The Human Side of AI: Leading with Purpose in Higher Education

Sathish:

“Welcome to today’s podcast. I’m here with Thom Chesney, who has more than 30 years of experience in higher education. We’ll talk about the human side of AI and leading with purpose. Thanks for joining.”

Thom:

My pleasure, Sathish. One small correction: you said Southwestern University. That is where my daughter goes to school in Texas. I am at Southwestern College in New Mexico. She would want me to tell you that.

Sathish:

“You have led multiple institutions. What has shaped your leadership philosophy over the years?”

Thom:

So much of it is shaped before we think of ourselves as leaders: the situations we were in growing up and the leaders we got to watch. What I saw, before I had a name for it, was servant leadership: putting the people you work with ahead of you or alongside you and working together as a team. I was an athlete from youth through intercollegiate athletics, and I had coaches who moved us because we believed them. In distance running, they ran alongside us. They were willing to do the same work we were.

When I moved into leadership in higher education, that experience weighed heavily on me: encouraging, nurturing, mentoring, and working alongside people to reach the outcomes they want. Embedded in it is a form of altruism. Things are much bigger than you, and the person in front of you is the most important person in the room, whatever your title. I have been president at three very different institutions: a community college, a small Catholic liberal arts university, and now a graduate-only institution. In all of them, being true to yourself and serving others first has been a good starting approach.

Sathish:

“You have seen higher education for 30 years. What has changed, including how people value education?”

Thom:

I have been on a college campus for 40-some consecutive years, starting as a student in 1984. In the 1980s there was an expectation that everyone would pursue some kind of education after high school, from apprenticeships and certificates to terminal and professional degrees. Since then the perceived value of higher education has ebbed and flowed, and I have worked full time in the field since finishing graduate school in 1996. Right now there is a lot of turmoil and divisiveness about its value. At a recent higher education conference, some people at my lunch table said on-the-job training and informal credentials should be enough. Others argued that a well-rounded liberal arts degree or focused study of two years or more is still essential.

The other big shift is delivery. When I first registered for classes in 1984, it was with punch cards, before online or phone registration existed. Now we have online education, which has shifted dramatically since the pandemic: synchronous, asynchronous, learning objects, and now AI. I remember the analog world of higher education, and I am now fully immersed in, learning from, and leading in the digital one.

Sathish:

“How do today’s students make decisions about education?”

Thom:

No two make decisions the same way, and some of it is generational. We have at least four generations in our workplace and among our students, even as a graduate institution. Students focus on the program and its content, how it will be delivered, and more than ever, cost, with the expectation of full transparency. Then the career piece: what does it get me? I see that across community colleges and four-year institutions too. What is in it for me, will the schedule work for me, and what will it cost?

That means institutions have to listen to student voices. Higher education used to proclaim, and some still do, this is how many credits you take, this is when and how courses are offered. Now students want flexibility. Can I attend face to face but take some classes around my work schedule, because I am supporting a family here or overseas? We try to capture information from prospective students who looked at us and chose not to enroll. Was it cost, delivery, or not seeing a clear path to their career? That is a real shift from when I went to college.

Sathish:

“What is your personal perspective on AI in higher education: risk or opportunity?”

Thom:

It is all of that. I think we are in chapter one, or the preface, of the book that will be written about AI and higher education. I am a stereotypical Gen X member. I grew up without a computer and have seen many evolutions in computing. My generation tends toward curiosity, experimentation, and individuality, so I am in full curiosity mode with AI. Even before we called it AI, I wanted to try GPS instead of balancing a map on my steering wheel, and then it started adjusting for traffic.

Many of our students pursue mental and behavioral health degrees, so the question I hear most is: are you worried AI counselors or AI art therapists will replace your graduates? I think about it, but I am not particularly worried, because of how we approach it. I reframe the question: will AI replace the therapist, or amplify their work? Can AI amplify relational work rather than simulate it? Our students and licensed clinicians are finding that AI can support the transcription and note-taking required for insurance providers, Medicare, and Medicaid. If a therapist is not trying to squeeze paperwork into their schedule, and only needs to review AI-generated notes, they can spend more time providing therapy and building the relationship that leads to good mental health outcomes. So I look for where AI supports and amplifies relational work rather than substitutes for it.

Sathish:

“So you see a big opportunity, with AI handling the back-end work so people can focus on relationships.”

