The AI-Native University Must Guard Against Getting Better at the Wrong Thing (Greg Fowler, UMGC)
“If we can reinvent education for battle zones, jungles, and deserts, we can reinvent it for the age of AI.”
I worry that higher ed will use AI to become more efficient at the wrong thing.
Better at coursework. Better at administration. Better at training people for the entry-level roles of yesterday, rules-based and routinized work, just as that work gets hollowed out.
That would be especially bad for the students who most depend on education to gain economic agency.
One reason I wanted to talk with Greg Fowler, president of UMGC, is that he seems unusually clear-eyed about that risk. Part of what makes him such a credible guide is the institution he leads. UMGC has been adapting to novel conditions for decades. This is a university with 175 physical locations and roughly 100,000 students around the world. Its modern identity was forged when it answered the U.S. government’s call to bring college to service members in postwar Europe. Since then, it has served learners across all seven continents, including in battle zones, deserts, military bases, and Antarctica. Reinvention is part of the culture.
Greg himself feels shaped by that tradition. He is a storyteller, a movie buff, and a leader who knows institutions do not change because someone unveils a new strategic plan. They change when people have a convincing story about who they are, what they are for, and what must change. Higher ed does not have enough of that kind of leadership right now.
That instinct for reinvention leads Greg back to the humanities. If machines can generate more of the output, universities need to care much more about the capacities underneath it: judgment, communication, creativity, discernment, and the ability to tell truth from fiction. As Greg puts it, “If we teach human skills with rigor and care, I think we will see a generation of humanists design fair and sustainable systems, reckon with injustice, create incredible art and innovations, and become, I hope, more connected than divided.”
That matters to me because I do not want an AI-native university that is just a faster, cheaper version of the wrong thing. I want universities, especially those serving lower-opportunity students, to prove they are helping people build real capability, real adaptability, and real economic agency.
This conversation gets concrete about what that looks like at UMGC. We get into assessment, and why Greg thinks AI can help scale practical, immersive evaluations of the skills that actually matter. We talk about rebuilding the student experience layer with AI companions and coordinated supports. And we talk about what real personalization could look like, with Greg using The Karate Kid to explain how different learners can take different paths toward the same standard.
I loved this conversation because it works on both levels at once: institutional purpose and actual design. Greg is one of the few leaders I know who can speak credibly to both.
Thanks for reading,
Allison
On The Stories Shaping AI Innovation at UMGC
ALLISON: What’s something you’ve changed your mind about in the last year or so?
GREG: I’ve been impressed by my team’s willingness to engage with the AI conversation at UMGC. I expected more pushback, but the more we’ve involved them in developing our approach, the more open they’ve become to innovating solutions. The response has moved well beyond keeping students from cheating on papers—a very different place than we were 12 months ago. The bigger challenge is separating signal from noise within the AI conversation right now.
ALLISON: Why have they pleasantly surprised you on this front?
GREG: The core of our strategic narrative is positioning AI not as a bright shiny object—or an innovation like the MOOC that stays isolated to higher ed—but as something with the potential to impact how we learn, think, work, live, and govern ourselves. That’s prompting more engagement and dialogue among faculty and admin alike.
ALLISON: As a leader, what are some of the approaches you’ve used to bring your teams and your staff along?
GREG: As an English major and movie buff, I’m always attentive to narrative—how do we tell stories that build understanding and belief in what we want to do? Any strategic narrative begins with the story already playing in the public consciousness. When team members clash, I ask them to share their respective narratives so we can find points of agreement and identify opportunities for collaboration.
We’ve also worked hard to dissolve the silos that emerge within large institutions, especially when major innovations arrive. AI requires a coordinated, enterprise-level, all-hands effort right now. It’s important to understand, for example, how an executive assistant for student affairs impacts library systems. I’m proud of how our team is doing this work—it’s smoothing our path to adoption and innovation.
ALLISON: I still think that within many institutions, faculty, staff, and admin alike are still denying, or perhaps aren’t aware, that AI is going to be transformative. You’ve worked in institutions of all shapes and sizes. What is it about UMGC’s structure that has allowed it to move in step with the pace of this disruption?
GREG: UMGC is a global institution—175 physical locations around the globe—and that requires us to operate more nimbly than many other institutions. We serve students worldwide through remote learning, but we also have people teaching, recruiting, developing partnerships, and supporting students in those locations too.
