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The TechEd Revolution with Arizona State University's Lev Gonick | GSVtv Podcast
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- [00:00]
A
Foreign.
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B
We are here at the ASU GSV Summit 2026 with Enterprise Chief Information Officer, Enterprise CIO at Arizona State University, Lev Gonick.
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A
Welcome to the Bob. Great to be with you.
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B
Great to be with you too. So you make this differentiation between EdTech and TechEd. They sort of where. Where the tech stack lies in terms of is it education first or is it technology for the sake of education? Tell me a little bit about how that distinction works.
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A
Over the last couple years, I've been trying to find language to talk about the moment that we're in with AI. And there are two just instincts that people have. One, it's just incremental. It's more of what we had before. And one is that in fact, this is incredibly disruptive and going to change everything. I happen to be of the latter rather than the former. And so instead of simply talking about it as more ed tech, there is a history for edtech. And I'm old enough to say, Alex, I was there at the beginning of the EdTech revolution. And what we did is we took all of the ways in which our traditional university operated and we slapped on a digital. So we made a digital campus look just like the old analog campus that I, you know, when I was a student, we went to and we learned to automate it and we tried to create, you know, sort of interfaces that were more compelling, but in the end, it was really not about the student. It was about digitizing each of the offices, each of the information systems. And all of that was, and good luck to the student to figure out how to actually navigate that. And from a technology guy's perspective, honestly, Alex, it's incredibly brittle to try to keep all of those pieces together.
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B
Yes.
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A
So what moment are we in? Right now? We're in the AI disruption moment in which we no longer have a. A requirement to continue to think about the applications being the center of the universe. And we're seeing that happen again in the way in which reasoning models work, and again the ways in which the data sources and the vector databases are being developed. And so I said, you know what? This is a different moment. This is a moment which we should find new language to talk about, the tech ed moment in which finally all of our aspirations for using technology to advance student success are now more possible than ever before. Not as an incremental improvement on the application experience, but really about the transformation of really following the student on their journey rather than having the students figure out how to actually navigate us.
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B
That makes a lot of sense. And that sort of steps.
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A
And that is a teched. And that is the teched revolution. I write about it every two weeks. I have a blog, I have all kinds of co contributors. Yeah. And it's touching all parts of the university, from the design of the university, to the curriculum development, to the assessment, to the way in which we do instructional design, to the way we try to do research activity, to hr, to. What does it mean to actually graduate an AI literate.
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B
Yes. Student.
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A
I mean that's, that's the whole moment that we're in. And you know, our language is using teched as a way of saying it's not more of the same.
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B
That makes sense. And ASU is perfectly positioned for that because it's always been at the cutting edge of technology, especially, you know, for decades. And now for this step change, enormous moment.
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A
And it is a step change. Alex, you're exactly right. This, this is. If we don't see this as an opportunity to actually help design that step change, it will happen to us. Yep. And what we did learn over the last 30 years of the EdTech revolution, as in more times than not, it was done to us. Yes. And so this is a moment which is a call to engagement, a call to the best minds in the world of education and the coalition of the technology partners who are out there to fashion something fundamentally different.
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B
100%. And you have all sorts of partnerships in place. ASU has made its own AI tooling that's used all throughout the campus. Give us some examples of some of those enormously powerful initiatives you're using to get to that tech ed future. Right.
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A
So let's just start by dispelling the idea that the old debate that we used to have between buy versus build, irrelevant. It's not, it's a totally false dichotomy. And ASU in our AI journey is absolutely leading with an and statement, an and both statement, rather than an either or statement that is there. So we have, and we'll continue to fashion wherever we can, try to create value out of those that are actually selling technology platforms and tools and want to create application experiences along the way. But at the same time, we've realized that is so early on that we can't wait for the market to mature, to start, as it were, quote, unquote, selling us the stuff we need today. So asu, in the fashion that, you know, well, Alex basically said we're going to actually do something and create a model in which we took a group of folks inside our organization led by a colleague, Elizabeth Riley, who was in our data science team, in our data analytics team. And we said, Elizabeth, listen, this is not a dream you're having. I want you to design an AI acceleration team from across enterprise technology at ASU. And she said can I have two or three people? And I said how? Let's start with 15. And she started pinching herself. But that's how the AI acceleration effort at ASU began. And it wasn't just data scientists and it wasn't just machine learning specialists, it was assessment people, it was the ethicists, it was design UIUX folks. And she built one of the only vertically integrated technology teams we have at asu because we are and have become expert at cross matrix delivery of solutions and software within the university to accelerate the journey that we're on. We created with her leadership and guidance and engagement with the faculty community and engaging our staff community, a platform technology which we call Create AI and a builder kit, a series of tools which we call Create AI Builder that are out there and in, in a way that is not just uniquely about asu, but you would expect this from asu. We focused on Create AI as really an opportunity for the faculty and staff to start with and now more and more of our students, not as passive spectators, not as people who are buying licenses, but actually as co designers and creators. So we launched this really Create AI platform for our staff and our faculty in August of this past year, which is we have 20 more than now, 20,000 creators, creators who see this as an opportunity for them to reinvent their part of the university to help students succeed, but also to make sure the university is running and there are 8,000 AI experiences that are now in a marketplace where people are sharing with each other. What a fantastic opportunity to show the unlocking of value by letting us build the secure, private, regulatorily compliant ethical ways of measuring bias within the models that we're using. Let us build that infrastructure, let us build the toolkit that folks can begin to use. And if for most of the university this is like a no code, low code environment, and that's why this amazing marketplace of ideas translated into actually a whole lot more than whiteboarding or scribbling on the back of the people are building with drag and drop and radio buttons, data sets, workflows, opportunities for getting students to tell us where their pain points are and students are then helping us build solutions for those pain points. That's the unlock of value at ASU and Create AI.
