A Conference to Remember ASU+GSV 2025

Welcome to Educast three thousand. It's the most transformative time in the history of education.

So join us as we break down the fourth wall and reflect on what's happening, the good, the bad, and even the chaotic. Here's your hosts, Melissa Lobel and Ryan Lufkin.

Hello, and welcome to the Educast three thousand podcast. I'm your cohost, Ryan Lufkin.

And I'm your cohost, Melissa Lobo. And Ryan and I are here with a special episode summarizing a bit of what we saw at a very popular conference in education, the infamous ASU GSB.

Ryan and I have attended this for many, many years, and it's always really interesting to see the trends, the conversations, how they've evolved, how they haven't evolved in some cases. And so we thought we'd do a little recap of what did we pick up while we were at the conference. So, Ryan, I'm gonna start with you.

A lot of it your direction.

What'd you see? What were some of the highlights or themes that you picked up at ASU GSB this year?

I mean, besides the sunburn on the top of my head from meeting outside, because it's always, one of those places that you're always struggling to find places to meet because there's so many attendees and so many people to talk to. But, like, always, you know, AI is dominating the conversation. And I think what was really interesting is, you know, the if you're not familiar with ASU GSB, they always have the air show that happens right before, the event. And it's a little bit like a startup alley that you would find in a lot of conferences to the nth degree.

Right? And so a lot of AI and tech start ups there, they actually hosted the twenty twenty five GSV Cup fifty, right, and in the top fifty partners AI partners that are out there. And we had some great, you know, practice that continues to be one of our great partners It was represented in that top fifty. SchoolAI, is one of those that is we work with that was represented there and and has some great information.

It was interesting. Brisk Teaching was the one that actually, I think, won that competition and their their k twelve focused AI powered extension and platform for educators that I know also plugs into Canvas. So great to see all of those amazing amazing products. Great to see demos of those.

What's interesting is I think one of the things that we're starting to see is some concern about the proliferation of individual AI tools is, you know, how many large language models are being implemented across your campus for all these different technologies And how do we start looking at managing those or limiting their the exposure for the university? And then really can that move towards more of an agentic approach? How do we start looking at consolidating some of those interactions or powering a lot of interactions with a single large language model across the campus? And so we've seen a lot of of that conversation going on.

Really interesting.

Yeah. Tell me more about that, or sort of the the distinction between the personal approach and the agentic approach.

And in the conversations that you were in, are we early in that transition of approaches? Are we midway through that? Is this the new approach? Give me a little more scoop.

Yeah. We're early in this. Right? This is something that I think we've talked about, the Salesforce Education Summit that was about a month ago.

And that's the first kind of time that was brought up for me that we're like, look, this is the next step is the agentic approach. And I don't know that a lot of schools are actually implementing it at that level at this point. But we've heard one of the things we get feedback on with Canvas is the fact that we're this open architecture with deep LTI frameworks and open APIs. It enables you to be able to plug in those tools.

So we're really well positioned to be able to respond to that, that idea that and if you're not familiar with an the agent, it's this idea that these tools are actually empowered to act on your behalf across different systems. So it access you and it'll go in and log in to it might go to your LMS and then your SIS and your email and and do tasks for you like setting up your courses or these more complex approaches than just the basic chatbots and even the more expert chatbots that we have that are trained on on specific areas of knowledge. Right? This is more of that proactive approach.

It really is the next step in innovation. I think we're early in it. I think we're just starting to see what that will look like.

One more question. Were there conversations about, like, the dehumanization of that? Absolutely. Yeah. Because I leaned into one or two sessions that started to talk about we can't lose the human in all of this. What did you pick up on that?

You're spot on. That was one of those things. That and equitable access, I think, were the two areas of concern a lot of people talked about. And, you know, there were some there have been some articles lately.

There was, there was an article in the Chronicle of Higher Education that talked about the AI University. And Bill Gates, in an interview recently, said, you know, teachers and doctors are jobs are gonna be eliminated by AI. And I think they're way ahead of their skis on that one. Right?