This has always been UMGC’s story: seventy-five years ago, at the end of World War II, we were the only institution to answer the US Government’s call to bring college to the 300,000 service members who stayed behind in post-war Europe. In a week’s time, the state of Maryland sent seven faculty members to Heidelberg, Germany, to figure out the model.
Ever since, our story has been one of intrepid problem-solving, on the ground and in real time. We’ve served students on all seven continents—we sent our first students to the South Pole in 1994 and on occasion have had students studying in Antarctica. Active battle zones, deserts, beaches, jungles: we’ve been figuring out how to deliver exceptional education anywhere. That’s our culture; that’s our mission.
That culture is why we’ve been able to bring so many team members onboard: if we can figure out how to do this in an active battle zone, we can figure out how to do this with AI.
ALLISON: Culture is made of the stories we tell ourselves about who we are. And so it sounds like you are attributing this effective change management process to culture, more so than the brass tack structures of the institution.
GREG: Yes—our culture and institutional history are critical to the pace of adoption happening now at UMGC.
ALLISON: I’m curious: as a movie buff, is there a particular movie that inspires your leadership, especially at an inflection point of change like this?
GREG: I’m always referring to The Karate Kid and The Neverending Story—two absolute favorites.
The Karate Kid shows us that there are always different pathways to successful outcomes, and that what works for one student may not work for another. Johnny and Daniel take entirely different paths to the tournament—both valid, but with very different resources and mentors. That’s a good metaphor for what post-secondary education is grappling with right now. If this is a game about clearly defined skills, how do we build those skills in a way that works for each learner? How do we get them into the tournament?
AI is encouraging us—as people, as an industry, as a society—to reflect on the purposes we serve, the value we provide, and the structure of our systems. In The Neverending Story, Bastian is similarly called to self-reflection, to see himself for who he really is. It’s fascinating to see how AI is holding up a mirror to so much of what we do—from curriculum design to student experience to assessment—and asking us to question long-held assumptions about those choices.
On Why the Future of Higher Education Needs to Be Humanist
ALLISON: What do people systematically misunderstand about higher education’s current moment?
GREG: College is not a monolithic experience—that cultural narrative has become far too narrow. We need every stakeholder and regulator to appreciate that higher education offers a variety of different and valuable experiences.
I went to an HBCU for very specific reasons that differ from the student going to College Park or choosing an R1 Big Ten institution. Students choose institutions with religious and military affiliations; they choose small liberal arts colleges, which are themselves a unique experience. They choose to start in community colleges, then transfer. And colleges serve so many different types of learners, from all stages of life: the majority of students don’t live on campus anymore, and a quarter of undergraduate students today are over the age of 25.
Eighty percent of UMGC’s learners work full-time, and about seventy percent are first-generation college students. College is not their “job” the way it is for traditional students—our students tell us coursework will never rank higher than third, after family and work. We can’t ask them to spend 40 hours a week on their programs. We need a learning environment that reaches them at 9:30PM, after the kids are in bed, and helps them leverage the time they have. My second month here, I got an email from a student out in the field with his night goggles, trying to figure out how to do his homework. That’s the learner we’re trying to reach.
Legislators in particular need to understand the diversity of students and experiences within higher education in order to correctly proportion funds and supports: these non-traditional learners are, ironically, many of the voters they claim to care most about.
Unfortunately, higher education hasn’t done a good job of opening up the black box and demonstrating its real value. Colleges have said “trust us—we’ll get you a job,” and students and parents have accepted that, while colleges haven’t held themselves rigorously accountable for outcomes.
Think of it this way: when I hire a personal trainer, I come in with a goal. That trainer develops a plan to get me from couch to marathon, or from 90lbs to 350lbs on the bench—based on what I already like to do and where I’m starting. A good trainer checks progress every two weeks. And at the end, there’s a clear success criterion: did I run the marathon? Did I get close? What can I do now that I couldn’t before?
We need to tell a similar story of growth to our learners and the businesses we work with.
ALLISON: Be as provocative as possible in painting a vision of what the AI native university looks like in 2035, for your population of learners: adults, military, student parents, full-time workers. What’s the most audacious vision?
