Carlee Wolfe - The Future of Work, AI and HR

[00:00:04] Welcome to the HR Data Labs Podcast, now part of the Work Defined Podcast Network. Join us as we explore the vital role of compensation, strategy, data, and people analytics in navigating today's complex business world. With the resources of Work Defined, we're now bringing you deeper insights and actionable ideas from top experts. Now, here is your host, David Turetsky. I am your host, David Turetsky. And like always, we bring you the biggest, brightest, most wonderful people inside and outside the world of HR.

[00:00:34] Today we have with us our BFF, Christy Brown from Hyatt Hotels. Christy Brown, how are you? I'm excellent. Thank you for having me. I love the intro from David to David, but also there's like a seriousness of welcome to the chat. Even though we're serious, but not serious. Oh, not serious. There's just a vibe. There's a very, we're gonna learn some stuff today vibe.

[00:00:59] Oh, we are. We are. And before we get to that stuff, Carly, for those people who don't know the wonderfulness that is Christy Brown, can you give a little bit about who you are? And what do you do at Hyatt? I certainly can. So I've been with Hyatt for about five and a half years. I currently lead our talent and org effectiveness group. So for us, that's TA Ops, leadership development, performance management, colleague listening and our opportunity youth programs.

[00:01:26] And we serve our global hotels. And for fun, folks not familiar with, I'm sure everyone knows Hyatt, or I hope they do. But fun fact about our industry is a lot of hotels are franchised. For us, that's about 50. 50% is franchised, which means our work impacts about 110,000 people around the world. So a couple people.

[00:02:16] For sure. My most interesting fact that I learned and most favorite fact that I learned both sit in those camps. My favorite fact is the, you mentioned, just in general, people in society and life. I'm very broad. My interpretation of that is what I love about the industry is the hotel's ability to impact and be a part of community.

[00:02:36] Right. And I mean that both in an operational sense of what's the art in the hotel to how do you engage? So like community development, also things like at the government level, how are you bringing in events to cities, right? All these things. Sure. And then my most interesting learned fact, and I think is what drives or continues to have me love the space is you, I think about hotels as travel, which it is obviously people are traveling.

[00:03:03] But when I was visiting a hotel when I first started, the GM said something very powerful, which is what you have to remember is that everything that happens in someone's life happens in a hotel. Marriage, death, illness, tragedy, engagement, work.

[00:03:23] I just got to get away for the weekend. I'm here for work. All of those things happen within the context of a hotel. And so when you think about servicing that, it's quite diverse and important, as you said. So those are. And you and I both, we've both been to conferences that take place in hotels where, so there's a lot of education that goes on in hotels, entertainment that goes on in hotels, whether it's comedy clubs or whether it's a bar or whether it's restaurants, those are all entertainment.

[00:03:51] But also, you know, there are venues, right? There's lots of things that happen, like you mentioned, births, deaths, yeah. And I was also thinking about. I said sleep, toothbrushing. Exactly. Laundry. But I was also thinking about the fact that hotels are major employers and like there are a lot of people who make their living, you know, not just going to hotels, but being at hotels and actually working in hotels.

[00:04:17] So it serves the local market and serves the local community. Oh, also, they buy a lot of local foods and produce, I imagine, as well for the restaurants and the food services. So there's just a lot that happens when a hotel comes to a community. Exactly. Here's your other fun facts of Hyatt's for headquartered in Chicago. I don't know why we're like, usually I'm not on like a big hike, but today we are around like. You can be, yeah. Hospitality. Hashtag Hyatt. Reflections. But I love this other one.

[00:04:45] So in Chicago, which is where our headquarters is, and that's where I'm originally from. So let's like tie in a personal point to this. One of our large Hyatt Regencies is there and is the only kosher hotel that you can have in the city. So if, for those that don't know Chicago, there's a, what makes the city very clean is that when, now we're getting to Chicago. Very quickly, the whole city burnt down from the great fire. When it rebuilt, they built like a very intentional structure.

[00:05:11] Part of that included having streets and infrastructure underneath the city. And so Hyatt Regency has layers, like five, six, eight layers underneath it. And in one of the floors, so it's a whole dedicated floor. Everything is kosher. Wow. All of the equipment, which it has to be, right? Equipment, storage. Rabbi comes in and performs the service there. And so if you have a large family and you want a kosher wedding, that's the spot. Bar mitzvahs, births, deaths.

