Closing the Gap Between Curiosity and ROI: AI Training Series

Stephanie Hubka, founder of Protos Learning, who has spent 20 years designing human-centered learning strategies and has trained leaders in 50+ countries, is working with ACT-IAC on the business value of AI training for non-technical leaders. Hubka argues organizations often treat AI as either a magic fix or an existential threat, when it is better understood as a capability amplifier that requires humans in the loop. She emphasizes anchoring AI training to real work and quick wins, using everyday language instead of jargon, and building data literacy without turning everyone into analysts. Successful adoption depends on psychological safety, experimentation, and trust, with learning teams acting as strategic partners who understand the business. She shares how ChatGPT quickly drafted an outline but failed to create a quality, human training experience, reinforcing that transformation is ultimately about people. Stephanie's passion for training is equaled only by her love of exploring the globe; an avid traveler, she has visited all 7 continents, 70 countries, and all 50 US states.

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Intro/Outro Music: See a Brighter Day/Gloria Tells
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Transcript

Yohanna: [00:00:00] Welcome back to the Buzz. Today's conversation is for anyone who's ever heard the words AI transformation in a meeting and quietly thought, okay, but what does that actually mean for my team tomorrow? Because right now AI is everywhere in strategy, decks, headlines, budget, conversations. But for a lot of organizations, the gap between excitement and execution is.

Yohanna: Still pretty wide. That's where learning comes in. Our guest today has spent more than two decades helping leaders and teams close that gap, designing learning and performance strategies that don't just teach new tools, but actually change how people work. They're the founder of Protos Learning. They've trained leaders in more than 50 countries and recently partnered with ACT IAC to lead the business value of AI training, helping non-technical leaders understand how to move from curiosity about AI to real world, uh, impact and ROI.

Yohanna: So today we're talking about what organizations get wrong about ai, how learning [00:01:00] teams can become strategic drivers of change, and what practical steps you can take right now to prepare your workforce for what's next. 

STEPHANIE HUBKA: Hello, I have Stephanie, um, on the bus. How are you feeling? Stephanie, 

Yohanna: please introduce yourself.

Yohanna: Uh, tell our listeners who you are, where you're from, a little bit about, about your background. 

STEPHANIE HUBKA: Of course. Yeah. So my name is Stephanie Huka and gosh, where I'm from. So I live in the Washington DC area these days on the Virginia side. For those of you who are familiar, I actually was, I was born on the west coast.

STEPHANIE HUBKA: I was mostly raised on the east coast, grew up in Boston, went to college in Pittsburgh, and then found my way to DC right after graduation. And. I have been working in talent development really from the day I first got to DC I took a temp job downtown. The goal was really just to make a little bit of money while I figured out what I really wanted to do, and I was lucky.

STEPHANIE HUBKA: I figured out what I wanted to do [00:02:00] from that temp job. And what I wanted to do was what they hired me to do. So for the last 20 years, I have been designing develop. And sharing learning experiences with people all over the world. I do a lot of travel. I really love getting a chance to connect with people, uh, get to know who they are and make sure that I'm developing learning experiences that resonate with them, that are exciting for them, and where they can have a little bit of fun too.

Yohanna: That's great. Yeah. Welcome. Welcome to the buzz. Thank you so much. Thank you. Though, like I mentioned, you spent two decades building, learning and performance strategies. How did your, uh, early career shape, the way that you approached learning in the era of ai? 

STEPHANIE HUBKA: I love this question. Let's go all the way back to the beginning.

STEPHANIE HUBKA: Back when. AI really wasn't part of the conversation. So when I first got out of college, I moved to the DC area. In fact, uh, when I, I first came here, the goal was not to work in talent development at all. I had a political science [00:03:00] degree and the plan was to work on the hill. Something would happen. And then when I turned 35, I'd run for president.

STEPHANIE HUBKA: Obviously win. And you know. Change the world. As it turns out, that would not be the job for me. Training ended up being a much better fit and one of the things that I experienced in the beginning, now I, I can't tell you that this is how I really understood it, but looking back at what training was when I was first getting into it, it had a couple of characteristics.

STEPHANIE HUBKA: It was boring. It was tedious to build and it was really complex to manage. Uh, it was really, in a lot of cases, designed for a kind of a checkbox. It was sort of a checkbox that either the learner would get to check off saying, yes, I did this and now I can do my job. Or that a company would say, you know.

STEPHANIE HUBKA: Check this box and now you can do your job. And it was typically far more focused on things like learning outcomes or knowledge transfer than it ever was about the humans that are involved on [00:04:00] both sides. And what that did over time was really lead me to recognize that learning will fail when humans are not at the forefront of training from the very beginning.

STEPHANIE HUBKA: So. Thinking about AI all these years later and where that fits in, we have the opportunity to speed up and streamline huge parts of the learning, design and development process. And what that really does for us is it gives us more time and flexibility to ensure that people are the most part, important part of the process.

