AI in Higher Education: Transforming Student Engagement and Enrollment

Sathish:

“Welcome to our second episode on AI in higher education. James, could you give a quick introduction to the audience?”

James:

Pleasure to be here. Just to confuse people, I am English. The accent comes from London and Bath in the UK, but I live in Chicago and work at DePaul University. It is a fantastic place to be. Every day there are new things to discover, fun projects to work on, and happy students.

Sathish:

“You have spent close to two decades at DePaul across online learning, digital marketing, and now AI. How has higher education changed during that time?”

James:

The biggest change is that AI is transforming the workplace. Universities used to have a roadmap proven by experience: this is your potential career path, this is what employers want. That has changed. We used to tell students to plan for two or three careers, and at least we knew what they were. Now universities say plan for six or seven careers, and maybe 60 percent of those have not been defined yet. So the challenge is preparing students with a deep level of critical understanding, plus the curiosity and nimbleness to see where new opportunities are emerging and move into them productively.

Sathish:

“Why did DePaul create the AI Institute, and what role does it play in AI adoption?”

James:

Our university has a specific mission, and one part of it is unique to DePaul: Vincentian personalism. Simplified, it means that if you can be helpful to one person, you need to deliver the same values and outcomes when helping many people at scale. That gives us a unique value proposition for AI. AI changes economies in small and profound ways, and the challenge is providing human respect at scale. We want AI to stay human as it becomes part of everyday life: understanding and mitigating biases, understanding the risks, and valuing the human experience. We may not be building frontier or foundation models at DePaul, but we are part of the ethical thought leadership conversation. We want students to leave with a deep understanding of AI and of where and when it should be used. The AI Institute brings that work together across disciplines and acts as a focal point.

Sathish:

“So it spans all your disciplines. That is a big task.”

James:

And there are different attitudes. I work mainly with the College of Business, where market realities mean students need practical, hands-on AI experience. Someone in our theater school, a musician, or a writing instructor has a different relationship with it. But even if you are anti-AI, we need to give you hands-on experience, so that when you take a position, you are speaking from a strong foundation.

Sathish:

“Where do other universities stand on the AI adoption journey?”

James:

There is a lot of survey data right now showing a huge gap between universities saying AI is important and saying they are working on it. Most sit in the middle, and I think that is dangerous. Universities are like ocean liners. They are large organizations, and you need everyone moving in the right direction. Where some are failing is internal communication. There is no clear picture of where the institution should be going, and this is an environment where we need to make decisions and move quickly to stay relevant.

Sathish:

“Enrollment is declining every year. How will that affect recruitment, conversion, and retention, and can AI help?”

James:

These are my personal views, not necessarily my institution’s. Many institutions plan for growth, as they always have, and I think that is dangerous. Some should plan for fewer students and work out how to deliver the same services to a smaller incoming class.

I think AI affects the funnel in four areas. The first is recruitment, where there is a chance to lower costs. The old marketing adage says 50 percent of my marketing is not working, but I do not know which 50 percent. Used well, AI can identify what is not working. But that is the smaller part. Conversion is where AI will really change things. Traditionally the university’s job was to convince a prospective student this is the right place for them. Now students use AI to research what they want, how to get it, and where to go before they apply, so the decision is already made. There may be an opportunity to spend less there, because you are no longer convincing, you are making sure you bring the student in well.

The last two are retention and experience. I think AI will probably reduce attrition, because students arrive with a better understanding of the institution and what they want. You could also try to identify at-risk students, but that is very nuanced, and I will come back to it. Experience is where universities need to change. AI is changing economies of scale, so institutions now compete against something that is essentially free. You cannot compete on cost, but you can compete on experience. At DePaul we focus on what we call high-touch moments. Think back to college: there were probably moments when you realized, this is why I am glad to be here. That is what we need to provide.

Sathish:

“Can AI predict which students are likely to enroll, succeed, or drop out?”

James:

Maybe, but there is danger here. AI is an umbrella term for many technologies. Some are predictive, but most of what we discuss today is generative, and most platforms are moving that way. Those systems are black boxes. We cannot yet see how the algorithms produce results, and that is dangerous for predicting student behavior. We might statistically amplify certain biases and flag a student as at risk in a way that is harmful or unethical. If we have models we can fully interrogate, see how decisions are made, and trust the data going in, then yes. But the jury is still out. I do not think we have forensic proof that a student is at risk.