[00:05:41] Exactly. The whole thing. The whole thing. So that's just an example to your point. And I'm a kosher. I'm kosher. So that would be perfect. I'll stay at the Hyatt next time. There you go. So, yes. I actually think I did because one Passover, I had to be in Chicago for the HR technology show. And I think I stayed at the Hyatt because they actually had kosher meals. Kosher for Passover meals. So there you go. There you go. There you go. Thank you. Thank you. Fun fact. There's another example. Fun fact about Hyatt, but not fun fact about Carly Wolfe.

[00:06:08] So we actually have to do the what's one fun thing that no one knows about Carly Wolfe again. Even though Carly's been on the program, she probably gets her jacket, her golden jacket for being on the program for as many times as like Jerry Seinfeld or somebody has hosted Alec Baldwin. It's hosted Saturday Night Live. Oh, I need. Yeah. What an HR jacket would look like for times on a podcast. I'd probably just send you one of these because I have. I love a hoodie.

[00:06:38] I love a hoodie. OK. OK. Fun fact. Fun fact. I don't know. I'll just share one that recently came out because we just didn't know what I'm going to do this team exercise. I've been both skydiving and bungee jumping, but I don't think I need to do it again. But someone, we were playing this game where you were trying to guess who it was. You wrote like three things that people didn't know and they were guessing, but you couldn't ask like a word that sat in there. So like you couldn't have asked me like bungee or jump.

[00:07:06] The person came up to me and said, do you have a passion for extreme sports? I was like, like as a hobby, like in life, what are we talking about? And I knew what she was asking me, but I was just being that person. I was like, no, no hobby. I think just young, young and adventurous would have been my answer in that case. But that's those those are two fun facts. Wow. Wow. I've jumped to stay on the ground. Well, now I am because I'm older and have more fears. And smarter. And smarter. And smarter.

[00:07:35] Because, yeah, I just saw I forgot where it was. A bungee really didn't happen in a park somewhere where it like flew off the side. And I'm like, I'm good. I'm good. You know, remember my friend Dwight? My VFA. Yeah. Yes. Awesome. He loves jumping off of cliffs with a thing. And I hated it. Like a hang glider type situation? Yeah, like a paragliding thing. Or paraglider. OK. Yeah. I don't know how he does that. I have a friend that lift jump dives.

[00:08:05] I don't know. Yeah. I don't like it either. But I'm a goalie. So what do I have to say? I have pucks shooting at my head at 100 miles an hour. So. Oh, that's scary, too. Yeah. That's my goalie helmet right there. Oh, cool. Very cool. I have two right there. But anyways, so that's that's good. We like that. So now we know much more about Carly Wolf and the Hyatt Company. And you. We just learned about goalie. Everybody knows I'm a goalie.

[00:08:31] I think I've mentioned on the show like a million times and people are like, well, please don't mention that you're a goalie. You have new people all the time. New people all the time. Maybe I do. That's true. For your new listeners. That's true. And we get to talk about much cargo today, too. Yes, we did. We learned a lot. And we haven't even really gotten started. We're nine minutes in and we really haven't gotten started yet. Thinking that. Yep. So the topic for today about that is things that Carly things on Carly's mind for 2026.

[00:09:01] And, you know, when we were talking about this program, we tried to come up with different topics. But the one thing kept coming back to the things that was shocking Carly for 2026. So after the bump, we're going to get into it.

[00:09:30] Are you an HR or talent leader trying to figure out how to have the biggest impact on your business and your people? Listen, you're busier than ever, but you're also under more pressure than ever before. The We're Only Human podcast has been running for over 10 years, helping leaders get a handle on these topics. I'm Ben Eubanks, the host of the show, and I started my career as an HR practitioner and executive. Now I run a research firm dedicated to exploring the trends affecting work in the workplace.

[00:09:53] We cover research from a practical lens, technology changes, compelling case studies, and more so that you can get back to work and have the impact you've always wanted to. And we do it with some fun. Check out the We're Only Human podcast today. So getting back into it, the first question that we have to ask Carly is what's on your mind?

[00:10:21] What has been rattling around up in that brilliant space between your ears that has just been driving you a little mad? Oh, driving me a little mad. I think it's, you know, one thing that is always rattling around in my head is kind of like this problem is the state of broad future of work. What's happening with AI and disruption? And where is HR going with all of this?

[00:10:47] And I think that recently I've been, I'm not saying this is like a large theme or the thing, because also this is from one person's perspective. But what I've heard a few instances of is putting, already putting containers around AI to, that like prevent, and I'm going to, I use the term AI broadly. So like, let's just use something simple, like an LLM, like a chat GPT or copilot or cloud.

[00:11:13] But putting guardrails around it or containers that prevent people to have access or ability to use, when it could, one, be really helpful in their job. Or perception of, I don't know if this is like legacy work thinking, our own control. But the idea of like, I think like job, applying for jobs, I've heard this a bunch of times where people are just really frustrated at people using AI to apply for jobs. And I don't understand why that's frustration for people in HR. Yeah.