STEPHANIE HUBKA: We can save more space to learn about our learners, to connect with them, and also to assess the kinds of learning experiences we're offering. From the lens of how the people might experience them and how they are included at every step of the way. It is so much more now about humans than I think it ever was when my career first started.

Yohanna: So humans in the loop still very much. 

STEPHANIE HUBKA: Completely, completely. 

Yohanna: So that's [00:05:00] solid that that foundation clearly shaped how you see learning today. 

STEPHANIE HUBKA: Very much 

Yohanna: so. Then what was, what motivated you to found produce learning, and how has your vision for training evolved since then? 

STEPHANIE HUBKA: Yeah, well, produce learning was really a natural evolution for me.

STEPHANIE HUBKA: So as I mentioned, I first moved to the DC area. Actually the, the job that I first took in talent development was attempt. Job, I mean, I was really thinking I'd end up on the hill at some point in time. I ended up spending about a decade working primarily with nonprofits here in the DC area, and really during that time after recognizing that training was often kind of boring and usually not very human focused.

STEPHANIE HUBKA: I knew that there was one thing that felt very universally true, and that is learning should be fun. So I spent, uh, really more than a decade having fun and contributing to fun wherever I best could at various organizations. But the challenge there for me was I was usually very much in the lane I was hired to be [00:06:00] in.

STEPHANIE HUBKA: So a lot of my career was spent in e-learning development. I wasn't hired to do, say, needs. Or evaluations. I wasn't always hired to design training. Sometimes it was just to develop it. So you know when you realize that you're kind of being kept in your lane, but you wanna grow past that lane sometimes you have to realize that if you wanna have all the fun, you kind of have to make up all the rules.

STEPHANIE HUBKA: And so self-employment became a really, really good fit for me. But at the end of the day, I think my vision for training has actually stayed pretty consistent over the years. I still think that learning should be fun, but I now understand a lot more about what that means and about why it works. And it kind of led me to my own personal mission statement, which is that learning is human at its core, and it's anchored by experiences that celebrate joy, curiosity and genuine connection.

STEPHANIE HUBKA: And that's really what produce learning focuses on. We are really kind of. Focused on creating experiences where [00:07:00] people can get curious, they can have fun, and they can really connect with others, with facilitators, with content that they're learning and also with themselves. 

Yohanna: Yeah. And since then, your work hasn't just stayed local, so you're not just in the DC DMV area.

STEPHANIE HUBKA: That's right. 

Yohanna: You've taken this thinking around the world. 

STEPHANIE HUBKA: Yeah. 

Yohanna: From your global experience training leaders in 50 plus countries, what's a universal truth about learning that? Still holds, holds, but you know, despite cultural differences. 

STEPHANIE HUBKA: I think the one thing that really holds true is people want what's best, not just for them, but for others.

STEPHANIE HUBKA: I think a lot of times you feel like people are really looking out for themselves, not necessary for necessarily for their colleagues or for their teams. People really tend to be motivated by kindness and helping others far more than they are motivated by a desire to get ahead or to be better than someone else, regardless of culture.

STEPHANIE HUBKA: People genuinely wanna be part of communities, and they want those communities to succeed and to thrive and to [00:08:00] support every single member. I've seen that play out in every single organization in every single country that I've had the opportunity to work with. I can't say it surprises me anymore because I now expect to see that kindness, but it really makes me smile every single time.

STEPHANIE HUBKA: People really do wanna be in it together with their colleagues. 

Yohanna: Oh, that's really nice. That's really good to hear. 

STEPHANIE HUBKA: Yeah. 

Yohanna: Um, so with that kind global lens on how people learn, let's zoom in on AI because that's where so many organizations are both excited and overwhelmed. In your, uh, in your business value of AI training for ACT iac, what's the biggest misconception about ai you aim to dispel?

STEPHANIE HUBKA: Yeah. Another really good question. I think right now the biggest misconception that we're seeing whenever we're talking about AI is that it's either going to be a magic solution or an existential threat. It's one of the two. There is no middle ground except for one thing [00:09:00] there. Is a middle ground, and I think AI is actually a really good capability amplifier, if you were to give it that kind of a term.

STEPHANIE HUBKA: AI doesn't replace our capabilities, you know, things like judgment or creativity or empathy, any of those. Those capabilities that we bring to work, it actually makes those very important qualities more scalable when humans stay in the loop and as we get there, as people stop asking things like, what can AI do for me?

STEPHANIE HUBKA: The goal really is to get them to the point where they can say, what should humans be doing better? Because AI exists, how are we able to amplify those capabilities without going to one extreme or the other? 

Yohanna: I like that. I'm, I'm a big fan of, it's like it is like this big ga Anyways, it is. I'll go off on it.

Yohanna: Yeah, 

STEPHANIE HUBKA: no, it is, and in fact, I'll actually give you an example. This is something I've been thinking about a lot lately. 

Yohanna: Okay. 