Because what we're seeing is these tools are still I had a conversation with a couple of analysts recently. And what we're seeing is these tools still try to give you what you want. They're trying to give you the answer that you're looking for. And then sometimes, in doing so, they just make things up or they stretch the truth or they get a little ahead of themselves and they're like, well, I know you asked for this and what I was trying to give you was this based off of your response.

It's really interesting. We don't fully understand how some of these knowledge language models are thinking in this process still. And so we're certainly not at a stage where we can just let them loose to run on their own, and they'll be replacing anyone because you still have to have an expert sitting behind their results, double checking their results. I mean, it can't be a layperson.

It has to be somebody that understands how they're wrong and understands the nuances of how they how they sometimes hallucinate or confidently incorrect. So there's that aspect of it. Right? Like, I I just don't see humans the the magic of a human at the center is always especially in teaching and learning, it's always gonna be the goal.

Right? That connection between teacher and student. That's not something you can really replace, in my opinion, with AI, but you can certainly scale that. Right?

You can have a digital twin that is able to answer basic questions after hours or on weekends and free up your time so you're not having to respond at all hours to student requests. Right? It has that basic knowledge. It's not you.

It doesn't understand the depth of your knowledge, but it can act on your behalf in basic ways. That's really helpful. But the other aspect too is the idea that some of these tools are getting really, really smart and really, really specific and, in some cases, really, really expensive. And so how do we make sure that we don't end up with this haves versus haves nots system?

I think that is again, we talked about that early on. You know, we talked about that two and a half years ago when we were kind of outlining our approach for AI with Instructure. And we said, look. Equitable access is gonna be key.

We foresaw that that this is gonna be an issue. And I think now we're starting to see that schools and institutions that can afford these tools are gonna be much more progressive and much more helpful. The other aspect too, one last point on AI for that is AI is not gonna replace teachers, but it might replace teachers that don't use AI. Right?

And we've gotta make sure that we're giving educators the skills, the professional development tools they need to understand how these tools work so that they're engaging with them. I spoke to a educator two weeks ago on a campus, and he said, I'm a good writer. I don't wanna use AI. And I said, then don't use AI to write.

Use it to summarize articles for you. Use it to automate some of the tasks. Use it to go through your email and weed out the ones that you don't wanna respond to. There's so many use cases, and I think because the academic integrity issue dominated the early conversations around AI, I think there's a lot of educators who have not really moved beyond that idea that it's a writing tool or it's a cheating tool.

We gotta make sure they understand that there's so many other use cases that this is powerful for. And it as administrators at universities and these are that, we've gotta give them the resources. We gotta give them the training to bring them along.

Well, that actually highlights one of the things that I really noticed, particularly at the air show, which, like you said, is a is a is sort of a startup alley for AI tools.

At ASU GSB, I ran into more individual educators than ever, more teachers, more professors, faculty members.

It really surprised me how many were attending not only the air show, but the overall conference.

And the questions that I would hear them talking about or even in some cases, they came you know, would ask me these questions were, how do I, like, understand this space? How do I navigate?

How do I know even what to ask Good feels daunting.

These it's like it's daunting because there's so many tools or so many different approaches. I was hearing a lot from educators. I'm not even sure what questions to ask or how to be able to know where to spend my time and not spend my time, which I thought was really interesting. This came up.

I was at the the BET show earlier this year in in London and was presenting in a in a session. And one of the questions that came up was from an individual teacher. And she said, can you help me what what questions do I ask vendors? I'm interested.

I want to be using AI. I wanna learn. I wanna be innovative, but I don't even know what question to ask. And one of the things I encouraged her to think about, and I continue to encourage people, is just ask them why their tool is using AI.

What's the point of AI?

What problem are they solving?

What problem are they solving? Exactly. But I think that was that was a big observation for me this year at ASU Speed for sure.

Well, you and I have both presented on AI literacy and really how do we help give those tools and that our deck is full of these resources. So we're actually we're creating in the Canvas community an AI resource hub that'll have all the links that we've included in our presentations. But it it's interesting because Arizona State University on their AI resources website actually has a process for vetting AI vendors. Right?

And and they're sharing that with other institutions. Right? University of Michigan was one of the first institutions that had a how to teach with AI in the k twelve classroom and in the higher ed classroom. Right?

There's so many resources out there. I love that about education. It's so collaborative. We share what we learn and there's so many resources out there.