GREG: I want the university’s work, writ large, to be about mastering human skills—critical thinking, effective communication, understanding diverse populations—because we must master these in an AI-powered future. If we lose them, we lose our ability to separate truth from fiction, we lose our relevancy within our economic engine, and we put our democracy at risk. I’m a humanist, so I’ll never stop saying it: the liberal arts remain critical to that effort. I don’t know what 2035 looks like if we don’t focus on these skills today.
I do think AI will tremendously aid the humanist orientation of higher ed. I was just looking at a tool that lets you speak a foreign language without developing fluency—that opens opportunities to learn, explore, and collaborate globally, where a language barrier would have prevented it before. What would it mean to become this kind of connected, creative, global citizen? Rather than continuing to distance ourselves from one another, my hope is that we leverage AI to make us more aware of and collaborative with each other.
One of the biggest challenges that we’ll need to figure out—likely at the policy level—is how to square the technology’s capabilities with respect for personal privacy. There is so much potential in a 24-7 companion that can personalize almost anything I want to learn—but as a colleague recently argued, no technology has ever escaped being weaponized. How, then, do we make this pivot? How do we ensure this story isn’t a Shakespearean tragedy, but a comedy—one where we all come back together within a sustainable community?
On Why Practical Assessment and Comparability Are Not Mutually Exclusive
ALLISON: In my view, assessment is the most important systemic barrier to achieving this vision for education. AI’s affordances for assessment are exciting: it has the potential to scale both new modalities and new abilities for assessing the enduring skills we’ve been discussing. If you were to put your thumb on the scale, what changes in assessment would you most like to see in the next two years?
GREG: In my view, AI is going to help us scale practical assessment, especially via immersive, virtual experiences. We will be able to test students’ ability to respond to a crisis in the ER—how do they demonstrate the disposition, physical skills, and communication skills in handling that situation? Or, how does a teacher in training assess, curate for, and interact with a gifted student, or a student who has learning challenges? How effectively are you communicating at that moment? What practice do you need to get better at these skills?
There is an important conversation to be had about what skill sets we will be giving up if we move towards this mode of assessment on a larger scale, but that conversation is eternal. Skill sets either evolve or they aren’t ones that we use anymore. But it doesn’t mean that other skills won’t replace them. What are those skills, and how do we make sure we tag and develop them in a way that continues to give us an edge? That’s the hard part.
ALLISON: What’s amazing about this experiential vision is that learners gain knowledge mastery while also practicing enduring skills. You can also see what happens when learners struggle: do they try again, how they work with others, how they address novel problems.
What are the practical barriers to implementing this kind of assessment in higher ed?
GREG: Cost, for one. These simulations are expensive, and if we don’t scale this right, we will widen the gap between the haves and have-nots.
Equity is another concern: immersive experiences must not replicate higher ed’s many systemic biases. If I put everyone into a dojo, I’ve lost the Daniel LaRussos of the world. These environments need to be designed in ways that don’t limit students’ success.
We have two cool, relevant projects on this last point, what we call Project Sherpa and Project Doppler. Sherpa provides a digital assistant that adapts to the needs of each learner, creating a tailored, personalized experience throughout the student journey. Doppler provides real-time forecasting based on students’ experiences and performance to help us understand what will lead them to success. It matters here because it is always responsively assessing where students’ competencies and roadblocks lie—the vision for both is to scale really high-quality, personalized experiences and assessments.
Affordability and equity were top of mind as we developed these tools, and they need to remain so for anyone building new assessment models going forward.
ALLISON: One common critique of this assessment mode is that we prize comparability: our funding mechanisms are based on it, and we advance learners and funnel them into opportunities based on test performance or GPA. How are you wrestling with that problem?
GREG: Comparability and practical assessment are not mutually exclusive. Think about the tournament in The Karate Kid: even though Johnny and Daniel take very different learning pathways that work best for them, they both have to perform at a similar level on the same task, in the same environment. We are still equipping the healthcare worker or the teacher to be effective in their roles on day one. How they get there might look entirely different—AI can help create the environment that truly meets them at their starting point and channels their focus to the next skill to master—but demonstrating skills in a comparable environment has always been at the core of practical assessment (which is not new).
Here’s another way to think about it: there are many ways to drive to Boston. I can take I-95 or I-93, side streets, or the main thoroughfare. But as I get closer to home, the options narrow. I can’t avoid turning down my street, then my driveway. Three different routes, but one driveway in the end.