STEPHANIE HUBKA: There's this poem. I kid you not, this is a poem that I read not too long ago. Um, the. The [00:10:00] person who wrote its name is Joseph Fasano. I think I said that correctly. Uh, it, it's a very short poem.

STEPHANIE HUBKA: I'm not gonna read it to you. Uh, but it's called to a student who used AI to write a paper. I had to laugh when I saw the title because I mean, how many of us have not at least tried to get AI to do our homework for us in some way? So of course, it is written to a student who is using AI to take the easy way out.

STEPHANIE HUBKA: There is one quote though that comes to mind every time I think about this. This challenge that we're facing here. This is the quote, but what are you trying to be free of? The living, the miraculous task of it all. And the reason I absolutely love that imagery is because a lot of us are very quick to shrug off the hard work that challenges us because AI can make it easier.

STEPHANIE HUBKA: I think the real challenge we're facing right now is to maintain our commitment to still embrace the work. It is not about letting AI. Give us that chance to take the easy way out. It is really about AI supporting us as we continue to embrace our curiosity [00:11:00] and we tackle the work that we do that is really so worth doing.

Yohanna: Oh yeah, absolutely. I, I'm so happy that you're challenging and you're tackling all these misconceptions. 'cause like, the next challenge is like, action, you know, how do you help leaders actually move from interesting to implementing? Absolutely. Right. How do you help the non-technical business leaders shift from, you know, AI curiosity to practical application and ROI Like what, what is it that you're, you're doing when, when you know, in your, in your training.

STEPHANIE HUBKA: Yeah, yeah. Um, I think. So really I'm a storyteller, so I start with stories. I really think when it comes to leaders, leaders don't need to simply understand how AI works. They really need to see themselves in the outcome. So it's not about AI happening to them, it's really about them being part of the story of how AI is implemented in the beginning.

STEPHANIE HUBKA: So. When it comes to my approach for AI training, um, especially for non-technical [00:12:00] leaders, it's really to anchor AI to real work. So things like emails that they might be writing, decisions they're making, personal favorite bottlenecks that they feel, we all know what it's like to have a bottleneck we wish we could get out of.

STEPHANIE HUBKA: Well, what happens if AI could be a solution? When we're thinking about some of these real life daily challenges we experience. So once leaders experience a productivity win personally. Even just a small win. I think the conversation really does start to shift from curiosity to things that are more like investment and accountability.

STEPHANIE HUBKA: So it becomes a little bit more real world, a little bit more achievable and people see themselves in what's happening. 

Yohanna: Yeah. I like that, that that's that. Oh, oh, that, is that what you've been talking about, like when that moment clicks? 

STEPHANIE HUBKA: Yes. And 

Yohanna: so what are a few of your favorite high impact real world AI case studies that you, that you can share in, you know, in this training?

STEPHANIE HUBKA: Yeah, so the training, we actually have a handful of trainings that are coming up over the course of the next year. Um, [00:13:00] so I'm partnering with a phenomenal group. Uh, the Contract Administration Network, international, LLC, can, um, we have been working on a series of different topics that we're gonna present, so.

STEPHANIE HUBKA: Thinking ahead to the handful that I'm gonna be working on. I am sort of co-facilitating with the amazing Melvin Brown, who I hope a lot of you know of. He is absolutely brilliant and incredibly inspiring. Um, when I'm thinking about the, the types of, um, real world, you know, case studies, I guess. I really prefer to gravitate a little bit more toward quick wins as opposed to say like the flashy stories.

STEPHANIE HUBKA: Flashy stories have their place, but I don't know if they have enough of a place in the work that a lot of us are doing. Most of us live in a space where quick wins make sense. So I'm talking about things like managers who are reclaiming time by using AI to prepare for meetings. I'm thinking about colleagues, uh, people who work with knowledge, especially reducing things like [00:14:00] cognitive overload by using AI as a brainstorming partner.

STEPHANIE HUBKA: I do that all the time. I'm also thinking about teams, so teams that might be moving from ideation to actual progress in less than half the time by assigning some of their more repetitive and time intensive tasks to ai. I love case studies like this because. I really think that they resonate better. Um, they're more human, they're more repeatable, and I find for a lot of us, they're also gonna be more immediately relatable as far as, can I take what I just heard in this example and move this into my day-to-day?

Yohanna: Even with these great examples, I think sometimes like internal buy-in can get, can be kind of difficult. Like what's, what's the most common barrier? Organizations and teams face when trying to communicate AI's value internally. Like what is it? Yeah, that stops, stops us. 

STEPHANIE HUBKA: There are, there are so many barriers.

STEPHANIE HUBKA: I think one of them that I see and I'm, I'm thinking really from some of my more current [00:15:00] experiences. We are getting really good at talking about AI as an abstract, when we really should be focused on more concrete experiences at work. One of the issues we have, we don't. Really connect. You know, if you're thinking about all, all of us as team members, we don't connect to jargon like efficiency gains or digital transformation or you know, all of these phrases we are using to describe what AI can do for us.

