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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 - Yessica Perez
Recorded 2026-10-09
Barb Bidan: My guest today is Yessica Perez, Chief People Officer at Reach Hospitality Group and Ojos Locos Sports Cantina. Yessica has more than 20 years working in HR and has led people work in very fast-moving frontline businesses. Ojos Locos has nearly doubled its footprint since 2022, so super quick growth, growing from 18 to 35 restaurants. So Yessica's work sits where growth, labor pressure, customer experience and frontline execution all meet. When Yessica and I spoke before recording, what stood out to me was not a generic AI readiness story. It was a sharper challenge to HR leaders. For years, right, we have been talking about getting a seat at the table. And what I loved is Yessica had a point that once we have it, we need to continue to earn that seat at the table. And that means understanding the business, understanding the P&L, what marketing does, what finance does, the operations problems we're trying to solve. So I am really, really excited to have you as my guest today, Yessica. I'm excited to talk to you about what that means for HR to contribute in this next era, not just from an HR lens, but as a business leader. So thank you so much for coming on the show today.
Yessica Perez: Thank you, Barb.
Barb Bidan: So I'm going back to that line from when we spoke before the show. You really commented on how, as HR leaders, we have been spending years asking for that seat at the table. And in this moment, we have it, and we need to continue to earn it. What does that mean from your perspective right now? What does that look like?
Yessica Perez: Well, yeah, I do want to reference it, and I'm laughing because I've gone to conferences for twenty years, women's conferences, business conferences, saying, "HR, you need to fight for your seat at the table." We have that now, right? But to answer your question, that means understanding the business. You have to understand the people running it, the numbers, the operations, where we're headed. And more importantly, it also means not being told what to learn. You've got to find out. Businesses continue to change: technologies, our markets, where we're going, where we're headed. You have to know that. But looking at AI and the technology, we shouldn't have our CEO tell us, "Go learn that." No, we have to stay ahead of it. We need to know what's happening with AI, how it gets implemented in the day to day. Because if you don't have that knowledge, you're going to be the person they're not asking how to redesign things; you're going to be the one reacting to it. And that's not what you want. So one of the things that I recently did is I joined MasterClass Executive AI, which was phenomenal, Barb. I didn't expect it to be as good as it was on the AI application, but it's helped me tremendously. So going back to that seat, personally for me, it's taken me years to get here. But now that I have it, you have to continually earn it and provide your value to it.
Barb Bidan: I love it. And what do you think HR leaders risk in terms of credibility loss if we aren't focused on the business, right? If we get too caught up in the policy stuff and HR programs, what do you see happening to the way the business views us?
Yessica Perez: It depends on our framing. As it is, many times we get the bad reputation. I even see it on TV all the time. I recently saw it in Ted Lasso. When people think HR, they're like, "You're in trouble." So many times they see us as the box checkers, the people who always say no. So it's our framing when we go into these meetings. Instead of saying, "You can't do that because you're going to break this policy," or "No, you can't do that, it's against the law," we can't approach it in that manner. We need to lead with the business outcome. "Okay, if we do this, these are the penalties, these are the potential risks. What I'm recommending is we reframe it this way." So we're not leading with the policy, the no, the violation. You're bringing something significant. You're saying, "If we do this, this is a potential risk, but let me help you with it." So I think it's how we frame things and how we approach it. And more than anything, before you jump into bringing solutions, have a solid understanding of where people are coming from, and knowing the business is part of that.
Barb Bidan: It's so funny that you mentioned the pop culture reference. Last night, literally, on The Daily Show, there was a "call HR" joke, and it might as well have had a police siren behind it for what the reference was. It was like the policy police, and I'm like, I roll my eyes every time I hear that. So you are speaking to my heart here on being business-focused. So in your business, what does that look like when you or your team are truly contributing to executive conversations, operations conversations, business conversations? How does that show up practically?
Yessica Perez: Well, I have a good example. When we entered California, which was recently, a couple of years ago, that was our first time in the California market. We had been set up, or were designed, for Texas or other states, but as you know, Barb, California...
Barb Bidan: Very different, California and Texas, I will say. I'm in Texas too.
Yessica Perez: I love Texas. So California, it's traumatizing, especially with the employment laws, the application, their PAGA claims, which we need to do a whole podcast on. They're tremendous. So since we're going into the market, recruitment, construction is ahead. Our CEO wants to open earlier, and it's understandable. A week earlier: the sooner we open, the sooner we make more money. So I can't raise my hand in these meetings and say, "We're not ready." Because what's the response? "Be ready." Right? "Figure it out. Be ready."