Sathish:

“Can AI improve student engagement inside and outside the classroom, for example as an assistant?”

James:

Absolutely, though it is nuanced. Universities have historically operated with scarce resources: the professor’s time, the physical campus, and knowledge in the form of books. Knowledge is no longer scarce, and online learning removed the campus limit on growth. What remains scarce is the professor’s ability to respond meaningfully. Research says two critical things. First, we learn best with rapid feedback. If you ask a question and hear back hours or days later, the answer is less helpful. Second, for every hour of instruction, a student at their best remembers maybe four or five things, yet most classes run two or three hours and overwhelm students with information. AI can potentially ease that scarcity. My fear is that if AI does much of the professor’s work, the student eventually asks, why do I need the professor? Universities have to work out what makes sense, and no one is an expert yet.

Sathish:

“Will AI replace faculty at some point?”

James:

The people funding generative AI assume it will replace jobs, not just professors but many people, and the people buying these systems see them as a way to reduce personnel costs. Logically that extends to universities. Think about grocery stores: there used to be a human checking your items, then self-checkout, and now stores where the system watches what goes into your cart. Capitalism looks for ways to reduce the human, and that is dangerous for universities, because we want the human experience. Some positions may disappear, but I think universities will hold on to the human experience as much as they can, because it is central to their values.

Sathish:

“Students learn at different speeds. Will AI-powered tools create personalized learning experiences?”

James:

Yes, absolutely. Most universities teach in a way the Prussians developed about 200 years ago to maximize output with scarce resources: 50 people in a room, one professor, two or three hours. We know that is not how learning works best. People learn at different speeds and times of day. In the US we send children to school at seven in the morning when their brains are not ready until around eleven, largely because parents need to get to work.

But there is a disconnect. Personalization works best when the AI is the student’s own tool. It is a rational fear not to want to hand your deepest thoughts to a system someone else owns and operates. When AI becomes a personal device the student fully controls, like Jarvis in science fiction, it becomes most useful. It knows you well enough to say: James, it is 12 o’clock, your project is due tomorrow, and this is when your brain works best.

Sathish:

“How will AI change the future of online and hybrid education?”

James:

Faculty and institutions have a significant fear of cheating in online courses. Fifteen years ago we thought we had solved it with proctoring systems that watch students during exams, and faculty were happy. Now we have agentic AI and real-time deepfakes that look and sound like you. Some professors fear a student can tell an agent: here is my course, do the assignments, and give me a B-plus so it does not look like cheating. Faculty are understandably alarmed.

The flip side is that students now expect ubiquitous, accurate feedback, 24 hours a day, seven days a week, and personalized learning. Online education has traditionally been about efficiency at scale: design once and enroll a thousand students. AI changes that equation into something highly personalized, where each student’s path fits their needs. So there are two paths going in different directions, and the challenge is finding a way to bring them together. There are no easy answers.

Sathish:

“Many universities have launched online programs. What separates the best from the weaker ones?”

James:

The best are truly programmatic. Some online programs are just a collection of courses: an accounting course, a finance course, with no arc from one to the next. The ideal online program is not about individual courses. It is the program. When you watch a movie, you are not watching a set of separate scenes; it has a narrative from beginning to end. The best online programs do the same. What you encounter at the start is referenced meaningfully at the end, and everything integrates naturally. That is the difference between strong and weak.

Sathish:

“What are universities’ biggest concerns in adopting AI: integrity, bias, data privacy?”

James:

The list is long, but it simplifies to this: the speed of change makes universities worry they will make the wrong decision. Universities work on contracts that require investigation, general counsel, and IT review, and often commit them for several years. The fear is locking into a decision that ultimately hurts them. Many also worry there is no unified internal support for those decisions.

One good thing came out of the pandemic. It was horrific, but it acted as a time machine that moved universities into the present. Online had been seen as unacceptable or unworkable, then everyone had to go online, and most institutions still delivered value and graduated students. That lets institutions move faster when they face a clear danger. With the pandemic, we knew the problem and could work out a fix. With AI, many institutions do not know the right approach and lack internal agreement on what to do.