STEPHANIE HUBKA: Those words don't always make a lot of sense to us. Contextually, we connect more to things like, you don't have to do as much editing or rework. On your current project that aligns for me. That absolutely is something I wanna hear. I wanna hear things like you're gonna spend more meaningful time making actual progress on your work.

STEPHANIE HUBKA: That tells me something. Efficiency gains. Yeah. I can sort of figure out what you mean by that. But when you tell me I'm gonna spend less time doing more important work, I wanna hear that. So I think really. Until we're [00:16:00] framing AI in the language of everyday work, the stuff we use when we're talking to each other, I think adoption is gonna stay kind of at that superficial level, or it's gonna lead us to not really understand quite what the impact AI can have on our work would be.

Yohanna: Yeah, and that makes me think about how. You know, the bigger picture isn't just productivity tools, but it's how organizations can learn as a system. How do you think ai, how do you think learning and training teams, um, become strategic partners in shaping an organization in, you know, within their AI journey?

STEPHANIE HUBKA: Oh, this is a huge question right now, and there's a lot of conversation happening around it. When we're thinking about learning professionals, talent, talent development practitioners, for example, one of the big things that they really need to know is. How they can understand the businesses that they work for.

STEPHANIE HUBKA: Yeah. Talent development is a really interesting space to work in. So any of my [00:17:00] learning leaders out there who work in this field, you're probably gonna know exactly what I'm gonna say. We tend to sit kind of at an intersection of sorts between things like knowledge, skill development. The culture of an organization.

STEPHANIE HUBKA: Um, talent development often is found right there. Behavior change, that's something else we're usually looking for. You know, training really isn't just about are we learning something new? It's, are we changing our behavior on the job? So we're talking about people who sit in a spot where they have a really clear vantage point, and from that vantage point they can see into a lot of what works well and what doesn't work well in the companies that they're working within For.

STEPHANIE HUBKA: But one thing I know is, is that a lot of people don't necessarily understand the business itself. So I think success in this space really comes back to one word that you actually used early on, um, when asking this question actually, which is about partnership l and d teams. Really know how to do their work well, you know, we know our space, we know our lane.

STEPHANIE HUBKA: [00:18:00] We're really good at it. But rather than focusing only on our work, which sometimes transforms into taking orders, you know, Hey, I need a course, I need a training experience. Can you do it for me? I think it's much more now about. Getting to know the business itself and seeking to be the kind of strategic partners that a business really needs.

STEPHANIE HUBKA: When you understand the business, you can speak the language, you can make those connections into what a great productive learning experience will be. That advances a business's goals and outcomes, that's where you're gonna start to see more magic happening. 

Yohanna: Yeah, and if learning teams are stepping into that strategic role.

Yohanna: The way that you develop talent probably has to change too. So with AI changing the nature of work, how should talent development teams rethink learning pathways? Like what's, what's that new way of, of doing things? 

STEPHANIE HUBKA: Yeah, that's a really good question. I love using learning pathways in training, but one thing I'm seeing right now.

STEPHANIE HUBKA: Think that linear pathways work as well as they once did. Learning [00:19:00] tends to really be at its best when it's continuous, you know, when it's not a one-off experience that you might take and then forget later on. You really need it to be connected into the context of the business and the context of your work, and you really have to have that clear connection between what people learn and how it's gonna make them better at their job.

STEPHANIE HUBKA: There's a, a question that a lot of us. Well think about when we're designing training on the learner side, which is what's in it for me. If you're a learner and you're sitting down to take a training, you wanna think about that. You know, well, why am I here? Why is this worth my time? What am I gonna get from that?

STEPHANIE HUBKA: And I really think that a lot of this focuses in on keeping that question in mind. And I think as far as AI goes, AI can actually offer quite a bit of help to us here. Um, it really can help us to design and implement personal. Learning experiences, things that are more personalized for the learner. I think it also gives us a little more space for things like just in time support.

STEPHANIE HUBKA: And that's gonna pull us away from the stuff that [00:20:00] I don't think we really love either developing or taking these one size fits all trainings. A lot of us have been, you know, kind of stuck in those in the past. It's, you know, if you're designing for everyone, you're kind of designing for no one. I think we can start to move away from some of that by allowing AI into that space where we can understand personal personalization a little bit better.

STEPHANIE HUBKA: And I think from there we really have a much better opportunity to help people build the kind of connection that we're really looking for so that they get why they're in the A training, they see how it's gonna help them, and they're excited to use what they learn and improve their performance and, you know, make things a little bit easier on themselves when they get back to work.

Yohanna: Yeah, and this is, and this is a, a lot of information. I think like a big part of that shift is 

STEPHANIE HUBKA: Oh yeah. 

Yohanna: Being comfortable with just data and something. 

STEPHANIE HUBKA: Mm. 

