How University Of Phoenix Is Redefining Online Learning For Working Learners

Forget the clichés about online college. We take a clear-eyed look at the University of Phoenix with CIO Jamie Smith and unpack how how the university is rebuilding around a simple rule: design for working learners by assuming school is the third priority after family and work. That shift changes everything—from the reliability of the tech stack to the tone of a nudge—and it’s driving a wave of practical innovation that blends human care with AI “bionics.”

Jamie shares how Phoenix differentiates through a clean, multi-petabyte data foundation, long-honed risk models, and a relentless focus on reducing friction outside the classroom. We explore why generic AI often fails without trustworthy data, how to set legal and ethical guardrails in a regulated space, and what it means to “build it in, not bolt it on.” You’ll hear concrete examples, from celebratory confetti that actually boosts motivation to skills-mapped coursework that flags when a learner is job-ready—then points to local openings.

Culture is the other headline. Phoenix carved out weekly “AI leverage time” so engineers could experiment, document, and demo progress, while also opening safe on-ramps for non-technical teams to build useful tools without creating security headaches. Looking ahead, Jamie sketches a near future of zero-UI experiences and personal GPT copilots that know a student’s goals and rhythms, escalating to human advisors when nuance matters. We close with pragmatic advice for traditional universities under enrollment pressure: strengthen data, clarify ambitions, avoid vendor sprawl, and move IT from back-office to strategic co-leadership.

If this conversation reshaped how you see online learning, subscribe, share it with a colleague, and leave a review to tell us what you want explored next.

https://www.phoenix.edu/

eloy@4leggedmedia.com

Transcript

Reframing Phoenix’s Reputation

SPEAKER_00 0:10

Hi, this is Eloy RT Z Oakley and welcome back to the Rant Podcast, the podcast where we pull back the curtain and break down the people, the policies, and the politics of our higher education system. In this episode, I talk about the University of Phoenix. That's right. The Phoenix is rising. I know many of our listeners will be surprised to hear me talking about the University of Phoenix, especially given my previous years of advocacy to rein in the for-profit sector, and specifically in California, to rein in the University of Phoenix. But those were different days. Those were days in which the University of Phoenix was not acting as a good player in the marketplace, at least in my opinion. But today, I think times have changed. And like I said, the Phoenix is rising. The Phoenix is on the move again. And going back to its roots of serving working learners, we cannot talk about serving working learners or fully online education without talking about the University of Phoenix. They were the pioneers. And many of the practices in the field, many of the ways that we think about working learners all began with the University of Phoenix. So I'm going back to the University of Phoenix to find out what's going on. And with me to talk about it is the Chief Information Officer, Jamie Smith. I talked to Jamie about the types of innovations that the University of Phoenix is bringing to bear for working learners, how it's leveraging AI to improve the user experience, how it thinks about designing for working learners. I think you'll find the conversation with Jamie fascinating. And I think it's time to take another look at the University of Phoenix. Yes, I know that their business model continues to change. Many people are skeptical about whether or not the University of Phoenix really is well intended now and going forward. But as I think back to about five or six years ago when they first hired Peter Cohen as a CEO, I've known Peter Cohen for many years. And he really did a great job of bringing the University of Phoenix back to its roots. So I think it's worth giving them a look, giving them a chance, and see where this all goes. At the end of the day, we do have something to learn from them, and the way that they're investing in innovation and technology will give us something to take a hard look at to see how they do. I hope that they continue to put their focus squarely on the learner and not solely on profits. But we'll see. But in any case, it's a great pleasure to have Jamie Smith with me today, the CIO of the University of Phoenix. So I hope you enjoy my conversation and please welcome Jamie to the Rant Podcast. Jamie, welcome to the Rant Podcast. Thanks. I'm really happy to be here. It's great to have you, Jamie, and thanks for taking time out of your busy schedule. There are a million things going on in the world right now. There's a million things going on in higher education everywhere, so I'm sure that's no different there at the University of Phoenix. So thanks for taking the time. Let me start by just introducing you to our listeners. I know our listeners know the University of Phoenix, but some of them may not have had a chance to get to know you. So, Jamie, you are the chief information officer there at the University of Phoenix. Tell us about your role and just how long you've been there at the University of Phoenix.

