AI Adoption Across the Institution: A Debrief of the EDUCAUSE Summit

Jenay Robert: Hello, everybody. Welcome to EDUCAUSE Shop Talk. I'm your host Jenay Robert, senior researcher at EDUCAUSE. I am joined by three phenomenal colleagues today to talk to you about something that we all enjoyed earlier this week together, the EDUCAUSE Summit AI adoption across the institution, governance practice and change strategies in Minneapolis, Minnesota. We've already started off the pod strong with some really fun technology issues, so that's always a great way to get started. But yeah, I'm going to stop babbling and let my colleagues introduce themselves and then we will get started letting you all know what we did this week. Kathe, you want to start us off?

Kathe Pelletier: Sure. Hi, everyone. I'm Kathe Pelletier and I'm the senior director for community programs here at EDUCAUSE. And my role with the summit was initially to be one of a small team who planned this somewhat new type of event for EDUCAUSE. And then I had the honor of co-MCing with a colleague, and that was really fun to be able to introduce the speakers and have a little repartee from the stage. Well, I'm going to save this for when I actually am talking about the thing, not just introducing myself. I'm going to pass it to Jamie to say hello.

Jamie Sundvall: Hi. Thank you Kathy. I'm Dr. Jamie Sundvall and I had the honor of giving the keynote for EDUCAUSE's opening summit. I also partnered with the CIO, Joe Sabado from UC-Santa Barbara, and we talked a little bit about policy assessment, so I was involved in a couple different aspects of the summit.

Jenay Robert: Let's go to Carie Ann.

Carie Anne Potenza: Excellent, good day. I'm Carie Anne Potenza. I'm Senior Director of Strategy and planning services with Ellucian. And so at the summit I was able to talk about the layers of governance that AI may need—everything from data governance to AI governance, and so I was lucky enough to not have to travel. My home is Minneapolis, Minnesota, so I was very happy to actually have a conference in my hometown.

Jenay Robert: And we also want to shout out to Ellucian being one of our mission partners at EDUCAUSE. So just thank you for your continued support and thought partnership and leadership. And as you said, your talk at the summit around data governance and these topics was really exciting and interesting, and that's why we really wanted you to share that with all of our colleagues today on the pod. And similarly, Jamie, I think your insights coming from the practice lens that you had and giving everyone that thousand foot bird's eye view at the start and then drilling down in with some of those deeper topics with Joe was really insightful. So I just want to thank you both for contributing to the event and Kathy as well, of course, our incredible MC. So to get things started, maybe we could go around and talk about some of our big takeaways from the event or maybe something that's specifically stuck in your head as a little nugget that you took away. Anything that rises to the top of your mind.

Jamie Sundvall: There's so many things like where to start. I'll jump in. So there were so many great topics that we talked about, and it was interesting to see how through discussion with colleagues in between different talks, people are generally struggling with a lot of the same things. How do we get out of silos and how do we get appropriate governance in place and how is it specific but not too broad, and how do we work through some of the unknowns that are coming up? And then we talked a lot about different aspects of AI that are out there and how governance needs to be structured around things aside from ChatGPT, because we hear so much about generative AI and I found that really fascinating. I think one of the most helpful things that I found in talking to colleagues from all over the country was looking at how governance is owned and who is responsible for governance because I found at the summit there were so many different people managing how policies were overseen, and some of that was being done through technologists. Some people, and I didn't say this at the beginning, I'm the assistant provost of artificial intelligence at Touro University Systems and we have a provost level office managing AI. But it was interesting to see how so many people had technologists managing it, the IT department, managing it, the provost office, managing it, and thinking about how do we best govern and who owns these policies because so many people were sharing that they have awesome evidence-based practices that are following really good structures and frameworks in place, but they're not formally documented and just discussing how do we get good governance structure in place. And so I found that really insightful to thinking about even our own process of making sure that things are effectively in place and not siloed in a way that causes fragmentation so students and faculty and staff can't use it, and also that we can support the trajectory and progression with AI effectively in a positive way. So those are some things that I was grappling with and taking away.

Carie Ann Potenza: I'll say I completely agree with you, Jamie, and one of the things that I love particularly that you brought to the table was you can do this. I think so many institutions were there and they were seeing you and Hans from UF like, "Oh my gosh, I can't go out and hire a hundred faculty," but then there's Babson and University of Notre Dame and all the art of what's possible, and no two schools will do it the same. And so adjust it for how you're going to do it and what works for your institution and how quickly you can speed to, I think speed was a really interesting component. I think people were like, well, we do governance and then we put it on the shelf and we meet about every quarter or semester and they're like, oh, we probably should talk more about this.

