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AI is reshaping leadership, strategy, and the very role of HR. In each episode, the host Barb Bidan explores how AI drives innovation and leadership in HR with actionable insights for the future of work.
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The Human Element - Dawn Stastny
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Barb Bidan HOST: [00:00:00] Today my guest is Dawn Stastny, chief human resources officer at Belpak. And I wanted to get Dawn on the show because of the vantage point that she brings to this conversation. Dawn spent over a decade running her own HR consulting practice Stellaris Group, working across more than 50 companies in a wide range of industries before stepping back inside as an operator.
Now Dawn is building HR and compliance at Belpak, a company that came together just this past year when three established packaging businesses, Coregistics, Proven Partners, and Belvica, combined into one organization with more than two dozen facilities across the US and Canada. That means that Dawn is doing workforce planning for a workforce that is almost entirely frontline and deskless on, on packaging lines across two countries at the exact moment that AI is changing what work looks like.
Dawn also came up through compliance and risk, so she brings a different [00:01:00] lens to this than most guests that we have on, one that's less about chasing the newest tool and more about how you make sound, defensible decisions about people when the ground is still moving beneath us. So we're gonna dig into what surprised her the frameworks that she's actually using, and what she would tell other leaders walking into this for the first time.
Dawn, I'm so excited to have you on. Welcome to The Human Element.
Dawn Stastny GUEST: Thank you. I am thrilled to be here
Barb Bidan HOST: Dawn, you have had an incredibly interesting arc in your career. You spent over a decade running your own HR consulting practice, working with a ton of different industries, and now you're back inside building HR and compliance from the ground up in a newly formed company. Walk us through that path.
Dawn Stastny GUEST: The combining of the three has been really fun from the standpoint of we were all very different. And so anytime you have a combination from an acquisition or a merger or something like that goes where you're mixing it, [00:02:00] it's rarely the structure that fails. It's a cultural people thing that is your challenge because they're all very attached to their legacy business. They're very attached to the way they did it and it's a pride thing. They're very proud of their entire organization and what got them there, and trying to move people to the next level is always fun. Trying to move them to the next level when they don't wanna give up the old one is a little more fun. And then in the end, now we've had this extra twist of AI kinda upending. It's almost the new industrial revolution, but I would say it's really more like the discovery of fire than that because it's moving so fast that's changing the people element in such a drastic way. there's really no good basis historically for how you get there now. - People look at it and say it's taking jobs. It's redesigning them, and we've had that happen along the way in [00:03:00] history. But to do it at this, almost education and everything else is having to change. Every fundamental core to the framework is changing because we can't educate people now, and my daughter graduates in December, so I'm the first-hand knowledge of this, seeing it every day with her friends that are graduating, is that we're no longer educating them for here's your career.
We're educating them almost, or they have to be educated in adaptability
because it's we have to educate them to reinvent themselves and reinvent the work and reinvent the flow every day.
Barb Bidan HOST: Oh, I mean,
It's moving so fast and yes, there are paradigm shifts in the past that we can point to, but none feels as big as this, I think probably in both of our careers so far. It's quite exciting, but you have a ton going on with the business combination and this shift.
What did running Stellaris Group and seeing dozens of companies up close, presumably probably [00:04:00] working with multiple clients at the same time, what did it teach you that you couldn't have learned any other way?
Dawn Stastny GUEST: We had two offices that were fully staffed and we had things going on every day because in a small business, which is where we focused on, was that you don't need HR every day, but when you need it right now, and you don't need to figure out how you're gonna do it or who's gonna do it.
But they didn't have a need or the means really usually to have that full-time expertise on staff just at a, "Hey, could you run down to my office for a minute?" They didn't have that. So that's where we filled in those gaps. But having the different industries, because we had legal partners, we had medical practices, we had industrial, you name it.