Designing For Working Learners

SPEAKER_01 3:38

Uh sure. My role is chief information officer, as you said, and my team oversees all of the technology platforms at the University of Phoenix. So all of the digital experiences, which being that we're essentially 99% online these days, that that's the campus, it's the bookstore, it's the Memorial Union, which was the fun part. It's that not so fun part where you had to pay your bills on campus, it's the career office. It's the totality of the experience, which is pretty amazing. And I actually have been here going on eight years now, so it sneaks up on you. And and this is my first turn actually in higher ed. So my background, I like to say I'm a mostly reformed consultant. So I spent a lot of time with PricewaterhouseCoopers and IBM and doing a lot of large implementations across a variety of industries, and then entered into the private world and was with Nissan Infinity for a while and did a lot of global stuff, which was really interesting. And then my last turn was with Service Master, which is a home services company, which you think, okay, home services and the higher ed, what do they have to do with each other? But I think you know what we find is our students aren't measuring our digital experience against other universities, even other online universities. They're looking at it based on the best experiences they have in their daily life, right? And so bringing the notion of applying technology to these experiences and making them better. And then, you know, while the mission of kind of killing bugs and keeping houses clean at Service Master was great, we are changing the trajectory of families for generations here. I'll never forget first I was interviewing the University of Phoenix and on the board our student Wi-Fi password, which we've changed it since then, so it won't work if we go back, but was we graduate families. And so long password, but it really hit me in terms of the mission, and I've been hooked ever since.

SPEAKER_00 5:28

I think that's great. Yeah, I think that really sets the stage for this conversation because it is about making that transformational change, individuals, families, communities, and the University of Phoenix has a long history in higher education, really the pioneer in online education. And I know it's gone through various iterations and different operating models, but just to hear you say that 99-ish percent of all of your instruction is fully online, that that mission continues. And that is definitely an area of growth across the country. There are lots of other colleges and universities now in this space. So, given that long history of serving working learners online, being the pioneer in online education, in some ways coming back from the ashes, not to put a pun on the University of Phoenix, a lot has changed over the years, and you've been part of some of that change. Through your role, how are you and your team thinking about deploying technologies and other innovations that help the university not only differentiate itself from other online universities, but also to really improve that student experience that that you alluded to, the whole purpose driving the reason you're there?

Reducing Friction Beyond Coursework

Human Support With AI “Bionics”

SPEAKER_01 6:49

Yeah. Yeah, it's interesting. That was part of what also got me very excited about University of Phoenix. I of course had heard of it, but going walking through the halls, I saw our first online uh education. It was really mailing a three and a half inch floppy discs. If you can remember those things, I'm probably dating myself just by knowing what those are, but I remember floppy disks. Yeah, exactly. And it was called distance education. And really, it wasn't about the technology. That's the important thing. The technology was just the thing that got us to the thing. And the real thing for Dr. Sperling was fitting into working adults' busy lives. And that's the whole reason the university started and it didn't exist, so he created it. And he was a bit of a maverick, which I like to think of myself as a bit of a self-styled maverick and enjoying creative destruction and the disruption and all of the positives that can come out of that. And so I think at its core, our average student is in their mid to late 30s. On average, uh single working parent, they have a lot going on in their lives, right? And so when I get my team to think about it, I think back to a focus group we were doing. This was fairly early on. And one of the students, we talked to students a lot, which is great. And one of the students was relating the fact that you're you guys are always gonna be third in my life at best, right? And I was like, third, that sounds weird because going like when I was going to school, I thought it was the only thing, right? I was traditional student and first generation students, but the way she related it was my family is always gonna come first. And so if my son breaks his arm on the monkey bars, so which sometimes happens, and I have to take him to urgent care, the assignment's just gonna have to wait. That's gonna come first. And then I need my career and my job to make a living and put put food on the table and all those things. And so at best, we were always gonna be third. And so the way I relate it to my team is our experiences need to be designed to be third. They need to fit into the places in busy working adults' lives where where they can. That five minutes that they have to turn in the assignment on the bus on the way to work, maybe the only five minutes they have that morning until the evening when they're sitting at their coffee table. And so, first of all, the technology has to be there. It has to be unobtrusive, it has to work, right? Those are like we have to be brilliant at the basics because we're always on, and our students are always on 24-7. And then also, I think everything outside of the coursework's always going to be hard. College algebra, the college math, and biology, though those things are what they are, and it takes quite to get through them. But the rest of the total experience should be as friction-free, proactive as possible so that we can get there. We don't want someone to have to wake up and try to resolve a problem with financial aid or those things are complicated as well. And so, in some ways, the digital experiences have to enable that, but they also have to fade into the background. So you don't, and so we focus on reducing that friction, ensuring that as an open access university, we don't want to be the thing that um gives you the lack of confidence to continue. Like progression is really important. Life happens, it's hard. And so we do leverage a lot of things also to be very proactive and nudge technology, all the things. We've been doing that for well over a decade with AI and ML and our OG models that are there, if you look at it. But really also, I think it more and more, it's about the things that we can do now with AI to enable, like our human support model is amazing. So, our academic counselors, for example, when you talk to students that have graduated and made it through, almost all of them have a very inspirational story about that dark day when life was happening and they were about ready to give up. And they got a call from one of our academic counselors. Some of the technology, also on our side, is about giving them bionics, like giving our people that are interacting with the students the tools that they need so that they can have those transformational conversations and those very inspirational, nuanced things. And especially, and I know we'll probably talk about AI. You can't go these days at least a half hour on a and talking about technology.