Barb Bidan: Right, figure it out, right? Good luck with that.
Yessica Perez: And if I were to approach it by saying, "We're not ready," it's like HR is holding us up. So again, it's the framing. So in this case, I said, "Okay, well, we don't have these systems in place. If we launch now, this is the potential risk. This is the potential cost. And what you forecasted we would earn earlier is going to crumble, and it will double. So it's not worth the effort yet. How about we do this, this and this?" So in this case, the opening was postponed for a week and we were in a better position to open. You don't want to be the barrier; you want to be the solution. So that's one example, because when it comes to these rooms, anyone can get to the room, anyone can be in the room. But your presence should make the decision better.
Barb Bidan: I love that so much. And you didn't say no there, right? You needed to maybe redirect, but you framed it in the business reality. You still got them from point A to point B by offering a solution, right? All of those things are the counterpoint around how we show up and still do the things we need to do in our job, which sometimes is helping the company not be put at undue risk, right? So we still need to do that. But what the business does not want to hear is the HR police putting up the barrier. Instead, you offered a solution. And I think that's the name of the game when it comes to being business-oriented. You also were pretty direct in our earlier conversation that HR cannot just understand HR, right? You talked about needing to know what marketing is going through, what finance is going through, what the business is measuring, how the P&L works, et cetera. A whole list of things we could go through. Why does the AI evolution we're going through raise the cost of not knowing the business for our teams?
Yessica Perez: Well, because before, we had tools to enhance, but AI is completely changing the landscape. For example, with marketing, AI can cut their marketing campaign work in half. When it comes to finance, closing the books, they can do that in half the time. So what's going to happen with the rest of the time? That means we need to start redesigning roles and skills, and quickly. I know we talked about this. If not, people are going to say, "I don't need this person," but you really do. So it's really important, because AI is changing this landscape, it's changing the skills and the roles, that we understand it so we help with the redesign and we're involved in it.
Barb Bidan: Yeah, we must understand the work. And even within our own teams, when AI impacts our function, if our teams don't understand the business, it will be a legitimate question: what are we bringing to the table, right? There are so many administratively onerous jobs in legacy HR that are going to be lifted off our plates, and then what? I think the gap in business knowledge will be so much more obvious as that starts to happen. How do you think about building business fluency with your own team, without pretending to be a marketing expert, for example, or a finance expert? How do you get your team doing that?
Yessica Perez: So what I do is I ask a lot of questions. And you have to also be humble with it, right? I have a few examples with finance. The gentleman who led our finance department loved Chick-fil-A. So I would say, "Okay, Bruce, here's your Chick-fil-A. Can I have 15 minutes? This is how I understand the P&L. How do you view it? How do you understand it?" And I have to be understanding of his time, because he's extremely busy. So it's 10 to 15 minutes every period, and we go through it together. So I go to the experts and I ask them, "How are you seeing things?" Because my role is to help them and to advise them, especially on people strategy. You cannot do that until you have an understanding of what's working well in their department and what's not, the pain points, right? Because we're there to be a partner for them. I will say one of the biggest things that has helped me in operations is, of course, working with the operational leaders, but also getting to the field. I love working with the frontline workers and frontline leaders. That's where I've had so much learning as well. And another element: sometimes what you find is there's always a gap between the leader's intention and the employee experience. So my role isn't to come back to operations and say, "Hey, you guys are doing this wrong." It's, "This is what I'm seeing. How can I help you?" Understanding their landscape. Now, for my team, it's the same thing. I want my team, especially when I think of our business partners, to know their regions. They've got to know their numbers. Which stores are struggling? Where are they against the P&L? What's their turnover? What are our people like? Who did we put in place? And they do that. One thing that came to mind, Barb, just going a little bit sideways: this week, California again, Barb, by the way.
Barb Bidan: We love you, California, but yes.
Yessica Perez: So we were meeting with our legal team, and we were covering five different cases in California. Our legal team is talking about defense and what's here and what's there. One of my business partners jumps in and she's like, "No, this happened with this leader, and this happened with this store, and this store was struggling." The point is, she added so much color, so much reasoning to every case that they requested a follow-up call with her. That gave me such warmth, because I know she knows her people, she knows her numbers, and she has a solid understanding of what's happening. There was one point where she said, "The store was struggling here. So this is why the leader said this in this way. And this is what I've done to correct it." Having the ability to contribute so significantly is because she knew her numbers, she knows her people and she's there. So anyway, that was pretty remarkable.
