Campus Technology Insider Podcast April 2024
Rhea Kelly 24:12
Have there been any early lessons learned so far? Particularly on the technology side, in terms of managing a project like this, or even just specific to the technology itself?
Lev Gonick 24:25
Well, yeah, I mean, here's, here's the one that I, I've spoken a lot to my peers across the country, actually and around the world, is you, we have two choices. We can try to graft on to our existing data teams, our existing whatever teams, our UI/UX, our educational technology teams, you can try to get two or three people who know something about AI and you kind of say good luck. And I think that that's what most universities are going to do, to be honest with you. Or, what we've actually learned and something to share, is that we've actually just created this dedicated AI Acceleration team. And of course, it takes a university perhaps of our size to establish a team of nearly 20 of these professionals to work on it. But I do think that the only way to accelerate through this work is to own more of it as the university, and certainly for our large schools, and those who are going to try to differentiate their offerings in the AI era, dedicated teams are going to be hugely important. And then, again, second lesson learned is immediately, try as quickly as possible to hitch your wagon to the most innovative faculty groups that are there. So for example, next week we will be announcing that ASU will be issuing what is the first degree in the country for AI and entrepreneurship, in our, in our management school at the W.P. Carey management school, School of Business. And so that, that, that is, that then allows us to actually keep that ecosystem and pipeline of development, just not focused in on playfulness, experimenting, but also now realizing that it's in service and support of, you know, essentially, you know, what our faculty and ultimately our student success needs to be geared towards. And so, you know, W.P. Carey has always been one of our great champions in this kind of technology-driven work, and we expect many other schools to follow suit, as well as many other universities try to do so. But the question is, are you as the enterprise technology team positioned to help? Or are you going to basically say, we don't have capacity to do that work, because we're overstretched doing all of the legacy caring and feeding. And I think that's the challenge to technology teams, is, I think you have to very much find a way to, to be of service to where the campus is, but almost always be prepared to support the campus and where it's going.
Rhea Kelly 27:14
That's something I think we don't actually hear about very much, and definitely not enough, that the idea that you're going to have to have a dedicated team for AI innovation support.
Lev Gonick 27:27
There was a time when this idea of what became known, first it was a course management system, and then it became a learning management system. You know, there was one person who was part of a team, who could figure out actually how to do a little bit of line coding, and so that person became, you know, the administrator of the original set of tools that, you know, three faculty were using to create a, you know, a course, using, you know, what we now call a learning management system. Well, that's evolved, on most schools, to teams. Now, the team may not be large, or the team, but it's usually more than just the preserve of one person who, by the way, has six other jobs. That's, that, that, you know, there will be a time, and I think it'll be in the relatively near future, when AI becomes, again, foundational and central to the redesign of much of the way the university works. How we're organized to work is, I think, really important for technology leaders to lean into, rather than to sort of hope that, I'm not sure what, that this is a passing fad, that AI really is actually going to sort of just go by the wayside. I mean, I do think that it's been about 25 years since we've had a significant disrupter to the way we're organized in service of supporting our campuses. You know, if we reflect back as to what changes we needed to make, I think technology leaders would be well, well apprised to actually making a run at figuring out how to prepare to shift and reorganize, to be of service to the university as each university and college tries to meet the opportunities and the challenges of the AI era.