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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 - Miki Virtue
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Barb Bidan: [00:00:00] Today my guest is Miki Virtue. She is the vice president of human resources at a financial technology company specifically supporting identity and fraud services. Miki's career has a through line that is more rare than many others in our field. She didn't come up through traditional HR generalist roles.
She spent the first six years at T-Mobile building training and communications programs, which means capability development, learning design, and closing skill gaps are not something that she arrived at ~ear-~ or later in her career. It's where she got started. They have been her lens from the very beginning. Miki then spent years building organizational development and leadership capability programs at Masterbrand Cabinets in manufacturing, and then at Taco Bell, where she helped turn around an underperforming market and recovered $2.5 million in sales. So at ~Alberts-~ Albertsons, which is a Fortune 50 company with 270,000 associates, Miki built dual-track [00:01:00] talent strategies for the proposed Kroger merger, designing simultaneously for both success and failure, which is a really cool scenario.
And now Miki is doing something that brings all of these great experiences together, leading workforce strategy specifically for AI adoption. Miki, welcome to The Human Element.
Miki Virtue: Thank you, Barb. Thank you for having me.
Barb Bidan: I am super excited to have you on. I love where you got your start. I'm also a non-traditional, didn't get started purely ~in the,~ on the generalist track. So you started in training and communications at T-Mobile. I also worked ~in~ in the mobile space too, so coincidental, and we share similar dogs we learned before the show.
So we have a lot in common, I think. But before you were ever an HRBP, you spent six years learning how to build capability and close skill gaps before you moved into some of your more broad HR roles. How does your foundation change the way that you look at AI readiness in HR?
Miki Virtue: [00:02:00] Honestly, I didn't really think of it that way when I was back in T-Mobile. I was in my 20s and still trying to figure out how the world worked, and it really hasn't changed much. Honestly, the first thing I look for has nothing to do with skills or technology. It really just comes down to curiosity because here's the thing, you can teach someone anything, but you can't genuinely teach someone to be curious.
And once you understand what makes them curious, you can communicate with them, you can train them, you genuinely understand what motivates them, and to me, that's just like table stakes.
Barb Bidan: Completely. When you think about where you got your start does that inform just how you think about HR in general, right? Starting on a more specialized path, like working out closely with the business is my guess. Does that inform who you are as an HR practitioner at all?
Miki Virtue: Yeah, absolutely. Because when I first started out, I actually started in supply chain and moved into [00:03:00] marketing. And so I was not always an HR practitioner. I was always a person, a human, and then an employee. And really what that taught me was, ~it,~ it really just nothing matters if the person's ~not--~ if you don't have the right person, ~th-~ they don't wanna be there, they don't have the right skills.
And so what that taught me about execution, because, in the OD side you're designing, right? You're designing what you think solutions are. But then on the flip side of it, as a human and an employee, you have to really understand how is this actually coming to life. And I honestly think that was the biggest transition I made in my career was from org design to HR business partner when I was at Taco Bell, because I just really wanted to deeply understand how my work was coming to life.
And so I've always had this push and pull on the work that I'm doing, understanding that none of it matters if I don't have the right people, and we can't execute against what I'm designing for.
Barb Bidan: Yeah, so having the right people in place [00:04:00] is obviously a critical element, and I'm sure then leads into some of the things that you have been working on more broadly since, right? The right~ right~ humans in the right places at the right times, and that plays into an AI future as well, right?
Your current role includes explicitly leading workforce strategy to support AI adoption. Talk to me about what that means.
Miki Virtue: Yeah I go right back to the human side of this. Truly, the first thing I look for has nothing to do with technology. It really boils back to curiosity. And so early on in my career, I was curious what did people need to hear from me on the communication side? This is a two-way street. But then on this AI adoption side, like I said, you can teach someone a tool in a week, but, you can't teach them to be curious about a problem.
And AI at its core really rewards curiosity. It punishes the certain and then it punishes those who [00:05:00] are, what I call comfortable with wrong. So AI, if you understand it, is probabilistic, and so that means it's gonna be wrong sometimes, and so it's gonna give you a really confident answer that is absolutely incorrect.