SPEAKER_00 10:38

We wouldn't be talking to the chief information officer if we're not going to talk about AI.

SPEAKER_01 10:42

Exactly. But especially in this world, we're viewing that symbiosis between our people, AI, and the student as a real partnership. And that's why we refer to it as bionics for our people because we understand how important that is in our students' lives. In some ways, I think about the technology, but I think about it as a means to an end. And that end is keeping the student in school, keeping them progressing for ultimately what are their career and life goals.

SPEAKER_00 11:06

I really appreciate how you began answering this question, which is designing, you know, around being the third most important thing in a working learner's life. I think that's a great point of view, great design principle that I I think in higher education in general, and certainly been in higher ed for 30 plus years, I don't think is has always been at the center of the design. And I think having that as a primary driver, I think, really leads us down the path of better understanding how we leverage whatever technology there is in that point in time. When I was first in college, I was accessing distance learning. I used to have to check out a VHS tape and play it in the library video and take the course there. That was distance learning in my day. Now it's come a lot further. Given your role and your team's role there at the university, you see all these technologies being deployed throughout the higher education marketplace and certainly amongst some of the other fully online institutions. How do you think that the University of Phoenix differentiates itself, particularly in the student experience? How would you describe that difference at the University of Phoenix versus other online institutions?

Differentiation Through Data And Nudges

SPEAKER_01 12:31

It was interesting. Being here during COVID, we overnight had either 3,000 competitors or 3,000 new imitators or whatever you want to call it. And I think that kind of did two things. It showed one, you could learn this model works, right? You learn it's a top-level model, but I think it showed also a lot of universities how hard and how different it is, right? And it's taking a long time for the University of Phoenix. Our secret sauce is the ability to deliver this model and all of the wraparound support as well. Of course, there's the classroom experience, which for us is asynchronous. It's one course at a time, five, five or six weeks at a time, depending. And so designed to again be third. So it starts with our curriculum and then how we deliver that, how we support our faculty. Our faculty are mostly adjunct faculty that are practitioners. And they're, we like to say, in the boardroom during the day, in the classroom at night. And so we can't have friction for our faculty either. It can't be hard to set up a class, to grade, to do all of those things. And then what's where the evolution of this is like one of the beautiful things about being online that's challenging in a physical kind of classroom in that world is a couple of things. We get an immense amount of data about the student behavior and student experience. So I call all of this digital terabytes of digital exhaust that we have to work with. I think in the days before AI and machine learning, like that was interesting, but maybe not that useful sometimes because it was hard to separate the signal from the noise. But now having that level of data and that understanding, that deep understanding of how students are progressing, what they're struggling with, what might be happening in their lives through this passive kind of collection of all this data with which we can train all of these models, it lets us be proactive. It lets us anticipate, look around corners, see what the student might be struggling with. And I mentioned kind of our nudge model, which is just one example pre-LLM. It's been there for a long time. But every time we've taken kind of the Pepsi challenge with one of the commercial off-the-shelf tools, that tool is always one. It's done better because it both identifies academic risk and progression risk and has very tuned nudges. And we've we've been working on that kind of iteratively in partnership with AI for a decade. And I think, especially now in this moment, having that technical and data foundation that we've built out, we haven't just implemented one vendor product and built our whole world around that. And we're not we're not dependent on outside vendors for innovation in their innovation roadmap. We can be very responsive to the student, find things both in the prospect experience as they're figuring out where to go to school. So things like very lightweight abilities to quickly get a read on your transfer credits. So the AI is reading transcripts and anticipating and using all of the data we've collected over the years by transferring in and out millions of credits with URC Phoenix, like having that corpus of this really good and clean data, it has to be clean also, has helped us differentiate because we can empower experiences that are very difficult to do without that. And that's what I'm probably most bullish about going forward is our ability to quickly lean into these things, see an opportunity, listen to students. And it's it's sometimes funny things that are differentiating. So we do again, we had a student paddle at one of our leadership gatherings. And so four and five students up there talking about their experience. And there was this little feature that we put on our student portal that was just like a what one of our one of our developers that was actually a student said, This might be fun, let's try it. So that when you got a new, either you completed a course or you made the dean's list or whatever, like confetti would fill the screen, right? Just a simple little thing. But every one of the students on the panel said, you know what? I was so excited to log into the student portal the next day to see that confetti, get that little good job, those pieces that are there. And then I think as this evolves, it's going beyond personalized to making it truly feel personal and not creepy. That's the line you always block with personalization is it has to be in the pursuit of what's best for the student and their outcomes. But for example, we can I think the other thing has changed, you were talking about kind of the span of time since both of us have been in college. Like at one point, the degree was the mark of completion, but also the mark of starting your career. And we like to say it's for us, it's not the finish line or the starting line. So, for example, if you've taken three courses at University of Phoenix and we've mapped everything to skills, so every one of our courses is mapped to distinct and verifiable skills, and the AI picks up that you're now qualified to be a scrum master, for example, finds a local job opening within your area, suggests that. And so again, it's about trying to match those very personalized outcomes as you're going through the experience and just focusing on that. So the things that we can enable, because we have that data and we have that level of personalization, are truly differentiating given where AI is right now.

Clean Data And Guardrails For AI

SPEAKER_00 17:22

That's a great example. And I love the way they use the term making it more personal, not just personalized. Yeah. I think we all want that experience in every interaction that we're engaged in. And I think sometimes while the experience that we're engaged in, whether it's a commercial enterprise or your bank or what have you, you're getting bombarded by the technology, but it doesn't feel personal. So I love the way that you describe that. Now, with the caveat that I am not a CIO, I'm not a CTO, I come from the administrator world. So feel free to correct me if I describe this not completely accurate, but a lot of colleges and universities are experimenting with large language models. There's always the on the news feed, so-and-so is now partnered with OpenAI, so-and-so is now partnered with some other large language model provider. And while it feels like that can get you so far down the road, having the model specifically look at and be trained from the data that your learners are giving you would seem like it would lead to a much more personal experience, and particularly given the amount of data that I'm sure the University of Phoenix has for all the years that it's been operating, all the learners that it served. What kind of advice would you give somebody who's thinking about tinkering or beginning to look at large language models? Is that where you would need to begin, or should you be looking at trying to figure out how to create sort of a small language model that's more specific to the learner experiences that have that you're picking up from your institution?