[00:11:43] Why don't we go through one first? Because I think it's really... Yeah, let's do one. Those are like two. Yeah, let's do it. Where do you want to go? I love the conversation about guardrails because one of the bigger problems I think that I have with it, guardrails of using artificial intelligence at work, is that it's kind of like when Steve Jobs first brought out the iPad and said, you know, here's an iPad, here's a tablet. Now, tablets weren't new at the time.

[00:12:12] But, you know, the criticisms were, well, it's just a big phone. And some of the criticism coming from shareholders were, why did you do this? Everybody's doing it. There's nothing new about this. And they said, what's the use of it? And he said, I don't want to figure that out. I want the user to figure that out. So in the context of what you're mentioning about guardrails and putting up guardrails on people's use of AI,

[00:12:34] why would you do that if we haven't even seen or scratched the surface of what people might be able to use it for, other than just a replacement for certain work streams? Yeah. Why would you do that? I don't know. I mean, the two things I hear are one, cost. Because if we, first of all, take something away, it costs less for us. In theory, right? Literally from the easy, oh, I used to pay a thousand dollars for this and now I don't.

[00:13:03] And misunderstanding of what we label as performance. Like those are the two things I've been hearing. Yeah. And I also want to also like, because I don't, I think you and I maybe are in an assumed space for this. Because what I want to share is, I also don't, I think guardrails, because it could be used in a lot of ways. I think it's important for things like privacy, like not, like thinking about good data, how we're consuming. Right. Ethics, all of those things. I think those all require guardrails.

[00:13:31] What we're talking about is, I'll use an example that someone gave, which is, oh, we're measuring performance based on AI adoption and usage. And if people aren't keeping up with that, we're thinking they're not really performing that well. And so we turn their access off. And I'm like, well, to your point, why would we do that? And that to me is a big number one misconception of what are you, what do you, when you say performance, what are you even talking about? If you're just talking about how many times they opened it or how often, how long it's open.

[00:14:01] What if they're just really good and they can get stuff done in 10 minutes and someone else takes 20. Is that what you're saying is better performance? I don't know. But what I do know is by turning it off and not letting them use it, they're certainly not going to be able to keep up with what is performing. Or. Or they're going to just find a different tool. They're going to use a consumer base. And what does that mean? That means they're going to be dumping your intellectual property into a. A potentially public space. Yes.

[00:14:30] Where better, better you understand what they're doing. Leave it on versus having them go and say, well, I found a tool that I like. It's not yours. And I don't have guardrails on it so I can do whatever I want in it. That's not good. For sure. And you're highlighting something I've found fascinating that I have thought about for myself just at that point. Because there's a lot of commercial tools that I use personally that we don't have access to at work. And I don't. I don't cross over. Like I do try to.

[00:14:59] I do have the wall. I understand it. But if someone looked at my AI usage and depth at work, it would not be the same as if you looked at it my whole life. So one, I think that we're assuming a lot of things about what, in quote, performance is or what impact is. Just that's just an example. But I also think it's still this early stage of we're in adoption mindset, which is did someone log in and is someone using it? Versus what are we gaining from that usage?

[00:15:28] How do we help people continue to learn and feel comfortable and use it for what they need? So there's a lot underneath there that's assumed that by taking away, to your point, there's risk of people using things outside. By taking away, we're also, if they're not going outside and they're just not, then they're probably not performing as fast as everyone else because literally you've taken and maybe taken an accelerator away.

[00:15:51] But the other thing, and I've been very passionate about this since the beginning, which is access is the root of being able to move forward. If you don't have access to something, you are inherently behind. And why would we want limit access when we're really, to your, again, your point, we're just beginning. Why would you want to create that gate? Basically, that has, you know, impact in many, many ways down the road, too. I think there's another problem with it, which is that if you haven't trained them, and this is your area, right?

[00:16:21] If you haven't given them the skills necessary to be able to really take advantage of those tools, how are you, are you going to expect them to be able to really be able to play the system to its advantage? Or are you expecting them to DIY?

[00:16:42] And then, I mean, there are different levels of aptitude on computers, much less on AI, especially nowadays. You can go and take those courses on Google, you know, from prompt engineering and whatnot, or on prompt engineering and whatnot. Different people will be able to react differently to those trainings. You have to find the right training for the people for the right way.

[00:17:07] And so I guess my point, Carly, is if you're giving it out to people, don't treat it like it's so damn obvious that everybody will just get it. Give them the tools to be able to use the tools that you're giving them because it's expensive. And it's not a good idea to just throw it out there and go figure it out yourself. That's just not a good use of time. For sure. For sure. I have been...

