#278: The Leadership Playbook Has Changed with Kelly Monahan of Beyond the Desk

Kelly Monahan: Like when you think about management, you know, anyone who's got an mba, it's based on this theory called agency theory, meaning we don't trust people want to work in the first place and they're never going to work for shareholder profits. And so that's how we got this whole command and control, really transactional style of leadership. And I think AI for good or bad is causing us. Is that really the path forward? There's no way that's a sustainable path forward.

Narrator: Guided by over 25 years in the data and research industry and assisting innovators with investment banking and advisory services, Sima Vasa brings you Data Gurus, a leading market research podcast that offers actionable insights for business acceleration and value creation. Join her as she speaks with key innovators in the space to bring you up to speed with the current state and the future of data analytics and data ecosystems. This is Data Gurus need support on your market research projects. Paradigm Sample is a full service market research solutions provider. Whether you need help with questionnaire design, survey programming or online data collection, we are ready to assist. Paradigm can do as little or as much as you need, saving you time so that you can focus on insights. Learn more@paradigmsample.com

Sima Vasa: welcome to another episode of Data Gurus. I'm Seema Vasu, your host. I'm so excited to invite Kelly Monahan, who is the co founder of beyond the Desk. Kelly, welcome to the podcast. We had you on I think a few years ago and I'm so glad to have you back again.

Kelly Monahan: Thank you so much.

Sima Vasa: Yeah, it's, it's been. And you've also had a lot of um, change in your life. I mean we've talked about the last time we spoke, we talked about um, workforce trends and you were full time somewhere and now kind of launched your own practice and business.

Kelly Monahan: Yes, yes. So I think the last time we spoke I was um, just transitioning out of Meta. I was their first future of work, researcher, director, great experience, spent time in the metaverse, realized there wasn't enough people in the metaverse to study, so made the transition to upwork and started their research institute. Because we were studying the impact of AI, ah, was having in the freelancer market. So got four years of an in depth view of what AI is actually doing to jobs, jobs and tasks. And it just got to the point, I don't know if you're feeling the same way that it feels like the Runway is getting shorter for actually getting this moment right and so it just made sense. Um, I had the right co founder to come alongside of me and just take a chance and actually start helping and advise leaders as they're going through tremendous m amounts of transition today.

Sima Vasa: That's amazing. And, and when did you found the company? Was it just November?

Kelly Monahan: Yes, November of 2025.

Sima Vasa: Wow. Good for you. It's amazing. And, and you also move locations you move from. Yes, right. That's a big change.

Kelly Monahan: It is a big change. I mean listen, I gotta practice what I preach. I'm all about accelerating through change. So here I am. Um, yeah, I along with like millions ah of other Americans relocated from the Northeast. Uh, New York and Philadelphia were not quite the same during the pandemic. And uh, Florida ah, alert me so no state income tax beaches. I just like I'm gonna start living my best life now.

Sima Vasa: Good for you, good for you. And so now you're working on um, content related. I know your new book's coming up but just tell us a little bit in terms of where your focus has been since you founded the company.

Kelly Monahan: Yeah, so it's funny, uh, the new book coming out is called Reclaim the Plot. But my focus right now is because I think we've lost the plot of what business is all about in a couple of different domains. One, I think AI is actually causing a pressure test to ask us what is the purpose of business? Is it truly pursuing shareholder wealth maximization at all expenses which we're seeing right now with AI development. And so I think that's we've lost the plot a bit of where we're going with that. The second thing is how we're showing up as leaders every day. There is no leadership playbook when you're having to deal with five to seven macroeconomic shocks in one year. I mean that's just unheard of. And so really focus on how do you help leaders navigate this new playbook that's required because it's not linear growth. A SWOT analysis is no longer going to make sense. And as a quantitative researcher I'm even humbled like we're moving into pure qualitative realm right now because looking back and even getting survey data is becoming too outdated. So I'm really helping leaders navigate AI and more broadly the complexity and the final theme I'm focused on, I love Gen Z. I think they are going to really shake things up. Um, I think we're beginning to see some things and yet they're coming to the labor markets with really poor early entry pathways of really I think a lot of delirium and confusion of what's happening? And so spending a lot of time of, of how do we get Gen Z back in the workforce and onboard it quickly.

Sima Vasa: Very cool. Let's talk about the first point. First, just, uh, you know, the history of the purpose of business. I know we've talked before and saying, you know, business has not always been the way that we see it today in terms of shareholder maximization at all cost. Maybe I'm being extreme in saying that, but before, I guess the 70s, there was a different kind of playbook or philosophy as to, um, why businesses exist and what their f. Focus or foci.

Kelly Monahan: Um, was.

Sima Vasa: Is that right? Focus. Plural. Yeah. Anyway, yeah, so tell me a little bit more about that because I don't think people fully really realize that.