Barb Bidan: Well, that idea of us being both, the words that came to mind are, a connector and a translator between leadership and the front line. Because we're one of the few functions that have that up-down visibility, our ability to play that role and make those connections, help those dots be connected, is massive. And it's not everyone in the organization. In fact, it's few people. I was trying to think of who else. I don't even know if there is another function that's got that up-down visibility that can help bring those things together when there is a disconnect, or I think you used the word mismatch, right, between the employee's experience and leadership's expectations or intentions. When there is a mismatch, how do we connect those two things? So you were the second person, by the way, that I've heard compliment the MasterClass AI programming. And you gave a great example from that coursework using ElevenLabs. You had a bit of a shout-out, something you created with ElevenLabs. Can you share that experience and what you learned through doing that?
Yessica Perez: I'm a little giddy about it. I created a commercial. Me, a commercial. I'm completely not tech-savvy. I'm not a marketer. But with ElevenLabs, you can create so much. You create a commercial. You could just say, "Put a Ferrari in the NASCAR 500," or, "I want this person walking in saying this." It's amazing what you can do. Some people spend millions of dollars, or hundreds of thousands, on commercials, and you can create a basic commercial with $100 or less. So to me, that was pretty incredible, what's out there and the capability. And more than anything, for me, it's a first look at how things are changing, tremendously and fast-paced. So I've done one, now I want to do two or three.
Barb Bidan: I was so impressed that you did that. Because you said you need to know the business, and then you started describing that to me. And it's like, no, you actually went and learned to practice a marketing skill using AI. So not only do you now know a marketing skill, but you've also learned one of the ways AI tooling can be disruptive to your marketing team and how they might be using it. It was win-win. It was a very impressive example.
Yessica Perez: No, that one was extremely fun. I did one, and now I'm doing another one, and I need to stop at some point. But it's one of those things where you see what you created and how easy it was. Going back to the MasterClass AI, we also had somebody called Parth Patel who showed us how to read data and how to pressure test data, and I learned tremendously from that. We had hired a third party because our sales had been down, and they were giving us their perspective on what was happening. I pressure tested that against AI using what they taught us, and it's fascinating. So now I use that even with my own theories and hypotheses and how I do work. So AI, if done well, is there to enhance. That's pretty much what I wanted to cover.
Barb Bidan: So you mentioned the actual dollars, right, that would be involved in creating a traditional marketing campaign versus what you did with the ElevenLabs experiment, and you could do it for $100 or less, right? You probably could have done it for free at pretty low quality in terms of assets. But drastically different. So in a mid-market company, where resources are more constrained, how do you think AI levels that playing field? How is it putting things in reach that were out of reach before?
Yessica Perez: You don't have to have the resources. You don't have to be a big company with infinite pockets. It levels that playing field, because we don't have the bigger team, we don't have the money, but AI lets you play bigger. And that's the distinction.
Barb Bidan: Right, totally. It's democratizing so many things, right? And that commercial example I just thought was a really good one. A mid-market company is not historically going to be producing ads that look like Nike's ads, a brand that's known for its branding and the caliber of what's possible. With few resources, now it is. And I think that applies well beyond marketing. It applies to our teams all across the board. Things that might have felt out of reach for smaller teams or companies with more resource constraints don't feel as out of reach. So you had a good example about using AI to pressure test a third party's explanation of a sales decline. Can you talk about that example and how you leveraged AI to really dig in and do something different with the data you were looking at?
Yessica Perez: Yes. I think it's using AI, but also, going back to this MasterClass, it's your approach to things. So I'll walk you through my project, which, by the way, I passed. That's why I'm talking about it.
Barb Bidan: A-plus, gold stars.
Yessica Perez: I know. So what the third party had told us was reasonable. Okay, it makes sense, but really, how have we tested it? So I got that data, then I got some of our recent data. Now, on that recent data from the company, I scrubbed it, I changed names. I need to talk about the importance of this: I do not want anybody taking their company data and uploading it to AI. There just have to be guardrails. So I need to emphasize that for sure. I modified our data so there weren't any identifiers. And then I went to public data, like Bureau of Labor Statistics data and restaurant statistics. And I said, "Okay, here's all this data. I need you to review it. Ask me clarifying questions. And give me your thoughts: is this hypothesis true based on the actual numbers that you're seeing?" And then you take it a step further and you say, "I need you to check the integrity of the data. Does it make sense? Are there any holes? Is anything not reading correctly or misinterpreted?" That can happen anytime, especially when you have board decks that are 90 pages, right? Is it correlating correctly? Then it gives me its reasoning as to why. And then the final step is to open a new chat: "I need you to act as my adversary. Poke holes in this. Is this reasonable? Does it make sense? And what do you recommend?" It was incredible, what we found on the data. It was about 60% accurate, in the sense of saying, "What they advised you here, here and here has this percentage of accuracy. This one doesn't make sense, and this is why." So now I want to approach everything that way.