The one thing I can say hands down, business in by comparison is easy. People are messy. And I love that
in that they're just... They're people. People are different. They're always different, and they make it complicated. It's [00:05:00] not the work itself that's complicated. It's the human dynamic
every time
Barb Bidan HOST: It's... when we jokingly say if the humans would just do what we needed them to do then business would be easy. And which is the thing that makes our jobs really hard, and I'm guessing that the amount that you would see through Stellaris and running and working with multiple companies at early stages where they didn't need a full-time HR person, you would just see a lot in a short amount of time.
I'm sure that's really equipped you for what you're now working through back in-house as an operator.
Dawn Stastny GUEST: It does. I tell people all the time I need to write a book because if you told them these things, they would swear you're making them up, and you're like, "No, that really happens." No, really, it does. It happens all the time. And the thing is that's the trick about AI that people have not recognized. The more AI and technology evolves, the more important and valuable the humanity skills matter. The difference in who will make it and who won't, and who will [00:06:00] succeed and who won't, and how it's going to go, all really comes down to those humanity skills. And people call them soft skills. I refuse.
I've had this personal protest for about eight years now that I refuse to call them soft skills 'cause there's nothing soft about them. Anybody that's had to do the hard conversation or work and still show empathy at the moment, but then toe the line, but then feel for your person, there's nothing soft about that. Nothing at
Nothing at
Barb Bidan HOST: Is no, and honestly, we've had to as working in HR, right? We have to master those skills, but also help others get strong in those skills as well, and couldn't agree more that those are the skills that will stick, right? As AI continues to deepen its ability to help us the pieces that make us human are the things that will differentiate, I think between performers and companies without a doubt.
So I know Dawn that Belpak is not a [00:07:00] brand new from scratch company, right? You brought together three established businesses from three legacy businesses. What was the actual moment, though, that you realized that you weren't just running HR? There was a lot of building from scratch that you need to do when you bring through three sets of policies, three sets of cultures, like three sets of norms, et cetera.
When did you realize this felt more like a build?
Dawn Stastny GUEST: It really became... The first two years of Coregistics under our current ownership, we ran autonomously. And so we had that first two years of learning how to work, not in a family-owned business, but in a private equity-owned business. And to learn how that it's... And it was hard for founders, 'cause founder syndrome is real.
I don't care what anybody tells you. It's very real. To convince those people that, "Okay, it's not yours anymore. It is, but it's not. You're still responsible for it, but now you have a partner, and you have to report certain things and do certain [00:08:00] things." So that first two years went very well for us.
It was a nice ease into it. But then the two acquisitions happened within 60 days of each other. So it wasn't like we had the benefit of, "Okay, here you are. Okay, now we're gonna add this one. Okay, now we're gonna add this one." No, it was like, "Here you go. Go get it."
And so that was really the moment, and it was in the summer of ' 24. So we had one in June and one in August, and by September, we were in full throes of how do we make it one. And there was a lot of change that went with that because Coregistics had a 12-year history at that point, and Belvica had a 30-year history at that point. And Proven Partners Group, they had a long history as well, but Proven Partners Group was a single location, whereas Belvica had eight in Canada.
So now you're talking cross-border. It's not just the US anymore because Coregistics was 14 on the [00:09:00] US side.
So that was when it was really like, "Okay, this is complicated." And even at a higher level of our executives, it was we just need one set of benefits. We need one payroll." Okay, but see there's the laws that Canadian data flowing to the US, not optional. They store their data in Canada, and you're not getting it here. 9/11 solved that for us with Patriot Act and some of those protections. Canadian data does not come to the US anymore. And then you have, Proven Partners Group who was one location who, 24/7, one of our largest facilities.
It's what we call a hyper facility. But they were used to being me, myself and I and they would make decisions based on Elgin. " That's what we're doing. This is what we do. We're here." Okay, but and if I said it once, I think I said it 100 times within September to December that year because I was in that building every day, was, "You can't make decisions for 23 other locations. We [00:10:00] have to do this as a whole. It's, One Belpak. One Belpak." I, We hear One Belpak in our sleep now because It's different to try and get past those traditional mindsets of this is what they know and this is what made them successful, so they're going with that
Barb Bidan HOST: Completely. I've been through something similar at Crunchyroll with a business combination at scale, so I totally hear you. I'm actually gonna pull us into the AI topic a little bit deeper because I know that this is a tool that obviously is helping you wrangle some of what you're encountering.