[00:17:33] Using this metaphor for a little bit now, which is put yourself in like a large gym. And I call it back of the gym mentality. And so like when you walk in the gym, the first thing you see are the machines, right? Stationary bike, stationary bicep, whatever it is. Right now we're in the sort of assumptive space around AI, which is like we implemented the biceps. And so now people are going to go do biceps, which is fine. It's something. But what we all, most of us tend to avoid is the back of the gym. And like the people in the back, they're like climbing on the wall and doing the jump ropes on the slack line.

[00:18:03] And they're like partly moving. You're like, what's happening? Although you look very fit and I would never climb a wall. But it looks sort of interesting and fun, but not today. Also, I don't know what I'm doing. We, organizations, but that's what AI is. You have a back of the gym. You have these tools. You have a wall and you have a jump rope and you have these bands. But it's not linear. It's not the machine. It's not sitting down and it's one solution. You're like, okay, what do I, I want to work on mobility. How do I do that with the tools that I have in front of me?

[00:18:30] So when we start, you need, organizations need to be able to build a culture around, have someone in the back of the gym come over and be like, hey, Carly, let me show you the jump rope. Or Carly, you did a really good job just even like exploring the medicine balls today. You didn't touch them, but you were out there. Great job. Right. Or you watch this, you walk through, you join us for the 30 minute intro to the back of the gym class and we got you going and now you're doing that at home.

[00:19:00] And you don't need to be climbing the wall yet. Like you could just pick this up or I'll go. This is, this is metaphorically training, reward system, capacity. So how do we do that versus what we started with, which is putting it in containers? So what we've said is because you haven't approached the back of the gym or perception that you're not in the back of the gym, we're going to drop this giant clear wall over the back of the gym, which means you can't get to it. You can kind of see what's going on over there.

[00:19:25] And by the way, we've like maybe left you with your stationary bike, but no one's in the front of the gym anymore. And you're like, what am I doing here? This is sad. So the whole. I love your metaphor. I think it's a wonderful metaphor. And I'll throw a different one in. There's also a difference between Ibex bikes and, you know, pick another bike. I don't know. But there's lots of different types of bikes. So Claude is different than Perplexity, which is different than ChepGPT, which is different than MLs and other things.

[00:19:52] So if you're getting access to the gym and you see all these different machines, but they all and some of them might actually be in the same row and they might do something similar. There may be differences between how each one actually acts. So the concept of if you learn one bike, you've learned them all is not exactly true. And so even if you whether it's hiring, whether it's training, whatever, even if you believe that someone's got all the skills, they don't. This is such a new area.

[00:20:22] Yeah. Don't assume because we know what happens when we do that. Yes. Yes. Yes. And that gets to your other question, because I think we've knocked this one down a little bit. Let's talk about the other question that you had when we first started talking about this, which is the concept of the hiring and the expectation that people either are or aren't using artificial intelligence in the hiring process. Because we've kind of set the expectation that if you're using, you're losing.

[00:20:52] Yeah, for sure. I mean, the system has been placed for a long time. Everybody's wondering, like, well, first of all, it's a frustrating experience. But also then there's how do I beat the ATS? Right. Or at least the AI in the ATS. And now and now and now they ate all of it. Right. So that was like a first 18, all of it, all of it cooked in. And I find it so fascinating that people get upset about people who are applicants that are applying that use AI.

[00:21:20] And they're like, I use I like filter it as a sense of character. And I'm like, what do you mean? Like what? I understand if they have submitted a resume that is a lie, like that is a sense of character. They didn't review what they're submitting or maybe they did. And they're like, this is so good. I applied to be a marketing manager, but I've sold myself as a vice president of marketing, even though I've been doing HR my whole career. Like that, I get that. But just pure play. I'm qualified. This is who I am, what I've been doing.

[00:21:49] And I use tools to help be crafted in a way that I could AI to AI, which is algorithms and keywords, which drives the algorithms. Like why wouldn't? Why? Why put that a barrier or over assumption that someone's unethical because they use a tool to get through the tool? Because then you actually don't even talk to them if you can use the tool to get through the tool. Exactly.

[00:22:12] Don't you remember, and I remember this very clearly, which is when AI first started really making its appearance, the place that it made it the most is in education. And especially in secondary higher ed, there was a lot of talk from teachers as well as from students that in order to be able to get optimum grades, you really need to use the tools that are available. And they were using artificial intelligence to try and simplify their lives.