So watch for that. We'll be posting in the Canvas community that AI resource hub. But I think the goal is to really share as many of those. How are schools applying this?

What are the use cases? Right? That idea that, in some cases, you don't know what it's capable of until you've seen somebody else do it or somebody else has pushed the boundary on that. Right?

And how do we learn from that? How do we share that is, I think, really important.

Absolutely. I couldn't agree more. You know, the other thing I picked up on, and I'm I'm sure you saw this in some of the sessions, separate from AI, although I know that is one of our favorite topics for our podcast, was navigating this changing political, social, economic landscape. Right?

And, you know, I heard in multiple sessions, and and this came up in multiple conversations as well. You highlighted this cost. Right? And how are we thinking about ensuring equitable access to really great innovations, but how are we balancing that with reduced budgets?

That was a big topic. How are we balancing that with large swaths of education, even globally, having to reinvent themselves because they're being either challenged or questioned or looking for new models in order to also follow along with the innovation in the most meaningful ways. I don't know if that came up for you at all.

Oh, yeah. For sure. Yeah. I mean, I think that it's just the the unknowing. The instability piece is is really challenging.

And at the same time, going back to AI just for a second, like, you can't we can't sleep on AI. We we've gotta continue, you know, that innovation. And, you know, even the the new executive orders around AI for education really do lean into that quite a bit. But it's that annoying.

And what is you know, are we gonna have the resources to do this? Is are the budgets gonna be cut? So how do we move forward with something we know we have to do in, you know, real time and still kind of hedge against those that the, you know, revenue issues and that kind of thing? So one thing I am hoping for is in the executive order from this administration around education, they actually outlined an AI literacy approach that promised an an outline for an AI literacy approach that we're hoping to come down the pipe soon because we are seeing you know, there's a lot of news in other countries like China.

They're implementing AI literacy at a very young age, first grade level, six year old level. And I think that's for the good of our society to be able to recognize deep fakes, to understand what AI is capable of so we understand misinformation, false information, but really just are prepared for the jobs of the future and using these tools. We've gotta start building that out, and that's something that I'm hoping that that the Department of Education actually leans into and provides that in the near future because I think that's really important and really helpful.

Yeah. Agree. Completely agree. Maybe I'll throw one other highlight that I I picked up on.

Totally different. Right? Because ASU GSB, for those of you that have never attended, I always describe it as three strands running together at once. There's the new technologies, innovations.

Let's come see what's happening in this space. There's the investment strand. Right? So there's a heavy okay.

Not only are we am I here to to learn what's new, but I'm also figuring out in the investment community, where should I be putting my dollars? How should I be supporting some of these innovations so they can grow more quickly? So that's a whole separate strand. And then the third strand is always around leadership.

And it's interesting because it brings together leaders of some of these companies that don't normally have opportunities to either come together. It also can be an opportunity for recruiting and some other things like that. What I picked up on, though, especially in talking with our CEO, is there's more senior leaders that aren't technology leaders, are leaning in more and more from education institutions, from districts, from states. You're seeing more chief academic officers at the state level in the US.

I met with a number of leaders from other countries around the world. The conversation's elevated. I think if I looked back at my ASU GSB five, six years ago, it was a lot of CIOs having these conversations. Handful of presidents.

Again, you had those investors, but now you're running into CEOs of companies. You're running into chief academic officers. You're running into folks that are not necessarily focused on technology, but really focused on this reinvention of education. I don't know if you ran into that.

No. Hundred percent. I was gonna say, you know, I attended Latin America reception. Shout out to my Latin American friends.

And I was surprised at how large that group was. And so I think the international just to your point, the international growth around this conference, these conversations, these aren't conversations we're just having in individual states or in individual universities. These are global challenges. And I love the we've got this kind of diverse group coming together to actually discuss how we solve those challenges.

It was really in a very positive in in a in a challenging time. And in a time of not knowing what's going on, it was a very positive vibe. It was a very, you know if you've ever been to ASU GSB or even if you haven't, it's one of those it's you spend more time missing sessions or being late to sessions because you got stopped in the hall to talk to somebody. You know, it is so funny if you've mostly, you and I have both been in EdTech for a long time.