I'd love to get into AI's impact on jobs and workforce planning, right? Because it gets talked about a lot at the strategic level, but you actually are living this also with a frontline multi-facility cross-border workforce, just like you described. What is something that has surprised you that you didn't expect until you were actually in the thick of it?
Dawn Stastny GUEST: We have always recruited very traditionally, [00:11:00] and I almost feel guilty saying that and going, "Shame on me, I should've moved probably sooner." Very traditional. You look at LinkedIn, you look at resumes, you post jobs, you do the things, and you screen people. You're weeding people out manually in a system. And it's very traditional in its manner, and that worked for the world for a long time. But when you start adding 24-hour facilities okay, I have a shortage of mechanics. I need mechanics to work on that equipment that the packaging equipment that these people are working on the line.
If the equipment's not working, those people aren't working, the product's not coming, bad things happen. If I need a mechanic on the third shift and my recruiter's not coming in till 9:00 AM, he's going to bed by now. I can't get him
Barb Bidan HOST: The old way doesn't work then, and that the traditional way doesn't work. Yeah
Dawn Stastny GUEST: And you think about it and you think I could get my recruiter to get up and come up here in the morning at 6:00 in the morning and do a phone screen with a guy."
But one, the guy [00:12:00] wants to go to bed. He's not interested. Having AI do just even that front-end screening, that first screen, the first pass of bucketing people into a system to say they have 100% of what you're looking for, they can work on all five machines, they can work on all five brand of machines, or they can work on it but they can't diagnose it, or they can do PMs, but they can't, and bucketing them into these are all the pieces of this has 100% of what you need, or this one has everything except this one thing.
Can you live without that one thing? And having it do the screen, one, it solves a bias, an even unintentional bias of I happen to like these particular kinds of candidates. I'm ex-military. I'm a huge fan of a military candidate always because I know the discipline that's involved in there, and even though I would not discriminate against someone for not being it, I'm gonna have a bias to, ooh, they get the halo effect right out of the gate [00:13:00] of I'm gonna expect you to have discipline in these other things because you're mili- you just came out of the military.
You were working on tanks. You can work on a machine. What can we do here? And those kinds of things, it has no bias, and people are easily derailed. When you talk to somebody and they don't necessarily want to answer the exact question, especially in an interview process, and they want to go a little sideways over here and derail you onto something else, and maybe you'll forget about that, AI does not forget. She will not and the one we use is called Anna will not forget. And if you said, "You know what? Somebody's at my door. I'm gonna have to come back to this," and I call back into that in 20 minutes to finish my interview, she's picking up where I left off. I'm not getting out of answering that question.
And so that's amazing in that the quality of candidate that you will find and the volume, and then the human element comes into, okay, now I can watch that [00:14:00] interview and say, "Okay, I see their face. I see their inflection. I understand the context of what that transcript says, and they have everything but this one thing.
Okay, maybe I can say we can make an offer, and you've got 90 days to develop that skill, and this one last thing, we can teach you that." It just improves and opens up a whole new pool of people that you wouldn't have had because they went home and went to bed.
Barb Bidan HOST: Without question. I've seen some really interesting tools especially in the high-volume frontline space, right? Where you just, you have to hire quickly, you're hiring for s- specific skills, and you need to make it happen because you have a shift happening where you need that person.
And so as you're doing that you've spent your career building governance and compliance frameworks, right? You talked about the additional degree of honestly fairness or lack of bias that AI can bring in this process. But now you are out there applying the sort of discipline, your own discipline around governance and compliance frameworks to workforce [00:15:00] decisions around AI and AI tooling.
What sort of decision framework are you actually using to guide yourself or guide your team on how to approach work with AI safely?