Build It In, Don’t Bolt It On

SPEAKER_01 19:10

Yeah, that that's a great question. As I think about it, one of the keys that we had been investing in for years, hoping and believing that this kind of data foundation we'd invest in. So we do have a multi-petabyte data lake where the data is cleansed, you can believe in at those pieces. So where and I work with Gartner as well for some advisory services, and the number one reason that these large language models and the new AI pieces are failing are really two reasons. But the number one is the data's not clean, it's not available. And you do try to take an off-the-shelf, fairly generic model, and it just doesn't work. The AI is going to believe what you feed it, it's the old garbage in, garbage out, but with more autonomy, right? So it's not some of the checks that you had in a deterministic world aren't there. And so that data foundation is really important. And then ensuring that your AI ambitions match where you where you really are in the maturity curve. For example, we have a virtual assistant that's a a genetic supervisor-based gentic framework that's sprawling out and starting in really deeply in enrollment, because we believe that if you learn that it's a really good experience, interact with Phoebe Phoenix, as we call it, while you're enrolling and onboarding, then you're going to carry that through years. You're not going to unlearn any other type of support model, those pieces. But in order to roll that out safely, we needed to have things like guardrails and not just around like prompt engineering and all those pieces, but there are words that matter in a highly regulated industry like education and especially in the enrollment space and other places to get legal, comfortable, but also ethical guardrails, ensuring that the outcomes that we're trying to drive are in the best interest of the student and their progression in those pieces. Rushing ahead of those things is a recipe for disaster, right? So you do have to train that. And then we have we work very closely with our legal and compliance and all of those pieces. But I like to say that the brakes are on the race car to help it go faster because you can be can go faster down the speedway and break later. And so that that's a big piece of it. I think the other thing is careful to not just bolt on AI solutions in a lot of different places. Because you mentioned the experience sometimes and the frustration of dealing with enterprises where it doesn't feel personal or you feel a very disconnected thing, and every vendor has an AI product today. So if you're just plugging them in all across the board and you haven't done that underlying work to build a foundation, that that kind of brain, that deep personal profile that all of these can access, but it's going to feel very disjointed at a very fast speed, where before things felt disjointed, but the technology maybe didn't have the level of autonomy that some of these agentic solutions do. And so it's more contained. And so you can make a mess faster as you're bolting it on. So we're trying to build it in and not bolt it on and rely on the foundation. Now, the other just the last piece I'll say with that is you also don't want to spend a lot of time creating solutions for problems that have already been solved. And so for we use Blackboard as our LMS, and we're working with a partner vendor who had a deep integration into Blackboard and already had solved what the experience feels like to interact with AI in the classroom experience. Now, the backend models are ours, right? And they can call out and train those and trained on our data. And so there are right ways where you can focus on not building out all of the plumbing yourself, then deeply focus on the things that are differentiating from an experience standpoint.

SPEAKER_00 22:25

I recently had a conversation here on the RAM podcast with one of your colleagues, Lev Gonick, the CIO of Arizona State University. And one of the things that fascinated me. Lev described this insatiable desire to innovate at ASU. Clearly, always a lot of pressure on the CIO and his or her team to keep up with that innovation, to continue to test the bounds, continue to focus on improving teaching and learning through technology. How do you and your team think about that? Because I'm sure you have a team there at the University of Phoenix who also has this continuous drive to innovate.

Culture Shift To AI Fluency

Safe On-Ramps For Non-Tech Teams

SPEAKER_01 23:06

