Deep Dive: AI's Growing Role in Higher Education

Mark Putnam

This episode examines the role of AI in higher education—what’s useful, what’s overhyped, and where universities should actually invest. With AI adoption accelerating, institutions face a challenging question - how to consider and make the right AI investments for their institution. We break down the differences between everyday AI and game-changing AI, and discuss strategies that balance innovation with financial sustainability. Tune in to cut through the hype and discover how AI can truly transform higher ed—without unnecessary risks.

Olivia

Good afternoon, Mark. Let's dive into it. AI is kind of everywhere in higher ed right now, and I feel like there’s this pressure—almost like a hype machine—pushing universities to aggressively adopt it. But, let’s be real, not every AI tool out there is actually, you know, worth it. Right?

Mark Putnam

Exactly. I think that’s the crux of the issue. Universities are being inundated with AI solutions—some of which are incredibly useful, others… not so much. Separating the signal from the noise is essential here.

Olivia

Okay, so how do they even begin to figure that out? Like, what’s the framework here?

Mark Putnam

That’s a great question. Broadly speaking, there are two categories that I think are key to understand: everyday AI and game-changing AI. Everyday AI is—well, as the name suggests—solutions that improve efficiency and workflows, things like chatbots or AI writing assistants. They’re low-cost, easy to implement, and frankly, they’re becoming pretty ubiquitous.

Olivia

And then there’s the big-league stuff, right? Like, the things that actually could, I don’t know, fundamentally transform how universities operate?

Mark Putnam

Precisely. Game-changing AI demands significant investment—financially and strategically. We’re talking about things like AI-powered research labs, predictive analytics, or even overhauling student systems and learning management platforms with deeply integrated AI capabilities.

Olivia

But that sounds… difficult. Expensive, too, honestly.

Mark Putnam

It is. And for institutions to decide where to invest, they need to be clear about the potential value. Everyday AI won’t revolutionize a university, but it can save time and resources. Game-changing AI, on the other hand, has transformative potential—if it’s executed strategically. It's not just about jumping on the AI bandwagon to keep up with trends.

Olivia

Right. It’s like, if you don’t have a plan, you’re just throwing money into a black hole. But I’m guessing this is easier said than done?

Mark Putnam

That’s absolutely correct. This is where leadership plays a critical role—having a clear vision for where AI aligns with the institution’s strategic goals. Without that, even the best technology can end up being wasted.

Olivia

And universities are often working with limited budgets, so wasting resources on, I don’t know, flashy but ultimately pointless tech, would hurt even more. Hmm. So—for now—it sounds like a more cautious, balanced approach is the way to go.

Mark Putnam

Exactly. Think of it as maximizing the quick wins with everyday AI, while making a few high-impact bets on game-changing technologies where real competitive advantages lie.

Olivia

Okay. I see where you’re going with this—and, wow—there’s already a lot that universities are navigating. Hold on, I want to dig into this idea of “quick wins” more. Like, what does that look like for students specifically?

Olivia

Okay, so when we’re talking about “quick wins” with everyday AI, what are some examples of what universities are already using right now?

Mark Putnam

That’s a great place to begin. For students, some of the most impactful tools include AI-powered custom chatbots, generative note summarization, and content creation tools. Services like ChatGPT or Google Gemini are already helping students understand coursework more effectively. At the University of Georgia, we are seeing explosive development of custom ChatGPT bots by faculty to provide specialized tutoring for students.

Olivia

Wait, so instead of, I don’t know, falling asleep in a lecture, students can get personalized study guides? That’s insane.

Mark Putnam

Precisely. It gives students on-demand assistance, so they don’t have to rely solely on office hours or peer notes. And the best part? These tools often integrate seamlessly into existing systems without requiring universities to invest heavily in custom solutions. And they are incredibly inexpensive.

Olivia

Okay, but what about faculty and staff? They’re the ones, you know, behind the scenes making things happen—right?

Mark Putnam

Exactly. Everyday AI is incredibly effective here, too. Take something like Grammarly or Microsoft Copilot—both are AI-assisted writing tools that streamline tasks like drafting emails or editing documents. Then you’ve got platforms like Otter.ai for meeting transcription or AI-supported email sorting, which can save faculty hours every week.

Olivia

Got it. So basically, we’re talking about freeing up time for all those *other* headaches higher ed professionals juggle. Makes sense.

Mark Putnam

Right. And this extends to operational functions as well. Many enterprise tools—think Microsoft, Oracle, Workday—now have built-in AI features for scheduling, automating workflows, and providing basic analytics. Universities don’t need to build these capabilities themselves.

Olivia

Oh, so it’s like taking off-the-shelf AI instead of reinventing the wheel.

Mark Putnam

Exactly. This is where everyday AI shines. It’s low-cost, easy to adopt, and delivers immediate efficiency gains. But—and this is key—it’s not going to fundamentally transform how universities operate. It’s a tool for optimization, not revolution.

Olivia

Right, so we’re in, like, the “baby steps” phase of AI adoption.

Mark Putnam

In a way, yes. Using everyday AI is like smoothing the workflows we’ve already got—it’s efficient, but it’s not rewriting the playbook.

Olivia

Hmm. It feels like a no-brainer to adopt these, though. If the tools are affordable and they save time, why *wouldn’t* a university jump on board?

Mark Putnam

Well, that’s an excellent question. For the most part, institutions are embracing these tools. The challenge comes in making them part of a cohesive strategy. Adopting AI piecemeal without a plan can lead to fragmented systems—or tools that no one’s actually using effectively.

Olivia

Ugh, yeah, unorganized tech adoption. Been there. Alright, so we’ve covered students, faculty, and, you know, operations. What’s next?