Dawn Stastny GUEST: One, the thing that always from jump in the beginning of it before it was really as heavy as it is now that everybody's on the topic my fear was always on the compliance side of you can't put just anything into AI. It's out there in the world now. What system are you using? How much data are you putting in there?
And that's our data, that's our customer's data. You can't... and trying to make sure we had the proper fencing around what we were doing. And if you don't have your own tools, and not everybody can afford to have somebody make your own AI tools just for you, and they buy something off the shelf, or they subscribe to a subscription that they didn't know they were gonna use and if they're using some kind of open forum that it's not protected and it's not indemnified, there's just a [00:16:00] huge legal and compliance risk associated to that of, "Don't put that out there."
That was always my fear on the front end. Now, because we have partnerships with, we use Microsoft products, and so we have Gemini and we have the Microsoft things where it is indemnified, and as long as you use the tools that are in-house your data is secure. That's less of a concern, but you still have...
People think AI is making decisions for you. No, AI is giving you information, and you're still responsible to figure out is the information right. Did it hallucinate? Did it make it up? Did it just infer something on its own? You're still responsible for figuring that piece out, which is hard for some people because they just wanna go fast. And fast is great, but only if it's accurate. They always ask me, "Do you want it right or do you want it right now?" Yes. Yes, I do. Both. Right now. I'm a C and a D, so I want it right, but I want it right now. That can be its own challenge as [00:17:00] well, but making sure that people understand the humanity side of credibility and good judgment and discernment and ethical decisions is still at the core, which is why I say humanity becomes more valuable and more important the more technology moves
Barb Bidan HOST: Completely. And we have talked about a lot on the show that humans still decide, right? AI makes those decisions easier, faster, et cetera. But the human decision-making absolutely comes into play, and so judgment, discernment, et cetera, become increasingly important. So now shifting a little bit more to the human side of things the employee experience.
So let's talk about the humans that are actually living through this change in the work that you're doing. What has the employee experience been like as it relates to AI within your business? And what are the ways that you and your team are intervening to make sure that you're continuing to [00:18:00] make that employee experience even better?
Dawn Stastny GUEST: I have been extremely vocal about I have a differing opinion than a lot of more senior... The higher you go up the food chain and the more senior level people become- ... their understanding of AI and what it will do for efficiency and productivity is a little bit different than the view at a much more operational level. And I've been very vocal of, if you can get AI and an agent to do the work and come up with, "I'm gonna save six hours a day," at a certain level, and not to bash finance people because I have all the respect in the world for them, that's the one job I want no part of I'll take people over numbers any day. They always look at it and go, "Okay, we could have somebody absorb that two hours and disperse that two hours, and that's where we're gonna get our efficiency. That's where we're gonna get our productivity." I'm very vocal about not, and I think our [00:19:00] workforce is appreciative of that- Yeah ... that I'm such the proponent of my answer, especially with the HR team, because that was where it originally started with us, of let's do a pilot with recruiting and see if we can make this better. My answer is never, where do I send that two hours? My answer is, "Okay, you've got six hours now. What did we not get to that we wanted to do that we couldn't do because there's only so many hours in a day? How do you turn that six hours into more efficiency, more productivity, do a better... go deeper, go harder, go faster in those things, and using that?" I believe wholeheartedly that's where the real productivity and efficiency for EBITDA margin and everything else that matters to the higher level, that's where it's really gonna come from. It's not going to come from, we took that six hours and we're gonna cut ahead. Because the person that taught the machine to do all those [00:20:00] things, and the person that did all those things and knows what to do with it and why you did it to begin with, and how it works and all of that legacy historical knowledge, you cut that head, you lose all of that.
Okay, great. You got the workflow. What do you do with it?
Barb Bidan HOST: I love that approach, right? You're giving the time saved back to the team member who's actually helped use AI, right? To create efficiency in their workflow using AI to save themselves time. They've earned some time back. What are they gonna do with it? I'm curious what the best thing that has been an unlock, like the best thing your team has gotten to as a result of having some time back to get to some things that they just were not getting to before.
