
Why measurement matters in AI adoption
AI should function as a strategic enabler, not a replacement for teaching, advising, or institutional judgment.
That requires continuous measurement.
UMGC is evaluating adoption rates, operational outcomes, and areas where systems underperform. The institution then adjusts implementation based on those findings.
This approach reflects a growing expectation across higher education that AI adoption should be tied to measurable student impact rather than broad claims about innovation.
What accountable innovation looks like
The question is no longer whether AI is interesting or technically capable. The question is whether institutions can deploy it ethically, transparently, and in ways that genuinely improve student outcomes.
For UMGC, accountable innovation means governance, human oversight, operational measurement, and a consistent focus on serving learners more effectively.
Transcript
0:03
When we talk about innovation at UMGC, I tell our team all the time we’re not here to chase bright, shiny objects.
0:10
Our approach to AI has been deliberate.
0:13
We’re providing AI training for every team member,
0:15
as a baseline, not as an aspiration.
0:18
We established an AI Governance Board to make sure adoption stays aligned with our mission and our obligation to our learners.
0:25
And we adopted nebulaONE as a closed environment where faculty and staff can test new tools, concepts, and strategies.
0:32
More than 300 team members are using it now.
0:35
That infrastructure matters.
0:36
Because the real question is not whether AI is interesting, it is whether it actually helps us serve students better.
0:42
So we’re being very specific about where to apply it.
0:45
Conversational AI now guides earlier outreach to learners who may be struggling.
0:50
In our Registrar’s office,
0:51
transcript review, which used to be largely manual, is now partly automated – freeing staff members to focus on the cases that need real judgment or intervention.
1:01
Similarly, Career Services have integrated AI into resume editing and mock interviews, giving students more practice and faster feedback than we could ever provide one-on-one.
1:10
Let me be clear.
1:12
AI is not replacing teaching, advising, or judgment.
1:15
It is a strategic enabler.
1:17
The way we know it is working is through measurement of outcomes, of adoption, of the areas where it comes up short.
1:24
Then we adjust based on what we learn.
1:27
That is what accountable innovation looks like here –
1:29
practical, ethical and always tested against the benchmark of whether it genuinely serves the people who partner with us on their learning journeys.