And so if your team or your folks have been trained for 20 years that being wrong is a career risk, you've just got such a bigger problem than a skill gap. You actually have a really big culture gap. And the technical stuff like that's just, that's table stakes to me. You can upskill that, but what you can't easily fix is a workforce that's been rewarded for, knowing all the answers and then suddenly having to get comfortable with asking better questions, and that's the real gap.
And most companies like aren't even measuring that.
Barb Bidan: And What I'm hearing is you need to either have a curious workforce or teach a workforce to be curious. How do you teach, um, or encourage curiosity, especially in an [00:06:00] environment where maybe it hasn't always been the thing that's been rewarded? How do you move people along that curve?
Miki Virtue: It is the age-old question of every business that I get to. It is so much more than just teaching curiosity. It's about creating psychological safety and having a culture where feedback is really rich and coaching is really honest. Every company I get into I can tell you what the three biggest things are.
Nobody knows how to forecast and budget. Nobody knows how to give really good coaching and feedback. And now we're dealing with AI. And so it's just-- it really boils down to a system that is self-reinforcing on the strong culture of transparency, coaching, and feedback, where it is okay for people to absolutely ask questions and undermine their own thinking and ask for better ideas.
And a lot of ego gets in the way there.
Barb Bidan: For sure, right? We humans get ~a,~ or do a [00:07:00] good job of getting in our own way a lot of the time. Are there any places that you found it particularly useful to leverage workforce data to target where maybe your ~l- ~team is lagging behind or there are some gaps that you need to address?
Miki Virtue: Yes. So your question is, where can I use AI to leverage workforce data to understand lags and such? Yeah, absolutely. ~We-- ~where I work today, data is not a issue. We have so much data, and so I love NotebookLM to help me synthesize all of the data so that I can be predictive. Certainly, I wanna be a strategic business partner, but more than anything, I wanna help my business leaders make decisions for the future so that they know and are where the hockey puck is going.
They wanna be where that... They don't wanna be where the hockey puck is. They wanna be where it's going. And so I will use NotebookLM to synthesize things like 360 results to great place [00:08:00] to work data, to turnover data, to attrition, to understanding who has bench. And then from there, I can say things like, "Okay, who's the best leader in my company based on this data?
Who's the worst leader? Okay, what interventions can help them go from good to great or best to better?" And really, truly understanding where those gaps are. So I'm not spending my time looking at turnover data on its own, but holistically I can say, "Oh my gosh, the team is saying this about the leader.
We need to help the leader get to where the puck is going." And all of that data ~synch- ~synchronized is really what helps me help my leaders get to a better future state of thinking.
Barb Bidan: Yeah, ~it-~ for a data-rich company, ~the~ the, degree to which AI has unlocked the ability to leverage that data quickly for insights like the ones that you're talking about I think is a step change [00:09:00] for where we're headed. And ~so I~ so let's turn the lens back towards ourselves as HR professionals and our team.
So you have inherently spent your career identifying gaps, skill gaps in other parts of the business and training and developing into those gaps. Let's turn that lens on ourselves for a minute. What are some of ~the~ specific gaps that you think that HR functions have right ~now~ that maybe they aren't even aware of, or if they are aware of, they're not readily admitting?
Miki Virtue: Such a good question. I think that, if we're talking about skill gaps, it really boils down to prompting. I'm not talking about prompt engineering 'cause that's technical, but what I'm talking about today is just prompt fluency. So prompt fluency is knowing how to have a really productive conversation with an AI system, and it really is how to ask better questions.
So [00:10:00] that means pushing back on an output that feels incomplete, or maybe it does feel complete and that's your bias. But how to know when the model is telling you what you wanna hear instead of what you need to hear. And it's kinda the same skill as being a really amazing interviewer except your candidate is a machine and almost nobody in HR is developing this deliberately.
Barb Bidan: .
Totally, right? it's like The probing questions, the follow-on questions, the questions that pressure test. And quite frankly, I think that this is also what requires you to not use AI in a mindless fashion, right? You can't check your brain at the door. You need to be consuming the outputs and then asking another layer of of critical questions. Why do you think that for a group of people who should be pretty good at interviewing, do we not have other places to practice this? Or ~how do we get,~ how do we get better at asking better [00:11:00] questions?
