Right About Now with Ryan Alford - 70% of Workers Feel Unprepared: How Instructure Is Rethinking Learning with Ryan Lufkin

Episode Date: March 24, 2026

New data shows that nearly 70% of workers feel unprepared for today’s workforce, raising bigger questions about how we define job readiness. In this episode, Ryan Alford sits down with Ryan Lufkin of Instructure to unpack what’s actually broken in education and how AI is accelerating the gap between learning and real-world skills. They explore why AI isn’t replacing expertise but instead demands stronger critical thinking, communication, and human judgment. The conversation also challenges whether schools are teaching the wrong things—or simply teaching them the wrong way. From the rise of lifelong learning to the debate between skills and degrees, this episode highlights what both employers and educators need to rethink to prepare the next generation. What We Covered 70% of workers feel unprepared – What’s driving the growing skills gap in today’s workforce AI in education and work – Why AI requires more expertise, not less Skills vs degrees – Are traditional degrees still the best signal for employers? The problem with modern education – Teaching the wrong things vs teaching the wrong way Lifelong learning – Why continuous upskilling is now required for career growth Breaking workplace “boxes” – How AI is empowering employees to operate across roles Connect with the Guest Ryan Lufkin VP of Global Strategy — Instructure (Canvas) Website: https://www.instructure.com LinkedIn: https://www.linkedin.com/in/ryanlufkin Podcast: EduCast3000 Connect with the Host Ryan Alford Host — Right About Now Website RyanIsRight.com Instagram: https://instagram.com/ryanalford LinkedIn: https://linkedin.com/in/ryanalford

Well, why do I need to be chaty? But he's the expert. Someone's got to check its work. It's great at doing research. It's great at being that assistant and accomplishing tasks that can be time consuming. But it's not infallible. We can't trust it to that level yet. Maybe someday, but we still need to be the experts. We can't offload that to the machines. This is right about now with Ryan Alford, a Radcast Network production. We are the number one business show on the planet with over one million downloads a month. taking the BS out of business for over six years and over 400 episodes. You ready to start snapping next and cash in checks? Well, it starts right about now. Hello and welcome to Right About Now. We're always talking about what the world has going on right now

in the world of business, marketing, personal development. We cover the gamut ultimately, but we're here to help you get ahead. Entrepreneurs, executives, everyone out there listening. We know you have choices. Thank you for being here. New data shows that about 70% of U.S. workers feel unprepared for today's workforce. That raises a bigger question. Is the problem education, employers, or how we think about skills altogether?

Today, I'm joined by Ryan Lufkin. The VP of Global Strategy Instructure. He has spent years helping companies and institutions rethink how people actually become job ready. And we're getting into what's broken and what needs to change. Ryan, welcome to right about now. Awesome. Thanks, Ryan. Hey, Ryan and Ryan, you got a good start already, man.

We're like brothers from another. Talk to me, man. Instructure, what that word means. We're the makers of Canvas. Canvas learning management system at this point, about half of all the college students in North America, and about a third of all, K-12 students in North America use Canvas on a daily basis in learning.

We're all about instruction. Instructure is the name of the company. It's funny, you wear a canvas shirt to Home Depot, and people are like, oh, you give me flashbacks to college. You wear an instructor shirt not as many people know. I always like to explain that connection. I did recognize that in our notes. that name, I was twitching a little bit. I'm not sure.

Well, it's funny. You can tell how good their educators were at designing courses in Canvas if they were like, oh, I love Canvas or, oh, I hate Canvas. You're like, the teacher probably wasn't using it right. Yeah. Yes. That's your point of view, I guess. It's probably how literate they were with technology. And a lot of times it's how much support they had in what does a good online course or a good hybrid course look like. I think too often, especially if they learned really rapidly at the beginning of COVID. Our solution grew rapidly because people had to move online over the course of about two days. You can tell the educators that were given a lot of support and a lot of resources and really trained what good looked like. And then the ones that were

kind of thrown into it without that support, our goal really has improved over the last five years of that level of online learning and course design. There's some meta talk there, Ryan, the meta of the fact that the teachers weren't prepared to use the software appropriately. And we're talking about how workers in general feel unprepared. You talk about this pace of change. that started in six years ago, March of 2020, and that pace of James hasn't slowed. Just when everybody thought, oh, COVID's over, we can take a breath. November 30th of 2022, Open AI, launched chat, GPT, and we got everything got turned on its head again. The last period from that have been just an incredibly fast-paced evolution of how do we use

this technology. I have a chart and tell us the seven stages of grief going through all of that. We're really in the acceptance phase with AI now and how are we applying it appropriately? 70% of workers feel unprepared. What does that really mean? You've got this kind of schism between education that in many ways is still really dealing with the academic integrity idea, this idea that AI is just for cheating versus businesses that are trying to figure out how do we optimize our jobs with these tools. And in many cases, don't feel like universities are preparing them for that. It's even worse than K-12 when you look at K-12 and there's a kind of an anti-technology and education movement going on that ignores some of the more glaring benefits of using technology to reach people that have accessibility challenges and rural and frankly, just maybe are missing school, things like that.

We've got to get everybody on the same page, and Google announced a really great program, try to provide free AI education to 6 million educators across the United States. We're getting ready to release some courses around AI literacy and even the detractors, those educators that are scared of AI or have doubled them and said, we're not using AI.

Honestly, take an AI literacy course, at least understand how these tools work, then you understand what they're capable of, and then you can actually make the more informed decision about how deeply do you want to use these tools and put you in a better position to help your self. students understand how to use them ethically, how to use them effectively, things like that.

If we're going to learn something for the sake of learning and for teaching ourselves how to problem solve, are these the problems that we should be solving? Do we need to learn calculus? Do we need to learn things that AI can do? And we'll foreseeably be around unless we all go back to the old ages because power goes away or something or a Wi-Fi goes away. Are we really teaching what we should be teaching in? Why do we still need to learn the things we learned 30 years ago? I will point to what was called the strawberry conundrum. Chachy-B-T 3.2. If you ask it how many R's were in the word strawberry, it would tell you two. And you'd say, go back and maybe look that again and tell me how many are there.

And it would say, there are two R's and strawberry. Of course, there's three R's in strawberry. And they could not figure out, because essentially large language models are a black box. You don't know what's going on inside there. They could not figure out why it hung up on that. And it wasn't until the next model, 3.3 came out. They fixed that. That's the reason that we all need to be experts.

Chachybtee has a high propensity for what we would call hallucinating. more often it's confidently incorrect. What it's trying to do is give you what you've asked it for. Some cases, it makes things up. It'll make up links, sources. It'll make up whole sets of information because it's just trying to give you what you want. And if it doesn't find it or if it doesn't spend the time to find it, it just kind of makes it up. We don't know exactly why.

But when we are the experts, we can double check that work and say, oh, you know what? That's not right. Let's go back and fix it. Let's not perpetuate that strawberry conundrum. What's really scary is that next generation that takes that approach that you're talking. talking about and says, well, why do I need to be Chagip? He's the expert. Someone's got to check its work. It's great at doing research. It's great at being that assistant and accomplishing tasks that can be time consuming, but it's not infallible. We can't trust it to that level yet.

Maybe someday, but we still need to be the experts. We can't offload that to the machines.