Kelly Monahan: Got it. Yeah. I think to your point, we just have accepted it like business is just all about shareholder wealth, profit, and we move on. So before, um, the 1970s, business had more of a stakeholder approach, meaning the purpose of business was to also serve local communities. Like, I'm from Rochester, New York. Kodak may be a bad example because they didn't keep up with the times. However you go into. I went to Rochester Institute of Technology, there was an Eastman Kodak investment endowment ready to get business students out. There was an Eastman Kodak ballpark. There was just an, uh, investment in the local community, into the workforce. And so you saw during the 50s and 60s a much more balanced approach to business and who they were serving. And at the end of the day we're serving customers. Right. And so you want to make sure you're showing up in a way that is aligned to customer value. But something happened in the 1970s with an economist, Milton Friedman, who wrote in New York Times op ed. It was an opinion piece. It wasn't even like an academic journal.

Sima Vasa: Wasn't a book.

Kelly Monahan: Yeah, it wasn't a book book. And he wrote and convinced a, uh, whole doctrine of business by saying this exact line in the New York Times, which is, it is the moral responsibility of business to maximize shareholder max, you know, profits. And that a whole bunch of universities, MBA programs took that as this is the new way forward to infuse growth. And honestly, like we have, like, when you think about management, you know, anyone who's got an mba, it's based on this theory called agency theory, meaning we don't trust people want to work in the first place and, and they're never going to work for shareholder profits. And so that's how we got this whole command and control, really transactional style of leadership. And I think AI for, for good or bad is causing us. Is that really the path forward? There's no way that's a sustainable path forward without some sort of frustration and uprising. Whether that's coming from rural communities where data centers are going into rising inequality, mass layoffs, you cannot sustain a level of success and high performance in this sort of environment.

Sima Vasa: Yeah, I mean, I think also the, the, and you alluded to it, it's like the, the concept was that people are inherently lazy potentially, and so they need the oversight and management to ensure that, uh, the return on investment of those dollars that a person was paid could, could again contribute to shareholder maximization.

Kelly Monahan: Yes. And I think I, you know, I'm talking and advise leaders today. I can almost predict their employee engagement scores by asking their leadership team and board, do you trust people want to be at your organization? Like, do you trust people are going to do the right thing? 50% of people in my research say no. Like a hard no. And that to me, I think is we look around and say, well, why does work feel so broken? Well, we've got to start right there. This is a huge mindset shift. If we don't think people even want to be there or to contribute, we're never going to create policies and environments where they are allowed to flourish and allowed to contribute, that sort of thing.

Sima Vasa: So I feel like there was like the heyday, you know, all these corporations, I remember IBM was like the gold standard and everything was going great. Obviously things have changed. Um, obviously the COVID made a big kind of digital transformation and not an office hybrid work. And now we have AI on top of it. Um, what do you think the root drivers are that really are painful? Not painful, but leaders are really struggling with, as it were, as it relates to running and managing a business.

Kelly Monahan: Yeah, I think right off the bat, before we even get into like AI and the people side, most industries today outside of AI are operating in a low to no growth environment. So I think the macroeconomic headwinds have put leaders on the defensive posture and having to explain to their board why profit margins are decreasing. And that's because inflation and tariffs in the macroeconomic environment have just made the dollar much more expensive than it was four years ago. So you could be doing the exact same thing and making less money by changing nothing. And so I think that is the backdrop of where a lot of the anxiety is coming from. The second root cause that I think, and I haven't actually done an official research study, but I'm, you know, anyone out There, who wants to, um, what I am concerned about is during the pandemic, we got into a chaotic mode of operating, mostly because the world got turned upside down. And in some industries it was a life and death situation of what we were dealing with.

Sima Vasa: Right.

Kelly Monahan: My concern is that neuroscience of getting addicted to chaos is what I've seen up, um, top. And I have not seen a slowdown. And if anything, I've seen an addiction to an accelerated speed. And I want to say timeout. The crisis is over. AI is not a crisis. AI is an opportunity. But we are treating it as if it's another pandemic and responding to it in the same way. And then the last thing is I think there's a really bismilled expectations right now between leaders in the workforce in terms of, again, we're talking about the purpose of business and just having misaligned expectations. Leaders today, what I are concerned about are playing checkers and not chess and are just trying to get it through the next quarterly earnings call where workers are saying, what does my next 10 or 15 year career look like? What is my employment looking like? What's my skilling looking like? Two different conversations happening at the board, C suite level and workforce.

Sima Vasa: Almost like leaders are just trying to survive.

Kelly Monahan: Oh, 100.