Miki Virtue: I love this question because I actually think it's the one that matters the most. I think a lot of HR leaders spend time diagnosing a problem, and the diagnosis feels good, it feels productive, and it's like progress. But at some point, you have to stop naming the gap, and you have to start focusing on closing it.
And so what I would actually tell someone is not to do a training. This isn't a committee or a task force. What would I tell them is ~you have to pick... ~You have to pick a decision that you make every week. Maybe it's recurring, consequential, maybe it's just an HR decision. And then you ask yourself, "Okay, what data should be informing this that currently isn't?"
Just one. And we're not talking a transformation, we're just talking one decision. And maybe it's how you're thinking about the span of control in a reorg. Very common. Maybe it's evaluating a high-potential employee that's still developing, or how you're forecasting attrition in a business [00:12:00] that, is surprising you.
You just have to find one place that you're currently running on instinct and then say, "Okay, what do I need to know less wrong?" And that question is the beginning of everything. So because AI readiness isn't a destination, it's a habit of mind that you build one decision at a time. And the leaders that I've really watched fall behind aren't the ones who lacked access to tools or trainings.
Those are the ones who kept just waiting for a moment to start, or a program, or a training for permission. But Monday morning is permission. So start with one decision, make it slightly better with data than you made it last week. Make sure you're telling yourself, "Okay, what is the one thing that would make me a little less wrong in this decision?"
And then do it again and again, and that's it. That's the whole playbook. And then the leaders who will be relevant in five years are not the ones who had the most sophisticated AI strategy. It's like they're just the ones who started [00:13:00] practicing the smallest version of it and never stopped.
Barb Bidan: It feels like you're describing a skill of being curious, right? ~It's like approaching~ it's not just approaching questions with curiosity, it's approaching life and your job with curiosity, right? Asking yourself the what if, right? What if we looked at this data this way, what would that tell us?
What is one way we can make this better using data this week over last week? And then checking yourself after, did it actually make it better, right? ~It's, there is,~ it's that natural curious state where~ you are~ you remain curious about, when I take action on a thing in my world, what is like ~the,~ the reaction that it caused?
What's the, the output that I get back? How do I use that as an input to lead to the next thing, is to me, curiosity, which is what we're talking about. But it is w- to hear you describe it, it is simple, yet not everyone is doing it, right? Again, you ~s-~ I liked what you said too about being, we're so focused sometimes on [00:14:00] delivering a smart solution, right? That we forget about being open-minded, to being curious. Do you agree with that?
Miki Virtue: Oh my gosh, absolutely. I think that, for decades, HR practitioners have been taught build the relationship, be really strategic, identify the problems. But now I think it's like we have to shift gears to actually solving those problems. We need to be not focused on designing it, but like actually fixing it, and I think we've just spent way too much time in the identification space, and now, we really need to move into this different environment.
Barb Bidan: I completely agree. So ~m- may-~ maybe I'm gonna put you to work here with this next question. So ~let's~ let's step into that and let's go, okay, so we defining the problem and, you've built the accelerated leadership development program at Albertsons for high potentials supervisor boot camps, like all of the things, right?
So you know what it takes to close a gap not just throw some training at it and hope. So what [00:15:00] would an A- like an AI readiness program for HR look like? What are some of the elements that you would definitely include? if You were me, I'm going to, ~create a r- create~ readiness within my team, what should I be doing?
Miki Virtue: Okay. So ~the--~ as you're speaking, the first thing that comes to mind is data literacy. So to me, data literacy is a symptom. And as I mentioned, HR has spent decades building credibility on relationships and reading the room or knowing your people and, like, all the things about, being valuable.
And I'm not throwing those things out, but somewhere along the way, "I know people" became a substitute for "I can prove it." And when I was scaling Oracle Fusion at Albertsons, it-- the technology wasn't the hard part. The, the hard part was actually getting my HR leaders to stop treating data as a threat to their intuition and start treating it as a megaphone.
Because here's what I actually believe. I think your gut is a hypothesis, and then the data is how you test it. So the better [00:16:00] HR leaders that I've worked with, who aren't the ones who abandon their instincts for a dashboard, they're the ones who, learn to use both, and they knew which one to lead within the room.