Thom:

Yes. Another way to put it: AI helps us prepare for the human interactions that connect us. I am a digital pack rat. Over the years as a president working in advancement and fundraising, I have saved hundreds of letters, appeals, and thank-you notes I have written. In the last year, for the first time, I have been able to give that body of my own work to an AI tool and ask it to find common themes and draft early versions of stewardship letters and thank-you notes. I then revise and use them. I feel ethically comfortable with that. I am not asking it to replace me or make me more artificial. If it helps me prepare so I can connect better, that is worth investing my time in.

Sathish:

“Is there a risk for someone early in their career who adopts AI immediately, without the experience to judge whether its output is right?”

Thom:

I think there really is, and I love the question. What I described builds on a 40-year career of doing the work myself. Someone new, trying to be seen as effective, could use AI as a shortcut to show they get more done than coworkers. The risk is more than what we call AI slop: sloppy, incomplete, or poorly informed writing, communications, art, or any work product. So we need to embed AI in the learning process across the whole spectrum, from early childhood through graduate education. When people are introduced to these tools, does that come with guidance on what to consider? For years we have taught students to cite and attribute sources and to validate that they are primary or scientifically sound. We need to apply that same thinking to AI, so people do not simply adopt it without considering the ethics, morality, and legality.

Sathish:

“Are students getting overwhelmed by so much information and so many tools?”

Thom:

In some settings, yes. It is easy to be overwhelmed by the proliferation of tools. I remember the explosion of apps, when every higher education institution built its own app, and over time most people went back to wanting a good website that works on any screen. Today there are so many choices, free and subscription, that it is hard to know how to choose. My advice: do not get overwhelmed by the noise. Be curious, pick one or two tools, and see what works for you. As you share more about yourself so the tool gets to know you, how does that feel? Do not worry that someone next to you is using a different one. It is like sports: narrow your focus and get good at one or two things. Along the way, you may come to trust your own critical thinking and judgment more. That relationship is about amplifying rather than being replaced, and it eases the overwhelm.

Sathish:

“What does leading with purpose mean in an AI-driven world?”

Thom:

A key piece is paying attention and being engaged yourself, not leaving the work to others. If I sit with my leadership team and faculty and share what I am seeing and learning, that builds a first level of trust. The president is paying attention to this; it matters to him; I want to engage too. The reciprocal side is hearing from others. What are faculty experiencing in the classroom? I ask my provost whether there is more concern about students submitting work that is not their own or using AI outside the scope of our student agreements. So it is twofold: authentic engagement and learning, and getting the full picture of how AI is being used across the college, and what that means for our policy, practice, and processes.

Sathish:

“Are universities preparing students well for this new reality, or still following the old approach?”

Thom:

It is a very mixed answer. Some institutions have adopted AI policies quickly and thoughtfully and are bringing AI into online and face-to-face learning to test what works. Some are creating AI-focused credentials and certifications. My undergraduate degree is in Spanish, and I expect language programs, English included, will soon teach appropriate use of AI in writing, speaking, and translation. But based on recent regional and national conferences, it is a mixed bag. It is complicated by changes from the US Department of Education. With a changing regulatory environment and a wildly evolving AI landscape at the same time, it is hard to do both with the staff, faculty, and resources you have.

Sathish:

“What kind of students and leaders will succeed in the next five to ten years?”

Thom:

Those who remain lifelong learners in the widest sense. I spoke with one of our graduates who has practiced counseling for more than 20 years and asked whether he worried about clients leaving for cheaper AI counseling. He said no, because his work is so relational, and he has evolved. He uses an AI tool to take the notes he needs for insurance processing. He has stayed open and kept growing beyond the counseling profession itself, adopting the supporting tools that keep him relevant. You do not want to adopt everything, but if you adopt nothing and never play in the AI sandbox, you may be left behind or forced into an unplanned career change. It is like those who shunned Microsoft Office and kept writing by hand; opportunities dropped when everyone needed word processing skills. It is manageable. Narrow in, experiment, let some things go, try others. People who stay curious will be more adaptable.

Sathish:

“On enrollment, will students still browse college websites, or will they turn to tools like ChatGPT and Claude to find the right program?”

Thom:

We are already seeing it. My institution is doing its first full website redesign in about a dozen years, and we have cut about 75 percent of our prior pages because we are optimizing for both search engines and AI. Every time I search, an AI summary appears at the top with links to relevant pages. So the new site is designed so Claude or any AI tool can pick up our content and say, here is what we found from Southwestern College. When someone clicks through, they expect a decision point. We will not make them click through several levels. We give as much as we can right there, then let visitors choose how to connect: text, email, a campus or virtual visit, or a phone call. Our students range from 26 to 66, so they need those choices. It has to be good, clear, and hit the decision points they expect.