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B
I want to double click on the data sets piece because I think this is one of the unlocks that's really interesting about AI Create is that you've tapped into. There's so much data inside a university ecosystem. Much of it is regulated in lots of different ways, of course, you know, but the underlying data structures that you've created under the Create AI unlocks so much possibility. It understands the course catalog, it understands the campus. I mean, there's just so much in there.
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A
And really, again, we're just at the beginning of this. You know, we have 25,000 courses at ASU. They're now actually in vector, two different vector databases, which actually allows for all kinds of interesting exploration and repurposing. We have a project that's underway called the Atomizer, which is the idea of you take these 25,000 courses and again, with the right kind of conversations with the faculty and the like, we look to actually decompose those courses from whole into parts, all the way down to atoms, and then we reassemble them as the market or the student actually wants to reassemble them. So that's one of the viable pieces. Just everything from like, how do you even explore? Like what, what a degree? What kind of degrees might I explore? Well, I mean, we're now taking that catalog and we've actually created a gamification experience which is not about like again, sort of the chat bot. You know, I got an A in physics in high school, so what can I do with it in my. But really literally a gaming where you get to interface. And again, using the Create AI platform as a platform in which our colleagues at ed+the folks who deliver ASU online have realized there's a real need to have a conversation, especially with online learners. But I would say with all learners to understand like what kind of degree we call Degree Me is the game. It's a degree Me game. And at the chance then from the degree Me gain to immediately begin to then assemble the classes to begin your first online experience, which we think has a huge amount of value to that opportunity to again, the whole process of how we do instructional design. You know, at a university like ASU, we have like over 300 instructional designers that are in play. The knowledge that they have and the kits that they use, the playbooks that they have, are now absolutely treasure troves of digital insights that can be remixed in ways that allow us to take the process of developing case studies for learners, whether they're online or at the university in the immersion of the campus experience and move from hundreds of hours of instructional design in case method to to using AI Avatars that can participate with and have a relationship with students who are trying to learn how to do interviews, or medical students who are trying to do opportunities for typical patient interviews, or law students trying to practice a case, or students want to do career count, like all of that data on how to. So we've moved that and that's now in an agentic workflow. What used to take hundreds of hours and teams of people still has an instructional designer oversight, but it's happening in tens of hours. Yeah.
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B
And you can make much more and it's incredibly compelling. Yeah. And you can do more because it is so.
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And it can be replicated and it can be again remixed in ways that again, working with agents, the agents who can create case method, agents that can create narrative, agents that can create rubrics, context evaluation, ambient listening and giving feedback to students like that is the great
- [11:10]
B
unlock of the value 100%. So you are at an organization that's very tech forward, very pioneering. I'm sure you talk to lots of other CIOs that maybe don't have environments like that and they want to do this kind of amazing work, but they need a lot of buy in. There's a lot of faculty committees as presidents. I'm curious what advice you give them if people are trying to sort of level up their tech game.
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A
Let's just be really clear, like engaging with your faculty is absolutely not only a good thing to do, it's a must thing that you have to do. And I think we've done it pretty good in partnership with the university's provost office and their collection of communities of practice that they very much have led and we've tried to support along the way, including professional development for our faculty. You know, we've had some 3,000 plus faculty participate in the professional development around the AI journey, which includes the instructional experience for them as teachers along the way. The feedback that I give to my colleagues and my peers that are out there is that it's enormously important to have a bias to action.
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B
Yeah.
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A
At asu, we don't actually have a strategic plan and we don't have an AI policy framework that took two or three years to develop. President Crow provides us with a trifold every year of the goals of the institution. And they shift every year for the last 20. Now six years in that journey.
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B
Wow.
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So that piece there, it's hugely. Let me take that back. Every year for the last 24 years. And the goals shift every. Every year along that journey. And the way we dealt, the way we execute on it is by design build. That's the design aspiration. Now we go build it and we iterate in the way that you would sort of think about it as the way software gets developed. Yes, yes. And so that bias to action is hugely important. A growth mindset is another piece that I share with the CIO community because too many of us are schooled in the idea that the only way to survive is to become the department of no. And enterprise technology at ASU is not about the traditional slogging of enterprise. It's actually about being enterprising. It's actually the unlock of entrepreneurship to actually help and to be of service. And I think those two central themes about. Basically, if you want to find a way to predict the future, Alan Kay said you have to find the best way to do is to invent it. Right. My view is if you want to predict an event, you better start now.
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You better. You have to go.
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That's the message.
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B
You have to go build. Fantastic. We got to have a longer conversation, but this is fantastic. This is Lev Gonick. He is the CIO Enterprise CIO of ASU at the ASU GSB Summit 2026. Thanks for joining us. Thanks, Alex. Thanks.
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A
It.