Barb Bidan: Totally. What did that teach you about taking AI outputs, or actually not even AI outputs, recommendations from experts, at face value? How are you thinking about that differently from doing that experiment?
Yessica Perez: Well, obviously I'm not going to be able to check or test everything, right? But it made me rethink things, especially in my work. I ask it to argue with me, and I think it's making me better and making me sharper. Going back to that table and being in that room and contributing: anytime we're going to make a big decision, a big people decision, anything that has a financial impact, we should be checking that data.
Barb Bidan: Yeah. And I think the other takeaway is it's easier now than it ever has been to perform a validation step, right? It would probably have been unrealistic in the past, when you hired an expert to do a thing for you, for you to be cross-checking that. You'd sort of expect the expert to have done all of that work, right? But your ability to go back and validate that quickly, because you can't do a deep dive every single time, is a good lesson for what we consider to be expert and how we pressure test for better answers, not only from the humans who are giving us answers, but also from the outputs we get from AI. So something that I have noticed you're doing, and I love it, is that every time I hit you with an AI question, you bring it back to some of the human obligations we have as leaders, right, as we're moving through this transition we're experiencing right now in the working world. You were really careful in our prep call to say that it's important we as leaders don't treat AI as a replacement story. So how are you thinking about leaders' responsibility when it comes to AI rollout, how they talk about it, how they do it?
Yessica Perez: So we know AI can replace quite a bit of routine work and it saves us time, but somebody still has to check that work. You have to double-check and question it. You have to know when it's wrong. And that's where people come in. So we also need to realize, as leaders, that our people are the ones who are going to be checking it. We have to help them with how their judgment adds value and help them grow with that, whether that means reskilling them or having different perspectives. But it's very important that we understand AI saves you time; it doesn't replace people. It's a tool that we're using to enhance, because no matter what AI spits out, people still own the outcome. As leaders, even though we're using AI, and even with our team, you could never go back and say, "AI said that, it's its fault." You own it. Same thing with our team. So our role is, one, making sure AI doesn't replace our people; they work hand in hand with it. And then also, as leaders, understanding that we own the outcome. It's never going to be "AI told Yessica" or "AI suggested this to Yessica." It's "Yessica delivered this." So whatever we're delivering, whatever judgments we make, we need to make sure they're accurate.
Barb Bidan: Totally, right? AI has become this easy scapegoat: "AI replaced my job." And your point is well taken, right? That is not a narrative that is helping us. As leaders, if we're redesigning roles because of AI, it's our responsibility to teach our teams additional skills, like the judgment you talked about. Do you have any point of view on how HR can help teach people these additional skills they're going to need when their administrative work is something AI can now handle? How are we going to teach judgment?
Yessica Perez: That's a great question. It's looking at the data, because for the judgment, whatever it spits out, I believe experience is going to tell you if it's correct or if it applies. So one, you're going to be looking at your people's experience and saying, "Hey, does this make sense?" You also want your people to be fine-tuned to what's going on out there. So use that time that AI gives you: go to the field, work with your partners, get a better understanding of it. So on the judgment piece, for you to have good judgment on items, you have to have a solid understanding of how things work.
Barb Bidan: Exposure. I'm with you one million percent, right? And that's where the leader's role comes in too. We touched on this: leaders own that responsibility. If you as a leader have the judgment that the person on your team doing administrative tasks hasn't had to have in the past, how do you create exposure to you so that you can impart that judgment to that team member? I think that's the name of the game as we move forward. I am having so much fun having this conversation, but people do not love an hour-long podcast, shockingly. So I'm going to bring us to the lightning round. It's a round of questions we do at the end of every episode with every guest, so just quick-hit answers to these. What is one thing you personally now do differently because of AI?
Yessica Perez: Pressure test my findings.
Barb Bidan: Awesome. Take that extra step to validate. Fantastic. What is one finance or ops metric that you think every HR leader should understand? And it's fine if it's specific to your business.
Yessica Perez: Labor cost. Labor is the highest expense on the P&L. So as an HR professional, you need to know what percentage of sales that is. You've got to know your labor cost. That being said, knowing what your sales are and knowing your EBIT, how much gets taken to the bank, is in addition to that. But you said one. There are just so many to pick from.