Sima Vasa: Right. And employees are like, well, if you took that job, that's kind of quote, unquote, not my problem. I'm going to plan my life and I need to figure out what that looks like. Um, I love the analogy of checkers and chess. It's actually really spot on in terms of m. How we look at it. Um, but talk to me about this, because I think especially, like, not especially, but in the research, data analytics space, you know, we do a quarterly pulse among all CEOs in the industry. And you can really, it holds true. People are, um, not experiencing great growth, but they, they are, they are protecting ebitda. Ah. Um, to a certain degree. They're not necessarily reinvesting as aggressively as they normally would because there's just so much political and economic uncertainty. How do you not call that a crisis? Because that is scary. Right. In terms of. I don't know what AI is going to do. Do I actually need people to do what I used to do? These processes are getting turned upside down. So I'd love to hear from you in terms of. Because I do think that we went from COVID and then there was a heyday for a little bit, and then since then it's been flat in terms of, um, not everybody, but general business Performance.

Kelly Monahan: Oh sure, absolutely. 90% of industries, um, almost everybody. Yeah, I mean I think that's a fair point, a fair push. Um, I think we're at this interesting time where because to your point, uncertainty is what's actually before us. Uncertainty at almost every level, whether that's a societal level, government level, the way that we show up and treat each other, everybody, like things have just begun, really uncertain. My concern is, I believe AI, ah, is going to be very transformative for sure. Like hands down, it's going to change the share of workers in terms of what we need for knowledge workers. I mean we're researchers. I mean talk about probably we're going to be honest. 30 to 35% of my job I run now through AI agents where it's helping me with qualitative research, design, surveys, all that. Don't worry, I still have humans in the loop. But the reality is I'm like, oh shoot, my job is already turned upside down in a matter of a couple years. But I still have a hard time as we start to look at the actual economics of AI and there was this great Wall Street Journal article today actually on this, where the cost of AI is still very expensive. All the token costs are now coming to hit companies and saying Uber is the one that's all in the headlines right now. They blew through their AI budget for the year and four months. And so I think to your point, what I see it as more of like what we have a problem of, of leaders not having courage and conviction to stand by their core business model. This is the value we do. Here's where we need to change. And it's almost as if like the panic and crisis has become the core and not in the peripheral. And I just, I don't see a world changing that quickly and dramatically where all of a sudden there's a 25% job disruption the next 18 months. I actually think AI is being used as a scapegoat for bad leadership decisions and bad business strategy during a pretty turbulent time where there's a lot of headwinds. I just have really, really rarely see a, ah, one to one substitute where it's like, okay, maybe I don't need a team of 10 researchers, I need seven or eight. It's going to be that sort of math.

Sima Vasa: Yeah, yeah, no, actually, you know, when you do scenario plant planning, I think the thing is, is that you know, prior to AI you did scenario planning and there were external factors that you could control, but you could predict a little bit. Like you could look at Historical interest rates you could look at. Right. And I think, um, the part that's different now is being able to predict and rely on historical kind of performance to then determine what am I going to face going forward. Um, and I'm sure we'll get there. We're learning a lot. I think with AI, my perception is it's been hugely, um, uh, talked about and I feel like there's a bit of settling in terms of, well, is this actually better or what? What's the critical reasoning around this? Like it's, it's a cool shiny object, but I don't know if this fits the use case in this scenario. I'm hearing a little bit more of that now.

Kelly Monahan: Oh, absolutely. And like, I know we talked a little bit about, you know, the 1970s. There's a different way to do business. AI has also been around since the 1950s and it's already gone through two to three hype cycles where back in the 60s we thought everyone's going to be, not need to work anymore. Robots would be doing all these things. These are some very smart people who made these predictions. Like Nobel winning economist, the guy who started mit, um, AI lab, Media Lab. And so it's, to me, I think that's why, you know, when all this panic was happening, I'm like, okay, well I think life is cyclical and I think business operations are cyclical. So we're in another cycle of AI now. Has AI made leaps and bounds in a smaller period of time? Absolutely, there's no doubt about that. But I do worry a bit to your point. There was a lot more hype as opposed to how this was going to actually transform. And this will take probably seven to 10 years for most businesses to fully get the ROI and the investments they're making today.

Sima Vasa: Yeah, no, I agree with you. And I also think, um, because we're also connected, we feel it more like if you look at 30 years ago, right, you got a newspaper that you read and you watch the news like on three channels or whatever that might have been, but now it's like you're in it. It's that chaos that we're a little bit, we, we keep getting dopamine heads about the world is kind of like totally radically changing in front of our eyes and a sense of, I don't think hopelessness, but a sense of like what, what else can I be doing to kind of. We all know this 100%.

Kelly Monahan: Yeah, I think that's spot on.

Sima Vasa: So, so tell me a little bit. I mean, we've talked a lot about Gen Z. Um, and you know, I hear the remarks in, in terms of the typical stereotypes and I'm sure your research points to some of that. But how are they showing up to work? And, and what are some of the challenges that you're seeing with Gen Z or N opportunities?