ALLISON: That makes sense—more divergence in the how and the process and the path, even if we practically need convergence in comparability or on competency assessment, especially with really high stakes gates into employment, like healthcare, aviation, education, etc.
GREG: Right. It’s an evolving and urgent question for educators across the disciplines: how do we leverage the endless and incredible experiences of the individual to maximize their learning, while also still converging around a shared definition of what it looks like to be career-ready? As learning gets more personalized, we can’t forget to set those important “Home” locations in the GPS.
On Closing The Talent-to-Opportunity Gap
ALLISON: This is a tactical question. We’ve discussed Project Sherpa, and I think it’s one of the most intuitive product-problem fits for AI within the university. Student experience covers a vast surface area—historically siloed and hard to navigate. But when institutions have managed it well, through holistic advising for example, the efficacy is extraordinary. It sounds like you’ve arrived at a similar conclusion. What’s the vision for student experience at UMGC, and what’s standing in the way?
GREG: The second part is the easiest to answer: Honestly, the technology is just not there yet. We’re having these conversations internally, as well as with Microsoft, Google, and Amazon. Realistically, we need multiple AI agents operating under a governance layer that sets rules for how they interact. We also lack the data infrastructure to store and connect the information such a system would require. You can’t simply bolt a solution like this onto existing systems, because those are built around siloed, linear platforms: Student Information Systems (SIS), Learning Management Systems (LMS), and Enterprise Resource Planning tools (ERP), each managing a separate slice of the student experience. It’s a very complex operational ecosystem.
ALLISON: And, ironically, we also can’t tell much about learners’ goals and motivations, within existing data sets.
GREG: That’s exactly right. Exactly right. That information has to be somewhere, but that research takes knowledge, energy, and resources. The beauty of AI, however, is that it ideally helps make complex tasks like these workable.
To sit a moment with the first part of your question: I think we are at the cusp of narrowing the talent-to-opportunity gap for perhaps the first time in human history. A class of 40 students is a class of 40 different universes, every one with immense potential, every one with a different history. Every instructor dreams of reaching each student they teach, but that’s impossible without individualizing almost every component of the course for each of those universes. AI could be the catalyst, at last, for doing so.
It won’t mean we can get everybody a job. It does mean that we can give everybody the skills—and a way to document them—that allows them to get a job they might not have been able to get before. That’s really exciting for students and universities alike—and something employers can get behind too.
One Small Signal
ALLISON: What’s one small signal in the world right now to which we should be paying more attention?
GREG: When I watch kids engage with this technology, I see them becoming less connected with each other and more distant from our shared world. They will become native users of AI, but technology moves exponentially faster than humans do—I fear our children will have unfettered access to this technology without the developmental readiness and skills they need to use it well.
As Shakespeare knew, young people are impetuous and passionate, and they are still learning how to take measured action, to be patient. Romeo and Juliet is a tragedy for a reason—young lives are lost because youthful passion is mismanaged by the adults entrusted with their care. We can’t afford to mismanage a generation of young people.
ALLISON: As a parent, I think about this a lot: what will my kids’ relationship with machine intelligence look like? What trust and connection will they build with AI? To me, a relationship can only be human-to-human. But the next generation may orient around “relationships” in an entirely different way.
GREG: That’s why it’s so critically important for us to understand what it means to be human and what the humanities do: they teach us, in a methodical and culturally-embedded way, about ourselves and our legacy on this planet. They empower us with the wisdom to build a better one.
When I was dean of liberal arts at Western Governors and chair of a number of advisory boards, I led an interdisciplinary conversation with the liberal arts board about what competency should look like. We ended up describing a set of competencies around understanding creativity—what drives people to create, their relationship to their creations, and how those creations reflect our entangled relationships to the material world and the cultures we build. We wanted learners to be able to read, interpret, historicize, and analyze relationships between people and cultural artifacts—including technology, politics, and science as well as art—which always reflect ourselves and our social constructs. In that work lies the wisdom to parse truth from fiction, to truly create, not just generate. In my view, creativity is the hard skill humans must hold on to.
If we teach human skills with rigor and care, I think we will see a generation of humanists design fair and sustainable systems, reckon with injustice, create incredible art and innovations—and become, I hope, more connected than divided in a world where so many barriers to knowledge and communication have collapsed.
That’s the world I want to live in, and the story I want to tell.