So, I think that that's what I really liked about the workshops or the conference was that you had everyone, or to your point that we had some technologists in the room, we had some academic leadership in the room and they were all coming at it like, okay, yes, we need to do this, but how are we going to do it? And then I think there was a great span of all the different ways that it could be done and how some institutions are doing it just for a year so far, some haven't started at all. Some have been doing it for five years. So it was that really good perspective that everyone can do this, and collaboration would be key across all your peer institutions sort of thing. So I think that was what I really enjoyed.

Kathe Pelletier: What both of you're pointing to. I'm going to talk a little bit about the structural aspect of the event, which I think hopefully was just the right amount of little tastes of quickie, talks from various people across the U.S. doing AI in different ways and thinking about AI governance and policy from different perspectives, but then really focusing on the discussion at the tables with participants or among participants. And after a while I started joking as MC, my favorite part of this job is having to interrupt everyone because there was just so much energy around talking to each other and sharing the sometimes really specific elements of we have this committee and this is the person who leads it, and then we invite these stakeholders or we meet every week or every month. And getting really down to that nitty gritty, I think helped to bring some concreteness to the art of the possible that it wasn't just this philosophical energy about like, oh yeah, we can do this, woo-hoo rah rah, but actually taking away some specific plans and connections, human connections that you can call once you're back on campus and say, Hey, Brandon, or hey Jamie, or Hey Carie Ann, I need help with this. Do you have any thoughts? Or what are you doing? Or what's working for you? So that was a really big takeaway for me in part.

And I just also want to echo the sense that even though I do think that there was a range of maturity levels in adoption of AI among the participants, but there was just so much commonality that really resonated, and that I think is just such an important reminder. Even when we were inviting speakers, many of the folks who ended up being on stage were initially saying, oh, no, no, I'm not an expert. We're just figuring it out. We're just getting going. I don't want to pretend like, and of course you don't know everything yet because we're all still learning. And I don't remember the Latin phrase of Michelangelo who said that Tim Creasey included in both of his presentations of Still Learning that Michelangelo at age 87 finishing, I think it was the Sistine Chapel would say, "And yet I still learn." And so I think that just was such an important mantra for us all to remember.

Jenay Robert: Yeah, I think you all touched on really one of the big reasons that we created this event, and Kathe was definitely part of this planning too and can speak to this, but this idea that AI integration or adoption is particularly challenging because it's multifaceted, and it requires collaboration across the institution, and it requires everyone to be on the same page about strategic goals and all of these things. And so we purposely created this event that would span all of these topics and really encourage people to bring participants from various areas of their institution. We had a lot of teams there, a lot of people that were two, three people from a school and in different areas of the school really trying to think about how we bridge these silos. And I think you all touched on that really nicely.

My question for all of you is if that was a big takeaway for all of us, and I think for many of our attendees as well, this kind of reifying the importance of working across silos when it comes to AI. How can someone listening to this pod or watching, how can they take that nugget and apply it at their own institution? Maybe they didn't go to the summit, but they understand the need to work across those silos. What advice do you have for people at institutions trying to do that?

Jamie Sundvall: That's a great question. I think going back to what Kathe was saying, I think EDUCAUSE does such a great job of creating this vibe in this culture because in the room the entire time, like Kathy said, the interruption of the conversations, there was so much going on and one of the unique pieces is that people were so hungry and they were wanting to connect and understand what was happening. And I would say that if you couldn't come to this event and you're thinking, where can I get started? First of all, thinking about what groups of people and organizations can provide you with the education that you can get ongoing, because as we talked about at the summit, AI is not something that you put a policy or governance structure in place and stick on a shelf. It's constantly evolving and it requires us to constantly pivot and be aware so that we're staying relevant for all of the professions and disciplines for our students and graduates.

And we're making sure that our faculty and our staff are staying fluent with the AI changes. And one of the big things that you can do at your institution is creating committees and an opportunity for people from all different divisions and departments to come together and have conversation. And even if you are in the stage where you don't have a particular AI structure and governance model, but you're thinking, how can we come together and see what different aspects of the organization are doing? The best place to start is having those conversations so that you can identify what are the challenges, what are the pros and cons across the institution, because that gives you an opportunity to then start advocating and thinking, what is our next step as it's informed by your intentional pursuit of education.