I'm obviously an employer as well as being part of the university. And in some ways, I think every employer, especially in the more technology-enabled workspaces, are feeling this. How do you create a workforce that's AI ready and truly leaning into it? And we have at the University of Phoenix, we believe that AI fluency and AI literacy across the entire university is an existential component of where we're headed. Uh, it was probably last May at an off site, my team got together and we thought about what good looks like in an AI world. What are the types of things that we need our engineers, for example, to exhibit to be comfortable? And so, for example, if you're someone who thrives in an in a repeatability or a low-change environment, probably not going to be suited for the world of AI. Like it's moving as slowly right now as it's ever going to, and it's only going to exponentially increase. But things like curiosity, problem solving, communication. So we defined what our competencies are. The other thing is being a technology organization, our backlog is never empty. So even pre-AI, there was an insatiable demand for all of the things that technology could do, especially in an online university. And so we found that we had to make the space for our team to actually learn and lean into AI. And it took some convincing with my peers. Let me start there. But we carved out over roughly a quarter of the year, two hours every single Tuesday for what we called AI leverage time. And that time was not available for meetings. It wasn't available for anything else, a very light curriculum, but it was there to give the space for allowing our teams to experiment with AI, agentic AI solutions, a very, a very deep community of practice developed. And then at the end of every one of those, they would journal what they did so others could see it, small demos. And so the transformation in the team, what we were trying to be careful not to create is this island of AI, like the cool kids over there that know AI and anything AI has to go through them because we do want, we do want it built in. And then back to rolling out those competencies that we talked about of how we're going to think about performance, how we're going to think about that. And so transformation's been dramatic. We shifted AI leverage time now to focus on our product teams. And so they're working as a team instead of individuals this quarter, still for two hours a week. And so, one, that transformation has been amazing. So having this like an army of roughly 300 engineers that are all AI fluent can develop it. And then the expectations, you get what you celebrate, get what you tolerate a little bit as a leader, right? And so celebrating the advancements, we're making that very visible. The other piece, and this is something I think Lev mentioned also that we found is the non-engineer world has a lot of access and can do things with AI that maybe business technologists. It used to be back in the dark ages of technology, somebody in some department would go get a Microsoft Excel or Visual Basic book or Microsoft Access, and you'd inherit this thing and they called it shadow IT, and it was always a mess. But I think with AI, for example, like our HR partners have created this kind of internal chatbot that's read their wikis and all of their processes, and they can ask it questions, and it's like an Ask the Expert. We didn't have to get involved in that. But when you scale that back to the guardrails, the safety pieces, there's a safe way to roll that out so that you're sure that sensitive information is protected and it's secure and all of those pieces. And so creating that on-ramp for the broader university and expanding the amount of impact that technology can have by letting others in safely is something we've been very intentional about as well. And then it starts actually with our president, who's insisted that the entire C-suite is just this uses AI. We live in it every day. In fact, our general counsel was on he we have an AI innovation Slack channel that everybody posts ideas on. And he got his own really powerful rig now that all the engineers were drooling over. He runs his own AI models locally. So it's like when you have your lawyers like that deep into it, like the expectation is we're moving forward. And then also he knows all the all the challenges with hallucinations and all the it's not just a magazine article that he's runs. I think that pervasiveness of it and then being able to have this engineering team as well as allow the broader university there has been transformational for us so far.