Yohanna: And I think sometimes, maybe this is me, but I think a lot of folks still feel intimidated by, by just data. You know, like, 

STEPHANIE HUBKA: oh, they do. 

Yohanna: You know, like [00:21:00] what do you think the role of data literacy and your training frameworks and how.

Yohanna: How do you build it among learners? 

STEPHANIE HUBKA: Yeah. You know, data, it it, it's a really important topic for all of us, especially those of us who happen to work in any part of the learning space. When it comes to data literacy, it's really about knowing where to find and how to use data. I think especially if you're talking about say, key business tasks, like solving problems, making informed decisions, anything like that, those are the spaces where you really are gonna wanna make sure that you have.

STEPHANIE HUBKA: Solid, understandable data. So for anybody who's working in talent development, I think data literacy is very much a non-negotiable skill. It really, it's, it's because decisions really do require data and we need to be able to know how to find it. We've gotta be able to validate it. We gotta make sure that it's accurate and then we have to be able to use it.

STEPHANIE HUBKA: So when I'm working with talent development practitioners, I typically focus on helping learners understand what data can [00:22:00] and can't tell them. And I also often remind people that that means that there may be bias in your data. You may not have good clean data right up front. You may have to understand where bias might insert itself so that you can get to that point that you're using good data.

STEPHANIE HUBKA: And to be honest. The goal really isn't to turn everybody into a data analyst. We love talking about data these days, and I think for a lot of people they think, I don't know if I'm a data person, you don't have to be one. It's okay. You don't have to, you know, decide that that's who you're going to be at work.

STEPHANIE HUBKA: But I think it is much more about the confidence that comes with that skillset. You want people to be able to review data so that they know what data is really telling them and how that data can be used fairly. 

Yohanna: So even if the skills are there, change isn't just a technical thing, it's an emotional thing.

Yohanna: It's a cultural thing. Organizational change around AI isn't just technical. Um, what tips do you give for leading that human side of change? 

STEPHANIE HUBKA: Yeah. I'm really glad that you. Mention this, and I think [00:23:00] you're absolutely right because we often approach it as being just technical and it's not, it's cultural as well.

STEPHANIE HUBKA: One of the things that I'm seeing organizations start to do, and I think it really does set these organizations apart when they start doing them, is normalizing discomfort and rewarding the team for experimenting a bit with ai. This gets into a little bit of a challenging. Space for some people because you really do need psychological safety on your team and in your workplace in order to feel like that discomfort is okay to experience and that you can experiment.

STEPHANIE HUBKA: Because with experimentation, sometimes you succeed and sometimes you do something that no one wants to talk about, which is to fail. Failure, great tool when it comes to learning. But of course a lot of us have been told it's not something you're pursuing at the workplace. Maybe you're not pursuing it. I think that'd be fair to say, but if it happens to you, it's actually a great learning opportunity.

STEPHANIE HUBKA: So we really do [00:24:00] need that psychological safety from people. I think you really do need leaders who are willing to say things like, I don't know, or, I haven't tried that. Or Why don't we all try that together? What that does. It brings in the element of curiosity that a lot of teams really thrive on when they happen to have it.

STEPHANIE HUBKA: You get an opportunity to make mistakes. You can see what happens when you make those mistakes. You learn from them. Maybe next time you make a different one, maybe you don't make any at all. But it really sets the stage for teams to start to talk openly about how they're using ai, how they're learning to use ai, and that's where you start to see the cultural shift.

STEPHANIE HUBKA: You start to see where. AI adoption isn't really threatening anymore. It's not really about what is AI taking from us. It starts to be more empowering. It's more about what is AI offering us? What can I do better or differently or more of now that I have AI as a tool to support me? 

Yohanna: Yeah. And also I [00:25:00] think the pace of innovation is wild right now.

STEPHANIE HUBKA: Mm. 

Yohanna: So, 

STEPHANIE HUBKA: oh, isn't 

Yohanna: it? Yeah. I think, um, 

STEPHANIE HUBKA: yeah, it's, 

Yohanna: you know, like what emerging AI tools or capabilities are on your radar as game changers for learning professionals? Yeah. 

STEPHANIE HUBKA: Oh yeah. Well, I think as far as capabilities go, I would say first and foremost, AI at this moment anyway, is probably best positioned for us as a brainstorming partner rather than a content generator.

STEPHANIE HUBKA: Can AI generate content? Of course it can. But is AI going to generate content that you can use? Maybe not now. I have seen a few examples where AI has produced what seems to be fairly, you know, it's correct. It makes sense, but it doesn't really have a whole lot of soul to it. Yeah. You know, there's no human touch.

STEPHANIE HUBKA: AI is not doing that for us right now. So if you're thinking about what AI can look like and how you might be able to use it as a learning [00:26:00] professional, start with brainstorming. But if you are looking for tools, um, one of the ones I'm using quite a bit now and really love, um, notebook, lm, I think a lot of people might have heard of it.