Dawn Stastny GUEST: of us have time to interview and make sure we have the right people than before because we can hammer down on, we can go through an exorbitant amount of resumes and skills and criteria because you're looking at skills-based hiring these days [00:21:00] really being very key. And especially when you're looking at frontline and operators and things of that nature, machine operators, mechanics and, blenders and mixers and people that have a very specialized skill set. To be able to get to, okay, these are the ones, this is the 20 we wanna take the next step with, and to be able to split it among all of us and go, "Okay, we want more hands on it instead of a recruiter," really, we don't have to wait as long to get the person we want.
For him to get through 20 of them, it gets narrowed to 20.
He can get through that. He can rank them. We can go, "Okay, these need this level of people. These need those." And you're moving at such a much more accelerated pace, but it's still human at that point. You've just weeded out all of the... And I hope nobody, I hope I don't hurt anybody's feelings and offend anybody.
Every school teacher that doesn't want to [00:22:00] go back to the classroom after June that has applied to the job that they really don't want, but please don't make me go back to the classroom. And if anybody that does recruiting will know where that comes from. For whatever reason in the summer, the teachers they flood the jobs
Barb Bidan HOST: anyone who does executive coaching around careers as I do also know that. It makes me sad every time, but I have talked to a lot of teachers and it is-- that's a whole other topic. But it is a thing and this is the time of year where you see it. And teachers spending the summer trying to figure out how to do something different, which maybe says a lot about how we've structured that for sure.
Dawn Stastny GUEST: education is the one thing that has not moved. If you look at the way we treat medicine, look at the way we treat building cars, look at the way we've automated all kinds of things. The one thing that has not changed in this country is education. They are still sitting at a desk with the things exactly like they were 60 years ago. It's the one thing that [00:23:00] has not changed
Barb Bidan HOST: which is scary since that's heading sending the next generation into the workforce, right? That
Dawn Stastny GUEST: I think it's-- Yes, it has everything to do with what we're talking about with this workforce planning and institutions needing having workforce hubs and institutions that teach a different way and teach a different set of skills because the jobs are gonna have to be redesigned with AI. It's not that you have... We'll actually have more jobs, I believe, than less jobs. They'll just be different jobs. So people will have to be upskilled and reskilled in different categories, but their knowledge base will be there. I think the real challenge in, I'm gonna stick it on a calendar and set a reminder just because I gotta know.
I'm competitive with myself as much as I'm competitive with other people, is I think twenty thirty-one is the year to watch because there will be no middle managers. We are gonna have a middle management crisis in twenty thirty-one because of all of the entry-level jobs that have been cut out by [00:24:00] AI in twenty twenty-six and twenty twenty-seven. Those people that have four years of experience and have come up through it and learned it and know it, and they're ready to take those middle manager roles you and I have to plan a date, Barb for twenty thirty-one to
have a conversation. Where is it? Yeah. Where did it go? Because I think it's gonna be a management crisis.
Because if you look generationally as well, Generation Z, they don't want to be supervisors. They have a gig economy mindset. They wanna be responsible for themselves. They want to set the boundaries. You know, people think it's because they're lazy. It's not they're lazy.
They grew up with us, who had our phone at the table, we missed the recital, we missed this, and they're setting boundaries that we did not. And good on them . I've had to work myself to that having a Z, but I have two millennials as well. So I have kids that are thirty-nine, thirty-eight and twenty-one
Barb Bidan HOST: Which is great training ground actually as a parent for the workforce, right? And working with an [00:25:00] inter-intergenerational workforce as well. And I wanna ask a question about the actual teams that you work with, right? When you are working with a frontline workforce I am curious if
any sort of AI innovation has come to the way that the business actually runs. And then where I'm curious from an HR standpoint is how you have managed communicating change to a frontline workforce that's not a desk-based workforce, and that you're needing to bring the frontline teams through things.