Olivia

Alright, so we’ve talked about students, faculty, and everyday tools, but what happens when we move beyond the basics? This is where the game-changing AI comes in, right? And, honestly, this stuff feels a lot riskier—we’re talking more than just tutoring bots or automated emails now. This is the big stuff.

Mark Putnam

Exactly. Game-changing AI is a completely different ballgame. Universities are looking at tools that can fundamentally transform their operations or research capabilities at scale. But, as you said, it’s risky—it requires significant investment and long-term commitment.

Olivia

Okay, like, what kind of tools are we talking about here?

Mark Putnam

Well, for starters, think about high-performance computing—or HPC—that’s being used in research labs. Faculty need access to GPU clusters for things like AI-driven simulations in medicine, physics, or even social sciences. It’s cutting-edge work, but the infrastructure alone can cost millions.

Olivia

Yikes. So, this isn’t exactly something you can slap on a credit card and call it a day.

Mark Putnam

Not at all. These investments require institutional backing, often in partnership with industry or through government grants. And beyond research, there are institutional tools like AI-driven Learning Management Systems or predictive analytics for student success. These have the potential to really elevate how universities operate.

Olivia

Wait—a predictive tool that identifies at-risk students before they actually fall behind? That’s wild.

Mark Putnam

It is. It’s using algorithms to analyze data, like attendance, grades, and even behavioral patterns, to flag students who might be struggling. But implementing these systems comes with its own set of challenges.

Olivia

Challenges like… what? Data privacy? Ethical concerns?

Mark Putnam

Exactly. First, there’s the financial challenge—these systems aren’t cheap. Then you’ve got governance issues. Who controls the data? How is it used? And let’s not forget accuracy. Misinterpreting the data could lead to unfair outcomes.

Olivia

Right, like imagine labelling a student as “at risk” when they’re not. That could spiral pretty quickly.

Mark Putnam

Absolutely. And this is why universities need to be strategic. Game-changing AI isn’t about chasing the latest trend. It’s about identifying where the institution can truly differentiate itself—whether that’s through cutting-edge research tools, personalized student services, or smarter resource allocation.

Olivia

But if it's so… high-risk, why even bother? Why not just stick to the basics?

Mark Putnam

That’s a valid question. The payoff can be immense. For universities aiming to position themselves as leaders in innovation or research, game-changing AI offers a huge competitive edge.

Olivia

Okay, so it’s like, no one’s forcing you, but if you want to stand out, you kinda have to take the leap?

Mark Putnam

Precisely. It’s not something to dive into lightly, though. Institutions need to evaluate where these investments align with their long-term strategies and whether the risks are manageable.

Olivia

Right. Otherwise, they’re just buying shiny tech for the sake of optics—like a slogan instead of actual change. Let’s dive deeper into the basics next. Everyday AI sounds pretty doable compared to this.

Olivia

So, earlier we were talking about taking those big leaps with game-changing AI, but it got me wondering—how do universities even figure out where to begin? Like, what’s the first step to make all of this more than just an ambitious idea?

Mark Putnam

The first move, really, is about prioritizing efficiency. Everyday AI is the low-hanging fruit—it’s affordable, scalable, and builds momentum. These tools can optimize workflows for students, faculty, and staff without requiring major overhauls.

Olivia

Right, so it’s like, tackle what’s easiest and get some wins on the board first.

Mark Putnam

Exactly. It’s about delivering measurable results quickly. Once those efficiencies are in place, an institution can start thinking about more ambitious investments—where game-changing AI can truly differentiate their operations or research capabilities.

Olivia

But what makes something, I don’t know, worth the risk? Like, how does a school even figure out if game-changing AI is worth going for?

Mark Putnam

That’s where strategic alignment comes in. The question isn’t just, “What’s cutting-edge?” It’s more about identifying opportunities where AI gives the institution a clear advantage—whether it’s in research, student learning outcomes, or even predictive analytics.

Olivia

Ah, so it’s not about just chasing conference presentations—more like solving a problem really well.

Mark Putnam

Exactly. And here’s the thing—universities don’t have to reinvent the wheel to get there. They should focus on partnerships with vendors like OpenAI, Microsoft or Google. These companies are embedding powerful AI capabilities into their platforms already. Why spend years developing something custom when there’s a solution ready to deploy?

Olivia

That makes sense. But I’m guessing it’s tempting for some tech teams to want to build everything themselves, right?

Mark Putnam

It can be. But building custom AI from scratch is expensive and time-consuming—not to mention the long-term costs for maintenance and upgrades. Low-code and no-code platforms, like Microsoft’s Copilot Studio, make it easier to deploy AI without needing an army of developers on staff.

Olivia

Huh. So instead of writing code, they just, what, drag and drop workflows? Like building a playlist?

Mark Putnam

Exactly. And it aligns well with the broader goal: use technology to solve real problems in a sustainable way. Technology should empower staff and students—not overwhelm them.

Olivia

Okay, that feels refreshingly practical. Honestly, I wish more conversations about AI were this grounded instead of all the heavy-handed “disruption” talk.

Mark Putnam

Well, at the end of the day, it’s not about chasing disruption. It’s about being intentional—maximizing everyday AI for efficiency, while investing selectively in game-changing AI where it truly moves the needle.

Olivia

I like that. It’s like asking AI to work smarter, not harder. And I think that’s a wrap for today!

Mark Putnam

Absolutely, Liv. Thoughtful adoption, and not just trend-chasing, is the way forward for higher education. Great chat, as always.

Olivia

Agreed! And with that, thanks for listening, everyone. We’ll see you next time on Dispatches from an Internet Pioneer!