STEPHANIE HUBKA: Okay. And if you haven't heard of it. You'll probably start hearing more about it. It's one of the tools I heard about, ah, gosh, maybe six months ago or so, and then started hearing more and more. Finally, I decided to go see what it was about. Um, it's actually a really good research tool. Um, I think it's also a pretty decent thinking partner as well, but you can upload a number of sources, uh, to it.

STEPHANIE HUBKA: It's gonna review those, analyze them. I like it because it tends to take some of these more complex and tedious tasks like, you know. Coming up with a review and summarizing tons and tons of data, it's faster, it's more organized. It frees me up to do the human work of starting to figure out how I might be able to develop training that connects with people as opposed to just, you know, sharing knowledge or information.

Yohanna: I haven't heard of that one. I've, I like all of the note taking ones that pop up in the Zoom meeting. [00:27:00] Like the, and you're like, Otter. Who's Otter? Who's like, and there was like a new 

STEPHANIE HUBKA: one 

Yohanna: called Otter. Yeah. I'm like, what? Who's Otter? 

STEPHANIE HUBKA: My favorite are the organizations that deploy those. Nobody names them necessarily.

STEPHANIE HUBKA: So the meeting starts and you've got 20 otters joining. Yeah. Like, I'm gonna need yet to identify your otters. Like all of you need to tell me who's otters who. And do we need 'em all together? There are more otters than there are us, so 

Yohanna: Probably not. Probably not. Yeah. But I Notebook sounds really cool.

STEPHANIE HUBKA: That's a good one. 

Yohanna: Yeah. All right, so for teams listening who might be thinking, this sounds great, but where do we start? What's one practical step teams can take this week to make their AI initiatives more successful? 

STEPHANIE HUBKA: I would say don't start as big as you think you should or as big as you want to start small.

STEPHANIE HUBKA: This is a journey. This is not a sprint that you need to get right, right now. Pick one real task that you're working on and use that opportunity to perhaps redesign it [00:28:00] with ai. Then have a moment to measure the difference between what it was like to do that task with ai and without ai. I like this approach because.

STEPHANIE HUBKA: I think if you were to take an entire training program, for example, and try to redesign it with ai, that's overwhelming. That's a lot. I think for a lot of us redesigning a PowerPoint deck with AI is a lot. Think about one small task that you have on your plate where AI might be able to help spend some time identifying the tool that's gonna help you spend some time actually deploying that solution and spend some real reflection time on why that worked or didn't work for you.

STEPHANIE HUBKA: What you do differently, would you try a different tool next time? All of these are going to lead you to the kind of data we were actually just talking about. This is gonna help you to figure out whether or not you are using tools that are efficient. Are you more efficient than the ai? By the way, that's gonna happen quite a bit, so it's gonna help you to figure out whether or not [00:29:00] you're moving in the right direction.

STEPHANIE HUBKA: You're gonna course correct, and more importantly, again, you're gonna build your confidence when it comes to using ai. Keep it small to start, don't overwhelm yourself. I think that's the first way that people start to set them up for immediate failure as opposed to the fun failure that comes with trying new things and learning from them.

Yohanna: And you have a lot of experience after all of the sessions you've led and organizations you've worked with. I'm curious what sticks with you the most, aside from everyone being so kind, you know, um, but what's the biggest lesson you've learned from. Facilitating AI education that you, that you wish every leader would hear?

STEPHANIE HUBKA: Yeah. You know, it's, believe it or not, not as much about the technology as you think it is. 

Yohanna: Yeah. 

STEPHANIE HUBKA: Okay. It's a lot more about trust. Everybody thinks this is gonna be a tech training of sorts. It's not. It's about developing the trust that you need in order to do this. Well, when people trust that AI is gonna be used well, it's gonna be used to support them, not replace them, for example.

STEPHANIE HUBKA: I think you [00:30:00] immediately start to see people's defenses drop. They're a little less afraid. They're a little bit more willing to embrace it when it's an option for them. Really every successful AI initiative that I have seen starts with human connection. Human connection, very much built on trust. So if you pull trust from your AI implementations and it's not part of the way you get your people talking about it or you're using it or modeling it, you're gonna start to see people withdraw.

STEPHANIE HUBKA: You are definitely not going to see the kind of results you're hoping to. 

Yohanna: You spend a lot of time. Helping others grow? 

STEPHANIE HUBKA: I have. Yes, I have. 

Yohanna: Right. And and you, and you talk a lot about like creativity and rest. You write and speak a about workplace culture and experiences like vacations. How do you balance learning work with creativity and rest in an AI accelerating world?

STEPHANIE HUBKA: Yeah. So to give a little bit of context there, I. In addition to all of the work that I [00:31:00] do in talent development through produce learning. Years ago, more than 10 years ago, actually, my husband and I started a little travel blog that we've now had for, yeah, I guess about what, 12, 13 years now. Um, we started it because we love to travel.