How has that differed compared to what those of us working.. with primarily desk-based workers,,
Dawn Stastny GUEST: we're really on the front end of an entirely new set of capital expenditures where we're automating a lot of the equipment. And just the idea... Okay, mechanics, because that seems to be the easy example for everything these days, is because they have such a specialized skill, and these are expensive pieces of equipment.
Even the old ones, our old equipment, can run up in the million dollars, [00:26:00] millions of dollars for a piece of equipment. But if you're gonna automate something, now it has the computer in it, and AI can do a lot of that automation. A mechanic may or may not be able to know how to work that panel.
If you've got an old-school mechanic, he can fix all kinds of things. He can fix any piece of mechanical equipment, but it's not mechanical anymore. It's computer-driven. And how do you... if you go to a copier now versus... and I think for most of us, when we look at it, you look at it and you go, "Okay, a copier today versus a copier when I started using a copier." I remember when Lotus 1-2-3 came out, so I'm that old. It's very different, and now you can push it and it'll tell you where the paper jam is. Whereas it changes everything. And so I think where we're gonna have... We're on the front end of that, but I think where we're gonna have our real challenge is in skilling those operators to not assume that it's a mechanical problem.
[00:27:00] It could very well be the computer. It could be push, and the new equipment will be very different to them in that they're not gonna open a panel and see equipment, they're gonna open a panel and it's gonna be a computer brain. And
that's a different animal
Barb Bidan HOST: So it turns out you've got the same reskilling and upskilling issue that all the rest of us are facing regardless of the industry that we work in. Just that the skills that you're tackling with a mechanic might be different than the skills that we're tackling. But the skills that you need to do your job tomorrow will be different than the skills you've needed in the past, is the bottom line there, and it's something that we're all focused on right now.
So let me bring us home here with a question of, around advice for those leaders who maybe are a little earlier in their journey of starting to adopt AI from an HR perspective. What's some practical advice that you would give to a peer in the industry to help them accelerate?
Dawn Stastny GUEST: I would say partner with your local community. Like we have gone out [00:28:00] of our way. I have a fantastic HR manager in one of my locations that she has gone to the community college, and she has partnered with them on internships because all our old school mechanics are gonna need some of these younger, fresh out of school mechanics that know how the computers work to help them to even internally develop.
Because if you start talking about, we can't just bank on people coming with the skills. Instead of consuming talent, we have to develop talent and partnering with your community. Because the local community college, you partner with them, they're gonna give you the best students that you've got.
You're gonna have a relationship with them. They can refer people to you. Ours even has a grant that they pay for the first two semesters, and then we pay for the third semester, and then these people have already learned all of our equipment, know our people. They're used to coming to us. It's almost like Cheers. "Norm." Coming to your space every day, you're [00:29:00] gonna have a better chance of hiring them fresh out of school because they know what they're doing. They know the equipment. They know the people. They've developed relationships there. I would say get in front of that. Tackle it from a, this is not to replace anybody.
This is to make your life a little easier so you can do the other things that we never get to that we want to. The fun projects, especially HR. The fun things, the extra data analysis to go, "What if we change this plan?" Or, "What if we change this program?" But you never get to, you just let it ride because right now I gotta get a 5,500 done, I gotta get this done, I gotta get that done, so - that's gonna have to back burner for a minute. You can bring it forward and move into that if you plan right on the front end and you adopt it. So don't have your people be afraid to adopt it because they're worried they're not gonna have a job, they're gonna work themselves out of a job. There've been so many large companies and conglomerates that have done that and sent out the 31,000-person [00:30:00] email. Ours is more, we wanna make more time to do the fun things. And give them a shot on the front end to go, "If I could get you two hours of your day back, what project would you pick for yourself that you wanna work on that you never get to?" And let them work on the things that are gonna get them there.
Because as much as people leave for money and other things, I promise you, growth, especially the younger generations, growth and their being able to contribute and develop is far more important than people give it credit for. They don't jump and change jobs every two and a half years because change is just what they do.