Sathish:

“When people reach your site, will they read, or just want a direct answer to their question?”

Thom:

Both, and we are planning for both. Southwestern College has been relational since it was founded about 50 years ago. Many people want to dig in and understand how consciousness-centered, experiential graduate learning works, and we have staff ready for those individual conversations. But not everyone wants that, so we are asking how to build a relationship in a different space that intrigues people enough to learn more about the curriculum and the career at the end of it.

There is also a paradox. Some people use AI to find what is real. Our education is experiential and relational. Someone can use AI to search for an experiential, relational graduate program in counseling and find Southwestern, choosing a tool while hoping it does not replace the teaching and experience at that college. Using AI to find what it cannot provide seems like a paradox, but it is a powerful tool.

Sathish:

“Can AI help track student progress and flag who may drop out? Are you using such tools?”

Thom:

It is already available and being adopted. It is on the agenda at ASU+GSV in San Diego next week, and there was a lot of discussion about it at SXSW EDU. The idea is to analyze student data and trigger alerts when someone falls behind, prompting outreach from a course navigator, mentor, or advisor. Much of it is still in development, and large, well-resourced online institutions got there sooner and are sharing what they learned. One lesson is that it is imperfect, just as AI is imperfect at reading radiology scans. But if it gets pretty good, what is the harm in someone reaching out to a student who has not been showing up, logging in, or doing the reading? If students know from the start that engagement is tracked, they should not be surprised by a check-in. Then there is a real conversation: my car broke down, I had a child, I lost my job. Someone is engaging to help them succeed. So yes, and institutions will need to articulate how and why they use these tools so they stay authentic to a high-touch, human brand.

Sathish:

“What risks and compliance issues should universities watch for when adopting AI?”

Thom:

The most obvious is whether institutions are clear about how they use student data, learning tools, and curriculum, so people trust the information is used appropriately and legally. If a college adopts a tool for grading multiple-choice tests or improving follow-up, are students informed? Is there an institutional review process, with checks and balances so there are no surprises? A student should never first learn that AI is being used to check their work when a professor says it appears AI wrote 55 percent of their paper.

Then there are the common concerns. Are we selling data? Do third parties have access? What about the information we provide to accrediting bodies and state and federal education departments? If annual reports on enrollment and demographics are AI-driven, how do we validate them? Institutions need to know every tool they use and what it means legally and for communication with employees, students, the public, and agencies. That may be a gray area right now, because individual decisions are being made. Who should know when those adoptions happen is a critical part of the risk.

Sathish:

“What do universities still overcomplicate, following rigid processes that make things harder for everyone?”

Thom:

Routine processes. Course scheduling is one. Institutions have the data to be student-centered about which courses are needed and in what sequence. AI could model scenarios: we need a certain number of sections of a course, and based on students’ modality preferences, one should be online and asynchronous and another on evenings or weekends for students who work during the day. At many institutions that is still very manual. Professional sports leagues run multiple scenarios to schedule 20 Premier League teams around locations, travel, and conflicts. Higher education could do the same with student progression data and run scenarios in minutes that take someone hours by hand.

Financial aid is the other. We have improved payments, but many people would celebrate a smoother process for gathering information and packaging grants and loans faster at the institutional level, so students have more time to decide among institutions. It is still very manual. None of this excludes human participation or shared governance. It is simply efficiency. We could do a whole separate podcast on the things we still do manually.

Sathish:

“We’re close to the end. What one piece of advice would you give leaders navigating this change?”

Thom:

Stay curious and open: read, explore, and experiment widely, but do not get overwhelmed. Use a tool to help you narrow things down. I chose Copilot, since my institution is a Microsoft institution, and I am seeing how much it learns about me and how I can test and challenge it. I also use it to summarize four or five articles or announcements about AI and identify what matters for my institution. Pay attention in a manageable way, so you are not surprised. People will come to you expecting you to know something.

The other part is to engage. Talk with colleagues at every level: the business office, faculty, operations, the grounds crew. Ask how they are using AI. You might be surprised. Our landscaping team uses AI with weather forecasts to decide when to water and when to expect water collection. We are in Santa Fe, after all. So be curious, and engage others.

Sathish:

“Thanks, Thom. I hope we can do another episode on more AI use cases in higher education.”

Thom:

My pleasure. I encourage listeners to connect with me directly if they want to follow up. Whether we meet again in six months or a year, we will have a lot more to talk about, because it has probably changed in the last hour we have spent together.