STEPHANIE HUBKA: And after a while, uh, we've realized we had a lot of people asking us questions about how we did it. How do we budget for it? How do we pick a place to go? And I guess what they're really asking too are what are the outcomes? You know, when you trade your time for any experience, people kind of wanna know whether or not it was worthwhile and.

STEPHANIE HUBKA: I think you know, today we've talked an awful lot about the need to prioritize the human experience. In a world that's more and more enamored with ai, I don't think there's a better way to prioritize the human experience than to have one. And so for me, travel really is about the human experience. It is about the opportunity to explore, to challenge, to try new things.

STEPHANIE HUBKA: To, you know, find places that you [00:32:00] love and also places that you don't love. And so when it comes to how that fits, especially into my world, uh, because I am a solopreneur, I work for myself, I am also a live to work person at. As opposed to a work to live person. I could work 24 7 if I had the stamina to do it.

STEPHANIE HUBKA: I love what I do. But that said, it really comes down to protecting your time. We need rest. We need breaks. We need opportunities to take vacations. Vacations, by the way, could be what I do, which is typically travel. They could also be vacations where you travel to your sofa. And you lay there because that's what you need.

STEPHANIE HUBKA: Or they are vacations where you travel to a local park and you watch your kids have fun on the playground or where you travel a few towns over to try that restaurant you've been meaning to try. There are a lot of different ways to do that, but the thing that you'll find is that when you do start to prioritize rest and vacation and travel.

STEPHANIE HUBKA: You're gonna wind up in [00:33:00] situations where you're building skill sets that actually translate back into work. Uh, one of the things that's always surprised me is that when I travel, I'm often in situations that are, you know, a little bit different than what I'd find at home. I'm usually a little off balance.

STEPHANIE HUBKA: There could be language barriers. I might be sitting there trying to figure out how in the world I'm gonna pay for something when I can't remember what the dollar is to wherever I happen to be. You're gonna be in situations that are gonna push you a little bit. What's happening in those moments is you're building skillsets.

STEPHANIE HUBKA: You're getting to explore communication, decision making, all of these things that, by the way, you're not gonna leave on vacation. You're gonna bring those back to work with you. So all of a sudden you've had a difficult communication experience while you're traveling. Well, what did that just teach you about how to approach a difficult communication experience you're having with a colleague?

STEPHANIE HUBKA: It really starts to come full circle. I've really found over the years that some of the best experiences that I've had in terms of [00:34:00] my personal development and growth have come from vacation, but really come to life when I've come home and gone back to work and been able to use what I learned. So it really is all in how you approach that time and think about not just having a great time, but the fact that we are growing in all ways all the time.

STEPHANIE HUBKA: And even when you think you're resting and relaxing and you often are. You just might be building a skillset that's gonna make you even better when you get back to 

Yohanna: work. Yeah. My little mini vacations are d and d, just putting my phone on. 

STEPHANIE HUBKA: I love that. 

Yohanna: Putting it like on a sh on a my bookshelf and then walking away.

Yohanna: Yes. Like that's for me mentally, that's like a real, 

STEPHANIE HUBKA: it is so healthy to do it. 

Yohanna: Yeah, absolutely. 

STEPHANIE HUBKA: So healthy. I, I'm so glad you do that. 

Yohanna: So before we wrap up, I'd love to bring it back to a human moment. You kind of were touching on it. Um. But you know, because stories tend to stick longer than strategies.

Yohanna: What's a, what's a personal story, maybe, you know, from your travels or training work that illustrates the human side that you were talking about, [00:35:00] that the human side of adopting new technologies like, like ai. 

STEPHANIE HUBKA: You know, uh, one thing we haven't talked about yet is how I first got started using ai. And I will tell you the very brief story.

STEPHANIE HUBKA: Um, I often will start with this when I am telling stories. Uh, there's a, a couple of sessions that I do on how to humanize AI generated content. So. When I, this is, gosh, I think this was 2022, so not all that long ago. I was at a conference for talent development professionals, about 12,000 of us. We were gathered in San Diego as a matter of fact.

STEPHANIE HUBKA: And leaving the conference, I realized that all anybody talked about was ai. Is AI coming for my job? Am I gonna be replaced by this thing? I don't even know what it is yet. Chat, GPT is gonna take it all. And I remember at the time, thinking. I am not buying into this in the least. I'd never used AI in any meaningful way.

STEPHANIE HUBKA: [00:36:00] Certainly not anything like chat, GPT. So long story short, I return home. I have a project that I'm finishing up. I had a, uh, a course design document that was due to a client on a, we had been doing just a ton of different training documents. So I had this very last one that was due, uh, it was a Friday. I sent it over to them.

STEPHANIE HUBKA: It's been all day recent. Researching it, by the way, you know, I mean, I was really proud of it and at four o'clock when it was done, I went and I met my father for a glass of wine. Every Friday at four o'clock, my dad and I have a glass of wine together, and it's one of the little rituals that we've got that I absolutely love.