SPEAKER_00 27:16

Now, given this pace of innovation and the deployment of new technologies, given your crystal ball, Jamie, where do you see the student experience? How do you see it looking different there at the University of Phoenix over the next five years?

The Next Five Years Of Student Experience

SPEAKER_01 27:32

Yeah. It's funny how far five years out seems right now. That's one thing I'll say. And I think as humans, we're we're not great at really being able to visualize exponential change, which I believe we're on the verge of that the hockey stick of exponential change. And looking forward, I know it's going to look very different. I and I think some things that we're seeing are traditional user interfaces, for example, the LMS, all those pieces. Like that may be there's a thing called zero UI or the invisible UI. It's really maybe all encapsulated in the chat interface, for example. That may be the primary way that you interact with curriculum, the instructors, the university, everything. And then I think the other piece that we're really deeply focused on is what are the jobs that haven't been invented yet that we need to prevent, prepare our students for? So every one of these, the industrial age and the information age, all of them have destroyed a lot of traditional jobs, but they've created more than they've destroyed. And so the hope is as we're leaning into this, what does that look like? And our provost very early on was leaned into AI, thought of it, you know. So a lot of universities were like, no, don't use Chat GPT or don't do these things, that's cheating. But we know that our students are emerging into a world where AI fluency is an expectation. If they're not using it in their jobs, they're not going to be top performers, they're not going to advance. So very early on, we did that. So it's about building that into the student experience, understanding what we're preparing them for. And I think even back to the same competencies that we're we're looking for in our engineering team, right? Grit is really important. Curiosity, like all of those things. So, how do we bring that out in the curriculum, in the experience there? And then finally, the way I almost envision like this co-pilot that sits on your and sorry for Microsoft to take the word, but really in your journey, it's a copilot, it's a navigator, it's whatever. Almost every student will have their personal GPT that deeply understands and knows them sometimes better than they do, and will help them on this journey at all hours of the day, 24-7, 365. When they need to reach out to a person, their academic counselor is there, but it comes with the bionics that are there. So again, I just think it's going to change so much. It's hard to say exactly what it looks like, but I think the kind of the pillars of what it looks like are still there. It's just going to be a very different. I guess we'll probably look back in five years and feel like we did when we were like you were getting that VHS tape, or I was mailing the cloppy discs back and forth, right? For a German class that I took to over distance learning. I think it's going to be that fast. And look, higher ed traditionally moves at a pace that's probably glacial. And so this is going to be an interesting transformation to see who meets the moment. And there are a lot of foundational pieces to meet that moment. But I think we're well positioned to do it. We talked about the data, we talked about the innovation, the fact that it's already online and we've leaned into it. And I think that's what society needs. Again, back to every employer having the same thing right now. And my other hope, just as an aside, and not technology related, is because of the speed at which businesses need to transform, um, I think employers are going to have to fund that in a way that they haven't before. Tuition is a bad, it's not just a benefit, right? Or whatever. It's going to be core to the mission of every business to have an AI-enabled workforce, or they won't be relevant anymore for much longer. And so that's where we're leaning in as well through our partnerships. And that's the best outcome for students, right? Your employer pays, you're employed while it's happening, all of those things, no debt, like all the great things that are there. So again, that's aside from technology, I think the impact of technology is going to drive that away.