And so the deeper gap, data literacy, it's data literacy plus intellectual courage. Excuse me. And so the willingness to say, "I was wrong about this," when the data shows you something you didn't expect, and the willingness to walk into your CFO's office or COO with a number instead of a feeling that's the gap.
And so I don't think that you can close it with a training course. I really think you close it by building HR cultures where being right matters more than being comfortable, and you do that with data literacy. Did I answer your question? That was a
Barb Bidan: a- yeah. Oh, 100%. And but no, and then when the data, right? So when you come in with a gut... your intuition tells you one thing, you check [00:17:00] the data tells you another. I think the other side of that is then the resiliency of thinking to be willing to take a full turn in the other direction if the data does not support your intuition, even if y- you've been operating u- under that same bit of intuition for the last 10 years, right?
It's having that courage to revert and go a different direction because the fact set has changed maybe, or you now have the facts in front of you and you should act in the right way, which is sometimes does require more courage, right? It sometimes is going to require you to say, whether aloud or in your head "I've been doing this wrong for 10 years," right?
And how do you create an environment within your HR team where that's okay as well, which I think is is where the success or failure of the next few years is really going to be.
Miki Virtue: Absolutely. When I look about the different industries that I've worked in, so I worked in manufacturing, I worked in QSR, grocery and [00:18:00] now I'm in financial services. It's like same problem, but different costume, right? Like in manufacturing, the gap was dignity. People on the floor had been told for so long that the job was their hands and not their minds.
And then, like, when you go to try to develop them, they don't trust it. So leadership development felt like a trick and a cultural catchword, right? And someone was about to ask them to do more for the same pay, so the skill gap wasn't really about the skills at all. It's about rebuilding the belief that growth actually ~available--~ is available to them.
And then, like in QSR or restaurants, the gap was speed versus depth. And so everything in that world moves fast. Everything, every metric revolves around speed. So decisions are made in seconds. Turnover was, like, brutal. Like triple digits in some places. So then you end up with these leaders who are really incredibly good at reacting, and then they're [00:19:00] completely underdeveloped at thinking ahead.
The skill gap there is strategic patience. And teaching someone who's been trained to put out fires and how to prevent them, like in financial services and insurance, the gap flips entirely. So now you've got really smart, credentialed people who can think 10 steps ahead, but now they struggle to make a decision without perfect information.
The skill gap is decisiveness. Again, tolerance for ambiguity, learning that good enough to move is sometimes like the most strategic choice you can make. And then like in grocery retail at scale, the gap is translation. You have these very enormous, diverse, distributed workforces, and the leadership pipeline looks like nothing like the front line.
So then the work is nothing about building bridges, it's just like getting leaders to actually see the people that they're leading, not as head count. And then as humans with real capability, that just hasn't been unlocked yet. So [00:20:00] the same problem is everywhere. At the root, yeah, it's like the same problem everywhere.
So every single one of those gaps really comes back to the same theme. In my mind, people who haven't been given permission to believe that they're capable of more, the sector just changes what that permission needs to look like.
Barb Bidan: Yeah. I love that so much. I wanna try and put that back to you ~in,~ in like the form of a curious question, right? Or maybe like a statement and a question that our listeners can go back and and take away with them. It's like your environment is absolutely teaching people just by virtue of that environment, like existing, right?
Like you take the
QSR example, right? It is training people to overdevelop certain muscles, right? Develop certain skills, right? Like speed in the case of QSR, and then asking yourself though what gap that creates on the other side, right? When we overdevelop this [00:21:00] muscle, what is the sort of counterpoint?
What is the thing that now we are creating as a gap because we've over-trained this one piece? Is... that I love when a guest offers something where I'm like, "Huh, that is like, I love your curious question caused me to, like the wheels to really start turning ~here~ here for me. Our guests, or our listeners, sorry, really love practical advice.
And they love being able to put things into play and into action quickly. So I'm wondering if we've got an HR leader listening and they're being honest with themselves and realize, "Okay, like I do have a readiness gap and I want to do one thing differently on Monday morning," what is an easy place for them to start?