[00:22:42] Well, I think there was that pushback initially of that's cheating. And I had conversations a long time ago, maybe four years ago with educators who said, yeah, that's cheating. And there are standards and we have to enforce standards on that. Those aren't available. I mean, those aren't around today. We're not talking about that in the cheating way. Do you think this is just another way for us to point to it and go, well, they're cheating. It's the same kind of educational paradigm? I think so.

[00:23:11] I think at the root of it, a lot of it's like misunderstanding and miseducation about what the tools are or why the tools exist and how we can work with them versus trying to fight against them. I think it's the same thing as an employer or an HR. Why are we upset about applicants? Well, maybe we should start to understand that more so that we can solve for it. But same thing with education. Maybe it's a lack of understanding. Certainly in education, there is a very high standard of your work, your originality, your rigor. It is your work. First of all, that model has been challenged for years.

[00:23:41] I used to actually work for Apollo Group, which on University of Phoenix was one of the first online institutions, actually was the first online institution. And when that started, it got so much slack. Like, is this education? Could people even learn in this way? And think of what that did, because the reason why it existed was for working adults, people who wanted to pivot from one career to the next. Why are we getting, again, why are we upset about it? But why are we wanting to put a box around it? People want to get jobs. So same thing. Well, then the pandemic changed that, didn't it? Oh, yeah.

[00:24:11] Oh, for sure. And even, yes. And now we're even in a different stage. I think tech changed a lot of this because Google was like, why would we go to a brick and mortar when tech's moving faster than that? So, yes, I think it's very similar. And I think it's, the question is, how do you use it as a tool? Teach people to use it as a tool, number one. And number two, also, I think, I say I think, because we're talking about this very interesting topic. Education is a pipeline into jobs. Like, it's a big pipeline system.

[00:24:40] And so why would we want to limit the skill set, confidence, and mindset of using the tools that will exist when we go to work? So I think that's another reason. Exactly, Carly. Because if you want people to have those tools and to utilize those tools, why would you have this fake, what's the word, disgust? That they use the tools that you're hoping they use when they're productive in the role. Why would you have that disgust?

[00:25:08] And why wouldn't you have the embracing of it? Because if we embrace it during the hiring process, don't we think that's exactly what we want to try and achieve throughout the rest of their careers with us? Yes. Because if you say, well, you can't use it during the hiring process, but we really want you to use it during the rest of your existence, what kind of precedent are we setting there? Yeah. Yes. I agree.

[00:25:34] And I was just, as you were going through, I was just thinking too, I think this is both of the examples we're bringing up are also examples where I think that we're talking about like what's changing in jobs, what's changing in education, what comes next. I think these are the questions that come next. So for example, let's go back to academics. Yeah. Right. At one point you were teaching people, how do you do research and how do you name references? Because even when you did references before, as you do today, you had to double check your references. This book may not be super accurate because you got to back up.

[00:26:04] Same things, right? With AI. You're like using as maybe a backbone to expand your thinking. Got to check your facts. You got to reference all of the above. So we're just teaching using a new tool with that mentality. The other thing I hear a lot, I'd be curious if you've had, which is like writing itself, whether it's like typing, handwritten, although this generation probably not handwritten, it's typing.

[00:26:27] So then the question becomes, and this I think is fair, is, well, there's sort of like a mental development or like expansion of like you're using your hands and you're thinking in a way that also just is good vitality for yourself, for your body. And so then if that's where educators are saying, well, like we need to keep them on their toes, keep them healthy. I think the question is, what else should we be doing to also facilitate and move that muscle? So back to your gym. Like we need to get, you're right.

[00:26:56] Maybe we need to get on a different bike, but is the bike the problem here? Like, is this what we're, are we really trying to say you have to, you can't use AI to help write things? Or are we just, or are there just other ways we need to solve some of the now impacts that AI is by using a tool facilitates? Yeah. I like to come back to the example or the argument that why do you care how they get to the end as long as the end result is good? And as long as the end result solves the problem, why do you give a crap?

[00:27:26] You know, why judge them? Or is it a case of, I don't want to say holier than thou, but is it a case of the, we have to care about how you get there and we have to judge the case on its merits?

[00:27:48] Because if we, if we allow them to just do whatever they want, we're setting up the wrong expectations for their working with us. I want to thank Carly Wolf for joining the HR Data Labs podcast again. And this has been a really fun episode, but we'll have to pick this up in the next conversation with Carly Wolf. Thank you. Take care and stay safe.

[00:28:17] Thank you for listening to the HR Data Labs podcast. Don't forget to hit subscribe and share it with your network. You can also check out the recordings on Spotify or the HR channel now on Roku and Fire TV. Thank you. Take care and stay safe.