SPEAKER_00 31:05

I couldn't agree more. I think continuous upskilling and reskilling is not just the reality of where we're at today. It is just going to be the way we function. And employers will have a role, state governments will have a role, the federal government will have a role, individuals have a role. And I think you're right. And I think institutions, whether public, private, on ground, fully online, need to be thinking about how to integrate into that reality going forward. Let me ask you one last question as we begin to wrap up, particularly on this last note. University of Phoenix has invested significantly in the technology that it deploys. It thinks about online education from a technology first standpoint. And it designs around working learners. A lot of more traditional colleges and universities across the country are wrestling with this reality right now. And we see all the other institutions, certainly the University of Phoenix has invested. Well, we talked about Lev and his team, they're at ASU. ASU has invested heavily. I spent a lot of time with Western Governors University. They've invested heavily in the technology. But those are still more of the outliers, and everybody else was trying to figure out how to catch up. As a CIO in this space, how would you advise others in the technology space at some of the more traditional colleges and universities as they think about how to begin this journey of testing AI and other machine learning technologies in their institutions? What would be your advice to them?

Employer-Funded Upskilling At Scale

SPEAKER_01 32:46

Yeah, and I have, since kind of joining the industry, interacted with a lot of my peers at more traditional on-ground universities. Serving more traditional students. When I say traditional, kind of the 18 to 24 nutritional piece. And um, I think it's going to be a big challenge. We started with this a little bit when we were talking about the orientation of University of Phoenix, is a little different in terms of reducing that friction, all of those pieces. But I think that part is just going to come because, again, as a matter of course, that's what students are going to demand. They're going to be choosier. I talk about the enrollment cliff and the demographics and more traditional spaces are there. And so it is going to be more competitive. And I think most of the universities don't have the kind of larger internal engineering staffs that we do. So part of this is about building that talent base internally so that whatever happens next, you can be prepared for it. So build agility into it, partnering across the various functions, the academics and student services and all the components, and rethinking what you are as a technology organization. A lot of times, technology organizations in traditional universities are more order takers and just keep the lights on, make sure that the email is working and all these pieces are there. And that's fine. That's table stakes, though, right now in this new world. And so you almost have to rethink what your organization is and can do and what your mission is as the tip of the spear of some of this innovation and doing it safely. So more of a true advisor partner role with the other groups. And then, you know, look, there are a lot of different ways to make this happen. While we've we haven't chosen to go all in with one vendor, there are certainly some vendors that are doing some great things in this space. Find the solution that's right for what your team is made up of. Don't try to build it all from scratch if you're if you have a three-person engineering shop. That's just not gonna work. But find willing partners uh across, and then back to just make sure you document and understand deeply what your AI ambitions are so that you can build small, but have outsized returns. So there is an opportunity for asymmetric returns here, but there's also that risk of asymmetric problems that you can create very quickly. So build the guardrails, do all the things you need to do, climb that maturity curve. But again, it's back to making the time for it and having that commitment to build that internal strength in the teams and rethinking yourself. I know that wasn't just one answer, that's a lot. But this is a multifaceted challenge that we're dealing with, or really an opportunity, I think, for technology organizations to have a deeper impact on student experience, period.

Advice For Traditional Universities

SPEAKER_00 35:14

Well, I couldn't agree more and seeing the role of the CIO really as uh not just a function behind the scenes, but a function right there with the provost, with the CEO, with the chief student services officer, continuing to improve teaching and learning to improve the student experience is going to be key, a key role going forward, given all the technology that's being brought to bear. So, Jamie, I know you've got a lot going on. I want to let you get back to work here, but I really do appreciate you taking the time to spend some time with us here on the Rant Podcast and for sharing your experience and your expertise. Oh no, thank you. This was great. I love it. All right, folks, you've been listening to my conversation with Jamie Smith, the Chief Information Officer at the University of Phoenix. We really appreciate him taking the time out to be here on the Rant Podcast. If you are watching us on YouTube, please hit subscribe. Uh, continue to follow us on YouTube. If you're listening to us on your favorite audio podcast platform, download this episode, hit subscribe and continue to follow us. Thanks for joining us, everybody, and we'll see you again soon.