STEPHANIE HUBKA: Look forward to it every week. This is kind of an interesting week though. We sit down, my dad asked me how work was, I told him about this little outline that I'd put together, and my dad has this. Phone out, which is sort of weird. My dad is of the opinion that if you're having a conversation with someone, you don't have your phone out.

STEPHANIE HUBKA: You connect with them, you focus. Right. Same, it's, it is 

Yohanna: same dad. Yep. 

STEPHANIE HUBKA: Yeah, I love it. I really, really do. But [00:37:00] he has his phone out and I'm thinking, well, maybe he's waiting for a call or something. He's asking me a little bit about, you know, the outline that I did and all of a sudden he starts reading it to me and I thought, oh my God.

STEPHANIE HUBKA: I sent my outline to my father. I didn't send it to my client. I sent it to my father. I was actually kind of embarrassed. I'd never made a mistake like that. I am a double and triple check my recipient kind of person, and all of a sudden my dad turns the phone around and it's chat. GPT. Chat GPT. In those few moments with the little information I gave him, wrote my outline for me.

STEPHANIE HUBKA: So as I'm having an existential crisis in front of him, he's laughing and he goes, you know, I don't know what you do for work, but apparently robots can do your job. And I'm thinking, oh my God, he's right. I have reason to be worried now. So. I went home that night, 

Yohanna: uh oh. 

STEPHANIE HUBKA: And I poured what I often describe as a slightly bigger glass of wine.

STEPHANIE HUBKA: And I sit down to see if I can do this. Can I recreate what happened to me? And I did. I recreated it. It did a great job. It pulled together my [00:38:00] whole outline in seconds, and I'd spent hours researching it. So then I thought, you know what? Let's see what you really can do. Chat, GP. Develop my course. What's going in my course, and we'll put it this way, it was a genuine dumpster fire.

STEPHANIE HUBKA: It was embarrassingly bad. It starts out with like, you know, introductory music and the first, you know, text that it has is welcome to the course. I'm gonna guide you through the course, and I'm thinking if I ever put that in front of a client, I would be laughed out of this industry. And what that taught me is that, yeah, the tech absolutely has a place for, you know, for when you're thinking about how you might be able to use it, it absolutely would have made the outline process faster.

STEPHANIE HUBKA: But what it could not do is insert the humanity into this training that without it, that training would have lacked in absolutely every meaningful way. Ooh. So when I think about what it looks like to use any form of ai, this is [00:39:00] why I always say you have got to start with the human first. The AI can do incredible things and often will, but if you don't start with your people, you are absolutely gonna miss the mark time and time again.

STEPHANIE HUBKA: And when people think that AI has been too responsible for something that they're going to experience. They're gonna feel disappointed that trust is gonna be broken, and you're gonna have a very hard time getting it back. So I think about that story a lot when I'm working with ai. Um, I think there's a real human side to all of this.

STEPHANIE HUBKA: There's a lot of fear, a lot of concern, and at the end of the day, there's a lot of opportunity and hope if we use it in a way that makes sense for 

Yohanna: us. Oh yeah. Now I'm gonna think about it too. You're, you've been thinking about it, but now I'm, that's all I'm gonna think about. That's incredible. It's, 

STEPHANIE HUBKA: it's tricky, but it'll stick with you.

STEPHANIE HUBKA: It will. 

Yeah. 

Yohanna: Absolutely. So that's time. Thank you so much for your time. 

STEPHANIE HUBKA: Thank you. This was so much fun. 

Yohanna: Yeah, I learned so much. 

STEPHANIE HUBKA: I had a great time getting to chat with you. 

Yohanna: Are you active on [00:40:00] LinkedIn? Can people reach out to you on LinkedIn? 

STEPHANIE HUBKA: Absolutely two places to find me, definitely LinkedIn. Please, please connect if you have questions.

STEPHANIE HUBKA: Wanna chat. I am always happy to chat about this, uh, in my website, produce learning.com. You will often find me there. We've got a blog starting up. Working on a podcast as well, so would love to stay connected there too. Okay, 

Yohanna: great. Yeah. Thank you so much. 

STEPHANIE HUBKA: Thank you. 

Yohanna: This has been a really great conversation.

Yohanna: I love that. Through all the talk about AI data and tools, what keeps coming up is something really human clarity culture and helping people feel confident enough to actually try at the end of the day. Transformation isn't about technology, it's about whether people know how to use it and believe it's worth using.

Yohanna: So thank you for sharing your insights, your stories, and the practical wisdom leaders can take back to their teams tomorrow. If you'd like to learn more about, uh, the business value of AI training through act iac, or explore, more of this work will include links in the show notes and to anyone [00:41:00] listening if this episode's.

Yohanna: Sparked an idea or a new way of thinking about learning in your organization. Share it with a colleague. That's how this conversation grows. So thank you for joining us on the Buzz. We'll see you next time.