They don't particularly like change. They jump and change in two and a half years because they stopped growing, they stopped learning, everything got comfortable, and they didn't have an opportunity or see a path to the next thing. If you're giving them that time to say, "I'm gonna get you two hours of your day back.
You can make an agent. [00:31:00] Let's do this. That'll give you two hours. If you got two hours, what do you wanna do with that two hours?"
Barb Bidan HOST: Completely. It's a major tool to overcome resistance, I think, to the changes that we're facing with AI as well. A huge unlock there. I could go on, but I'm gonna take us to the lightning round. Just so a couple of quick hit bits of advice here. What is one tool or resource that you would tell every HR leader to check out this quarter?
Dawn Stastny GUEST: I would say Claude or Fountain. Fountain is amazing for the recruitment piece. That front end it's incredible, and they have different agents already built out that you can do a trial. You can do a trial for 90 days and decide, do I love it? Do I not love it? Does it work for me? Does it not work for me?
And get your toes in there. But Claude is probably the most versed that I've used in what we do to be really efficient at getting that time back to go, "Now I'm gonna work on something that's [00:32:00] of more human value, and that's gonna use my personal skill set and intellectual capacity that AI can't do. I'm gonna automate some paper over there."
Barb Bidan HOST: Awesome. Let me give you one more. What is the best piece of advice from your years of running Stellaris that you actually think still applies completely today?
Dawn Stastny GUEST: Never ever say, " Okay I've seen it all now," because someone will top it every time. The human element, never underestimate people. And, I told the COO this morning, I know you didn't serve in the military and I did, and one of the first things we learn in the military is the most dangerous person in the world is the one that has nothing to lose Make sure your people are seen or heard.
And there is no amount of the other stuff that will get you past people. You can have all the inventory, equipment, CapEx you want. Without the people, you got nothing. And so it doesn't matter what you buy, what you sell, what you have, your inventory, your stock, your [00:33:00] process. Without the people, it's not happening. And those people at that level, the front line, they have to know that you care, that they're valued, that they're appreciated that they can tell you things, and that trust. That's what you gotta have, or it's never... none of it will work
Barb Bidan HOST: Dawn, let me take us home here with I tried to capture some notes as we're talking. It's been an enjoyable conversation today. I captured two things that I wanna share with the audience. One is your reminder that soft skills are not soft, so I liked that you called them humanity skills.
The more AI evolves, the more that humanity skills matter. It's just a little different twist on something we've talked about before on the show, so I liked that framing. And then the second big idea here I think is that giving the team members an opportunity to pick what they do with the time freed up from AI-based efficiency, right?
So where AI [00:34:00] creates efficiency, ask your team what can be unlocked, what are we not getting to today that we can give them time back to do versus creating efficiency with AI and then kinda cutting those hours. If we give those hours back to the business, what can we do that we were not getting to previously?
And so I always leave guests with the final word. What is one piece of advice that you would give to viewers to think about on the rest of their drive home today, so our HR peers and counterparts listening to the show?
Dawn Stastny GUEST: No one likes things to happen to them, even if they don't have full control over what's happening, and AI is the prime example of none of us have control over AI. It's a wildfire. It's going. But - to that point of giving them the, a choice in what they do with that, if it's gonna happen to you, at least let them participate in it happening to them. Don't just have things happen to people. No one wants it to happen to them. They want [00:35:00] it to happen with them. So if you involve them, that's where you're gonna get your adoption. Your adoption is not coming from an edict, and here it is, and we said, and you got it. It's gonna happen with, "Here's what we can do with this," and let them feel that they have some Part of control over how it's gonna happen, not just they wake up one day and their world has been changed by AI and someone else
Barb Bidan HOST: Everybody all included, all in on AI transformation is the way to go. I've enjoyed our conversation today, Dawn. Thank you so much for coming on the show. I've really appreciated it
Dawn Stastny GUEST: Oh, thank you. It's been a pleasure