Carie Ann Potenza: Totally agree. You have to have multiple people at the table. I think it's something to be said that EDUCAUSE invited, Prosci there to talk about change management because I think that's going to be a huge factor is to who you involve at your campuses. You're going to have your resistors and you're going to have kind of your grassroots behind the scenes like Phil talked about at Babson, the students went out and did stuff on their own. But I think it's really important, as Jamie just mentioned, is to talk across the organization and maybe find those pockets of things that are happening because they're happening, whether it's surfacing to a leadership or not. And so talking to faculty, talking to the IT teams, talking to student services, one of the things from the Ellucian study that we did last year, we're recognizing that right operations might be a little slow just because the sensitivity of the data that is, we not sure how to use AI in those areas. So there's plenty of other areas to really embrace AI, right? Melissa from Instructure was there, right? Start with your LMS, like helping identify learning opportunities of measures of using AI in the classroom through your learning management system. But I agree with Jamie, right, getting everyone at least talking about it is a great start.

Kathe Pelletier: And I will probably put you on the spot in just a bit, Carie Ann, because one of your presentations, actually both of your presentations did such a great job of showing how important it was and how possible it is to develop AI governance and data governance structures that are suited to your institutional mission, vision, culture, size, etc, that there's not a one-size-fits-all approach. And so really anchoring yourself in who you are as an institution first and thinking about students, thinking about learning, thinking about student outcomes after graduation and where they want you to go as you're crafting your approach to AI adoption is so critical. The other thing too that I would advise folks who didn't get to attend the summit if they're not already, just another kind of key mantra that came out that Dan Day actually from AWS mentioned a couple of times is think big, but start small so you don't have to eat the whole elephant all at once. So just taking action and moving one foot forward is a start. And so keep moving one foot and the next foot and the next foot, and don't get so overwhelmed by the scary big swirling thing that is AI right now.

Carie Ann Potenza: Totally. And that really addresses two things that I think we didn't directly address, but was definitely as educators and learners in the room were surfaced. So one is don't go big with your data, keep your data small and focused. Jan did a great job of talking about that, and that also speaks to the climate issue that we didn't address directly at the conference, but is obviously top of mind for everyone, and particularly the vendors that they're working with on if you're using all this data, all that power has to get is going to impact the climate. So then starting small, to your point, Kathe, of really focusing on what data is necessary, what data is required, and using kind of small incremental opportunities of testing things out. And that also kind of lowers your risk as an institution.

Kathe Pelletier: Yeah, and that was another theme or thread that I was hearing just kind of in the conversations at the tables that I think the data management, data structuring, data organization, and governance is probably where many institutions are struggling, if you will. And so I really appreciated both. I don't want to just repeat what you just said Carie Ann, but I appreciate it, what you said is spot on. The idea that looking at data as your product at the institution and really thinking of it as foundational to any leaps that you might want to take with AI, and it's not sexy, it's not exciting, but that work is just so critical. And also just for everyone to hear that institutions across everywhere are, that's hard. A lot of folks are still at the starting point there.

Carie Ann Potenza: And right, to your point, Kathe, that the data is a product, but also the data is the students. So bringing the students to the table and having conversations with the students about how they want their data used, when they want it used, what they want it used for. One of the models that I talked about is having a student data rights council as part of your governance. They need to be at the table because most of this data that an institution wants to use is their data, is the student's data. So totally.

Jenay Robert: I'm so glad you brought that up. I think that was another one of the big key takeaways for a lot of people was about the absence of students in a lot of the decisions that we're making right now. And we heard from several institutions that are being really intentional about including students in the process in ways such as what you mentioned, having some advisory council or something like that. And that was a great takeaway for me too. It made me think a lot about how we can platform that idea more and help institutions. I think it's a really challenging issue with a lot of policy, not just AI policy, but a lot of things to really meaningfully include the students in those processes. And they don't feel like we're doing things to them. We're doing things with them. So any other major takeaways or perhaps common challenges that rose that were particularly interesting things that maybe our listeners, I think especially for me, I oftentimes, when I am at one of these AI-based events, I talk about our research data at EDUCAUSE, our Landscape Study that we've done in 2024 and again in 2025. And one of the consistent findings there was that we all feel quite optimistic about a lot of things and we all feel quite concerned about a lot of challenges.