Miki Virtue: So what I've been talking about this podcast is really three things. It's trust, it's belief, permission or curiosity. And so you gotta trust that the organization would invest in you and your team, not to just extract from them, [00:22:00] but you have to build the belief that your teammates are actually capable of more than their current role requires.
Permission from their manager, their culture, sometimes themselves to be a beginner again. So if you can fix those things, the skills will follow.
Barb Bidan: I love it. I have enjoyed our conversation so much. I'm gonna bring us home with the lightning round, so just a few, like, super quick-hit questions to get your hot takes on a couple of things. So what is one AI tool that your HR team is actually using today?
Miki Virtue: NotebookLM. We use it to synthesize tons of data, tons of qualitative data, engagement survey comments in environments, interview feedback, listening sessions. I look for patterns and themes that would have taken my team weeks to analyze, NotebookLM
Barb Bidan: Awesome. I do think ~LL-- ~it's not the first thing that everyone names, but every time I've used NotebookLM, I've been like, "Oh, I'm sleeping on this [00:23:00] tool. I need to remember to use it more often." So thank you for that reminder again. So what about the HR skill that barely exists today but is gonna matter most in three to five years?
Miki Virtue: Prompt fluency. So knowing how to have a really awesome conversation with an AI system, asking better questions, pushing back, really understanding what the model is telling you. Like I said, it's the same skill as being a really amazing interviewer.
Barb Bidan: Got it. What about one HR practice that you think AI should replace as fast as possible?
Miki Virtue: The annual performance review.
Barb Bidan: Like
cheers, cheers from the crowd, cheers from the hiring
managers, Cheers.
from the employees, cheers from the HR team. Why do we still do this? I don't know, but I'm with you. I- we could probably spend a whole hour talking about replace it with what, continuous ongoing feedback, like always knowing where you stand in the eyes of your manager.
I'm fans of those. Yes, I'm with you. Let's get rid of that and make that a better process that delivers what it's supposed to. What is something that your T-Mobile [00:24:00] or earlier training years taught you about building capability that you still apply today?
Miki Virtue: Yeah. I just, I think people don't resist learning, but they do resist feeling incapable. I think the design question was never like, "How do we transfer knowledge?" It was more like, "How do we make someone feel really capable in the first 10 minutes?"
Barb Bidan: I love it. I love it. So I try to do my best as I'm talking with guests to try to a few takeaways for listeners. So let's see how I did. Obviously curiosity was gonna come up, so I've got understanding, like the need to understand what people are curious about. And I loved your comment that AI rewards curiosity and punishes certainty. And so remembering that approaching AI transformation with a curious mind is critical. I feel like the second takeaway kind of ties to that a little. I taglined it as culture matters, right? More now than ever. Psychological safety, an environment where risk is tolerated, an environment where we can learn from our mistakes, so i.e., mistakes not [00:25:00] punished, and we are allowed to iterate and get better. I loved the prompt fluency focus. Prompt fluency really just means learning to ask better questions. And I liked that you equated it to similar to really great interviewing skills, because secretly I would also love it if we all were much better, more inquisitive interviewers when it comes to hiring. So I'll take ~the, the dual,~ the double dip there. And then if we were gonna do... So I got four here actually. So the fourth one is if we were gonna do an HR development program, where would you start? Key skill of data literacy, could not agree more. And then learning to better balance our intuition and balancing that with the data to make doing the right thing the thing that we strive for, not just the thing that feels comfortable.
So hopefully I did an okay job of synthesizing all of the great thoughts that you had to offer. But I like to leave guests with the final word. Miki, what would you say to a listener who's been listening to us on their ride home. What do you [00:26:00] want them to carry on thinking about for the rest of their drive?
Miki Virtue: Yeah, I was thinking about this. What I would really like to leave you with is never confuse your comfort with the status quo for competence.
Barb Bidan: I love it. And I love it, and I'm gonna wrap us up here, and I'm gonna be thinking about that for the next 20 minutes. So ~hope-~ I hope everyone is too. I don't have a drive home, I'm here, but everyone else can be listening to it. It was so great to meet you and talk to you today. Thanks for joining me on the show.
Miki Virtue: Thanks for having me, Barb.