Barb Bidan: That's okay. I like it when we get a bonus one. And honestly, that theme has come up: you must know how your company makes money, full stop, right? Regardless of your role in a company, you should know that. I think that's something we absolutely need to hold our teams accountable to understanding: how we make money. So I feel like I might be able to guess the answer to this one, but you've been doing a lot of experiments, so I don't know. What's one AI experiment that has made you more optimistic?
Yessica Perez: That commercial. I keep going back to it, but I need to move on, right?
Barb Bidan: You're a marketer now. You're going to get an award soon for that, I think.
Yessica Perez: No, not at all. Not at all. Our marketing team is wonderful. I just think their world is pretty great. So that commercial, for me, but I probably will move on, because there's more to do with AI.
Barb Bidan: Yeah, when something makes you go, "Wow, I just did that," it makes you realize what these tools will be able to produce in the hands of actual experts, right? Because you weren't a marketing expert on that. Imagine.
Yessica Perez: Imagine. Yes.
Barb Bidan: When you have those wow moments, those are the things that make me really optimistic about where this can take us over the next 10 years, or the rest of our working lives. So the next one is: what is one HR habit that is overdue for retirement?
Yessica Perez: There are several. Measuring training by participants. Because when people show up and say, "Compliance, everyone showed up to training," to me it's like, you don't measure attendance; you measure the application of what was taught. So it's not, "Yes, they passed this easy four-question quiz that, guess what, you can take again and again until you get 80%," right? It's really the application of what was taught, and you don't see those results until down the line. So I think measuring training that way isn't necessarily truthful.
Barb Bidan: Good one. Perfect plug for monitoring outcomes over activity in general, but that's a really good example of that. So complete this sentence. This is the last one. Having a seat at the table means blank.
Yessica Perez: Being curious, being kind and being humble.
Barb Bidan: Awesome. I always try to do justice to what we've talked about by doing a bit of a recap for guests, and I was having so much fun during this conversation that I hope I got a few good takeaways. And I hope these are a little bit of a novel way to think about some of what you said. Near the beginning of the conversation, you talked about learning the business by asking for just 10 to 15 minutes of a leader's time. And that resonated with me because I do that too. And never once in my career, which is long at this point, have I had a leader say no to that. So it is so easy to extract learning from the experts in the business who can teach you about the business. So I just loved that: just ask for 10 to 15 minutes to get something explained to you by the expert. And if you do that routinely, you're going to know so much about the business. So that was a huge takeaway. And our listeners love practical stuff too, so that's something they could go do tomorrow. I also really loved this idea of how our teams, when they're deeply embedded with the business, can be the connector between the frontline and leadership in a lot of ways. You talked about when there is a mismatch between a leader's intentions, maybe with a decision, and the experience of our frontline workers. Our teams are one of the few teams that have the up-down access in an organization to be able to close that gap and make sure there are not so many mismatches between leaders' intentions and our team members' experience. So I loved that, because that's a way we can add massive value, right? That is a way we can change how the business runs, how effective things are, how fast leaders' intentions actually get put into practice, when we can make sure that mismatch isn't happening. And then the last one that I want to offer back: at the very beginning of the conversation, we were talking about policy and programs, and how we need to be more embedded with the business and use our seat at the table. And you were telling a story about how, effectively, I hesitate to say it this way, you say no to something. But what you did was you didn't say no, right? And I think if more HR professionals thought that way, that our job is to offer solutions. It doesn't mean we are not there to also help mitigate risk, et cetera. But the point is, you gave an example where you got the business leaders from point A to point B, which is what they were trying to do. So you solved the same problem; you just gave them an alternative way to get there. And to me, that is the counterpoint. That's what we should do instead of showing up as the policy police. That's what that looks like: get them from point A to point B, even if there's a slight detour along the way, but demonstrate how it still gets there, and gets them there better and more effectively. And then you haven't said no at all; you've said "yes, and," and they love that. So I do not want to take the last word. We always like to leave guests with the last word. For the chief people officer or people leader who's been listening to us on their drive home, what do you want them to continue thinking about for the rest of their drive?
Yessica Perez: Take care of yourself. Your role isn't easy and people depend on you. But for you to be your best self, that means taking care of yourself, getting enough sleep, doing whatever you do to de-stress. Take care of you so you can help others.
Barb Bidan: Always good advice for our friends and colleagues. I had such a good time talking to you today. Yessica, thank you for taking your time to come on the show.
Yessica Perez: Thank you.