What do you think are some of those other really sticky challenges that maybe people need to be prioritizing right now? Or we feel like our attention is pulled in all directions? Are there some things that rise to the top for you?

Kathe Pelletier: I want to first underscore what you just said and apply it to the vibe of the conversations too, because we invited folks to speak who are maybe ahead of the curve or doing really innovative things that we wanted to showcase. And of course we got a lot of our attendees got to register wherever they were on the maturity scale of AI, and yet it was such a nuanced balanced conversation. Even the presentations included both this amazing optimism and excitement about the potential for AI, but also, hey, here's a risk. Hey, let's make sure we pay attention to this. Hey, let's make sure we bring student voices in and think about ethics and think about the environment and think about all of these factors that if we're not paying attention to, we really could go sideways. So that wasn't a surprise necessarily, but I think just how balanced it was stood out to me.

Jamie Sundvall: I think a couple of things that tie into each other. One emphasis was understanding mobilization and resistance within an organization, which is where the change management theme was really helpful in thinking about, like Jenay said, a lot of us are very excited about the work we're doing and also stay up late at night thinking about all of the risks and concerns and challenges for our organizations because there's a lot of scary things that come with that, especially the speed that it's moving. And we seem like there was a common theme where we talked a lot about how do we mobilize people through the resistance or the fear and looking at how we can provide support and ongoing not only governance and data, but the operational side, which is more of what I speak to in how we can better understand the social and cultural aspects of the faculty and the people on the ground that were asking to join us in making the shift. And so that their perspectives and values can be taken into account. And when we're doing this work around governance and data management, how can we take the values of the institution and the values of the people that work at the institution so that we can make sure we are supporting moving through that resistance and then providing informative training even if we're not potentially bringing on technologies that we're training on, but bringing training and support and basic understanding to, as Kathe said, meet all the different maturity levels because that happens in our institutions as well. And I found those aspects of understanding the social and cultural pieces specific to the people we are working with and marrying that with the educational opportunities to develop that faculty and staff fluency and literacy, because how else are we going to do that for our students? And so those were things that were also in my mind,

Jenay Robert: Carie Ann, and I want you to weigh in on this, but before I hand it over to you before I forget, I want to mention that Prosci piece is something that we do have resources for at EDUCAUSE, and so we'll link those in the show notes. There's change management training, that's an EDUCAUSE Prosci collaboration. So we'll be sure to link that in the show notes. For anyone listening who says, "Yes, I identify with this, change management is one of my biggest challenges." And we have things to help you along those lines. So yeah, Carie Ann, sorry about that.

Carie Ann Potenza: And so right to that point, the awareness and the alignment, like Jamie just mentioned, making sure that you start with what is it that as an institution you want to achieve with AI? It should not be outside your strategic plan or your priorities as who you are as an institution. It should really be woven through. Similar to change management, I think one of the things that I would be excited about having this workshop next year, I think there's really a need to figure out how we measure success depending upon who you are as an institution, what your goals are with AI, coming back to those outcomes of what you're going to do with AI, how do you measure success? Because the ask is going to be more and more. I was talking to a lot of institutions where they're like, well, we have to pay for whether it's ChatGPT or things like that.

And they're like, how do I justify the expense with what efficiencies are we getting out of it? What success are we getting out of it? So I think one of the things that I think, Jenay, your original question is what are some of those challenges? I think those are going to be the challenges over the next year is as institutions implement a level of data governance, AI governance, trying to get those people at the table to talk about AI, how they're using AI both in the classroom, in the administrative tasks, and then from right, a cybersecurity and an ethics and a bias, like Kathy mentioned earlier, how are you going to measure success as an institution that you know it's working for your students, you know it's working for your faculty, you know it's working for your students. So I think as we move forward, thinking with that end in mind, how are we going to measure those success points?

Kathe Pelletier: I love that. Yeah. I think the only other thing I would add is that we did a quickie fun survey at the end of the day on the second day, and one of the questions was, who was not in the room with you that you wished were here? And the most common response was your president. And so I think that really speaks, and of course we know, and I think Tim brought this up in his research, that the most critical, you're more likely to be successful with an initiative if you have an engaged champion who understands what you're doing, who is driving it, who is actively supporting it. And so that work, I think is really important to make sure that your institutional leaders are a part of it and have the literacy that they need and order to really drive this and incorporate that into strategy and just the fabric of how you're doing work at your institution.