Sathish:

“In the future, will elite universities and newer colleges be on equal footing for students?”

James:

I am cynical here. I think the gap between elites and non-elites will probably widen. Elite institutions have money, and money fixes a lot of problems. When you are scrambling for money, it is much harder to compete. Think of Gartner’s Magic Quadrant, with completeness of vision on one axis and resources on the other. There are ways to compete with fewer resources, but elite universities have both, so all things being equal the gap widens. The other part is the individual. AI gives individuals more opportunity, whether an independent professor or student. I think AI may be more transformative for people from disadvantaged backgrounds than for those from comfortable ones, which is ultimately a good thing. No one is an expert here. It is uncertain territory.

Sathish:

“What should universities start doing today to stay relevant in an AI-driven future?”

James:

Scenario planning. It assumes there are significant uncertainties in the future. Take a concrete one: many universities depend on international students to survive financially. I came to America from the UK as an international student. Right now we do not know if students can easily get visas or whether they will want to come to the US as they have before. AI is another uncertainty, from artificial general intelligence to artificial superintelligence, when computers may be smarter than humans. Universities should map possible futures, decide how they would respond to each, and have a plan in place, so they can move sensibly as the future becomes clearer. They also need to be more nimble. The pandemic pushed universities to be nimble, and we need to be in that mode again.

Sathish:

“What is the future value of a degree? Will skill acquisition change?”

James:

Degrees will be around for a while, because humans change slowly even when technology and the environment change rapidly. Over time there will be change. But 20 or 30 years ago people were already predicting the death of the degree and naming what would replace it, and those replacements have not taken over the market. So I still think degrees will be around.

Sathish:

“What advice would you give higher ed leaders who feel overwhelmed by AI?”

James:

AI is only one of several existential crises keeping senior leadership awake. Feeling overwhelmed comes from not feeling in control of your environment, and meaningful action restores that sense of control. You may not fix the problem, but you can take the first step. When something disruptive is happening in your life, you cannot fix it, but taking one step makes you feel less stressed. That first step could be forming a committee, bringing people together to investigate, or simply experimenting with a tool. As long as you do something, the stress eases.

Sathish:

“You said universities should plan for reductions. Is that more about reducing staff, or serving more students with fewer staff?”

James:

It depends on the institution; there are no universal rules. Over the past 20 years, staff has been cut historically, and most institutions have cut to the point where they cannot cut further. Institutions now realize that faculty numbers are where cuts will likely happen. That is a hard conversation. I hear tenured faculty in the US who once said this would never happen now acknowledge that, if cuts are needed, this is where they will fall. Nobody wants to hear that fewer people will be employed, but for many places it is probably necessary. Leadership often promises 5 percent growth, and that is much harder now. The difficult internal conversation should be: plan for fewer students, and work out how to stay financially sustainable while still delivering the right value.

Sathish:

“What skills should students build for the future, when so much becomes obsolete quickly?”

James:

I will borrow from others. Two weeks ago we held a symposium on AI in Business, and a panel of people who make hiring decisions, from different organizations and levels, all gave the same answer: curiosity. Candidates who show intellectual curiosity get the job. A week later, at one of our biweekly internal AI sessions, a speaker from a hiring company specializing in AI said the same thing. So students should show intellectual curiosity and feed it. One of the best things they can do is use these tools to create something meaningful. With Claude Cowork, for example, you could build an app that does not exist yet, design your own learning path, or research a topic. Be curious, then show you acted on that curiosity.

Sathish:

“What are your closing thoughts on the future of higher education?”

James:

I work in higher education, so I believe there is a future; I would not be here otherwise. In the same way, I am a parent because I have faith in the future. Higher education faces significant threats right now, and it will change. The US has roughly 5,000 universities and colleges, and I think there will be fewer. But higher education will remain because it changes people’s lives in meaningful ways and improves culture and society. Without it, we would live in a far poorer place, and life would not be as much fun.

Sathish:

“Any final comments for our audience?”

James:

For anyone who feels there is too much change: find a way to at least entertain the idea of work-life balance. Get out into nature, talk to someone, put down your device, cook a meal from scratch. Do something slow that has value, make room for it daily or weekly, and talk to people without technology for at least an hour.