It's kind of like old home weight too. And so you actually get to see a lot of the people you've worked with that have moved on to other EdTech companies. And I just I love that aspect of it. I think it's always amazing to run into people that you stop to talk to one and then two more walk up and, you know, it's just it's fun.

Yeah. I totally agree. And maybe this is a good place we can both end. But I was surprised by the positive vibe, particularly given so much concern about technology and and education and and the merging of the two.

Right? And there's also a whole workforce development strand. Ryan and I tend you you and I tend to lean in on the more education strand than some of that workforce development. But even across the board, there was a positive vibe of we're in this together.

Like, I really felt that this year, maybe more than in the past, and still a deep interest in solving the big questions that are out there. So maybe I'm gonna throw a question at you, Ryan, as maybe our our wrap up here. What did you leave wishing was being talked about more?

And I think there was a little bit of it, that recognition of you know, you were talking about professional learning and lifelong learning, that aspect of it, but, like, the recognition of learning, so the credential side of it, or what what does that look like long term? And there was there was definitely some of that. And that was and it could've just been my perception because I naturally get pulled into those AI conversations. But this idea that we need to find ways to recognize learning wherever it happens throughout a life cycle.

And and, again, that stackable credentials, sometimes they call it CLR. Sometimes it's learning employment record. Right? Like, these different terms.

But how do we make sure that students are able to demonstrate their proof of skills and their proof of knowledge, you know, for at every phase, at every joint. You know, like, something we take to heart. We both do sort of, you know, certificate programs. I recently did one with with Oxford State Business School.

Right? You know, you just did one with Google. Right? Like, those this idea that you can actually go out and and constantly upscale and rescale.

But how do we get a more, I guess, verifiable approach to that?

Expansive Yeah. Understanding of recognition. I think so from an academic perception, I'm gonna I'm gonna add on to that as sort of my thing that I wish we were talking more about. We're still talking, in my opinion, about skills as something that was formally obtained and verified.

And how do we start to expand our notion academically and in society of what recognition really can be? How do we create identification or our unique identification in what we have to offer for ourselves?

And in that is informal learning, informal training. Embedded in that is, you know, I always think of when you get credit for prior learning in education. Right? It it's formalizing that from a credit perspective, but what it's acknowledging is you have skills that you've accumulated, maybe not in a traditional program or course setting, but you have those skills. And how do you acknowledge and bring those skills to the uniqueness of you so that you can contribute into society and into the professional workplace or even your personal environment more effectively. So I hope we I hope we, from an academic perspective, nerd out a little bit more in the space around what can recognition be, what's the expansive understanding of recognition.

Because the problem there too is we're still seeing employers. I mean, we suffer from it ourselves, but you're trying to hire people and you're getting thousands of of resumes or thousands of applications. And how do you cut through that and really find the right people for that job with the real skills? And AI AI does a great job of writing resumes and writing that kind of stuff. So how do we cut through that noise and really get to the heart of who would be the best employee for this job? And that's, I think, the I love that that's your your angle because I I really do think that was not talked about enough. And we there's so much more to do on that.

I love it. Spot on. Well, thanks for chatting with me, Ryan.

Yeah.

It's a big recap.

I know. Obviously pick up on.

Yeah. This is we haven't had a chance to talk about it since we got back. So this has been off the cuff, but really fun. So thanks for listening.

Yeah. And we'll include there's been a couple of good summaries out there of what happened at ASU GSB, so we'll make sure we'll drop some of those in the notes as well, just in case you're curious. And I think even some just background information on ASU GSB for those of you interested in attending next year, kind of understanding that conference's connection. You talked about it. Brings a really diverse community together.

It's very unique in the in the space.

Yeah. We'll make sure to share more with that for anyone interested. So thanks for listening, everyone.

Thanks, everybody.

Thanks for listening to this episode of Educast three thousand. Don't forget to like, subscribe, and drop us a review on your favorite podcast player so you don't miss an episode. Episode. If you have a topic you'd like us to explore more, please email us at InstructureCast at Instructure dot com, or you can drop us a line on any of the socials. You can find more contact info in the show notes. Thanks for listening, and we'll catch you on the next episode of Educast three thousand.