Kelly Monahan: Yeah, you know, I think, you know, as an elder millennial, like I ran on the cost of in a millennial Gen X myself, um, I remember, you know, 20, 25 years ago when we came to the workplace, it also felt like all these stereotypes of like you guys just want ping pong tables and beer kegs and your avocado toast. And it was like, actually we just want to be treated like a decent human being. But okay, um, but I think the reality is like, you know, as I Look back now 25 years ago from when I was entering the corporate world for the first time, here's the difference in the data. 30% of them aspire to leadership positions, meaning 70% are looking up and saying not worth the peg, not worth the chaos. You know, like, not for me. So I think from uh, climbing the corporate ladder, I'm not seeing that same one, I don't think that pathway exists to many degree the same way it did maybe for us. And then two, I do think Gen Z is really not thinking it's worth it in many ways the way that we've designed leadership today. The other stat that's like super depressing is only 48% of uh, gen zers actually think business is doing good. And so 52% are really actually concerned that they don't think corporate America is moving in the right direction. It's actually something they are willingly opting out of. And so to me what I see is more of when you kind of talk about crisis is an identity crisis for organizations. Like to your point, IBM, I couldn't wait to get a job at Deloitte Accenture Meta, like these were the big brands and now I'm like, you know, with my nephew I'm like, I don't think I would go there, like go like I would actually recommend something smaller. And I think that's what we're going to start to see is the future of work is much smaller. Um, because I don't. The economics of a big business no longer makes sense with AI and so I think that's part of anyways, you know, we can talk a little bit about that. So with Gen Z, it is a total upside down world they're entering into and I think we're going to see a lot more entrepreneurship. I think we're going to see, honestly, a little bit different pace and tone and style. And I think, you know, I work with a lot of baby boomer leaders. It's. It's foreign, it's bizarre, and they think it's rude behind closed doors. And so we've always had a generational gap, but in this particular case, I think we have a chasm, um, because boomers are trying to hand the baton off and saying, look at. This is legacy. This is great. We're doing great things. And you've got a generation saying timeout. I'm not sure the planet's gonna even be around in 50 to 70 years. Like, I don't know. I'm, um, I'm into this game here. And the last thing I'll say, like, the one phrase that I find really interesting to hear from my gen zers when I do research is they're not into the corporate theatrics. And so they think a lot of what we're doing in a leadership perspective is performative. It's theatrical, not actually real, and they have no tolerance for that.

Sima Vasa: Yeah. Isn't that interesting?

Kelly Monahan: So I. Oh, I'm, like, kind of jealous.

Sima Vasa: Well, and do you think the convict conviction will stay, like, a lot of, you know, sometimes it's a lot of people, like, uh, oh, wait till they have to go pay the rent or pay a mortgage, and they're going to grow out of this kind of principled life, if you will. Um, what. What do you think?

Kelly Monahan: Yeah, I think. I think there's definitely going to be an element of that. I mean, it's very easy to be altruistic when you don't have $10,000 a month and, you know, bills you're paying. The only. The only interesting variable that we're tracking is this will be the largest transfer of wealth between baby boomers and their children. And many of their children are Gen Z. And so I think the question's going to be, does that principled life persist? Not necessarily because they're making six figures, but because there has been a transfer of wealth. And I think that's going to be, again, as you talk about scenario planning, a bit of a confounding factor to think through. We've never m. Millennials didn't really get handed a bunch of wealth, and so we pretty much quickly got back in line as long with Gen Xers. And so we're kind of like. We've, like, had angst and resisted along the way, but, like, We've still very much been like, yeah, I want that leadership position. Um, so I don't know, I think it'll be telling. It's probably going to be a 50, 50 split and part of it's going to be privilege. Right. Depending on whether or not you're part of that wealth transfer.

Sima Vasa: Yeah, that's interesting. I didn't think of that. Um, yeah. And then, you know, as, as parents do you say like, it's a huge opportunity, opportunity to let your kids go do good in the world. Um, right. And you know, is that a positive thing? I mean, there's all kinds of questions around that. But I do admire, I do admire their conviction. It's, it's quite refreshing. Um, in terms of, yeah, in terms of being really concerned about larger macro issues, 100%.

Kelly Monahan: I was just doing a focus group with, um, interns at a large law firm. So, you know, these are like 20 to 23 year olds who are just coming out of law school or just finishing law school, I should say, and then trying to get to a big law firm. And it was so fascinating because if I think about like 15, 20 years ago, you know, the drive would have been going into corporate law and you know, making money or starting your own private practice. Almost every person, there's about seven people at this roundtable. One was going into energy, trying to solve climate crisis energy, trying to regulate data centers. Someone else was going into much more of kind of a healthcare legal realm. And so it was super interesting. I mean these are the top of the top. We're talking Harvard grads, Stanford grads. And their appeal was not to what I would have thought at that age, if that makes sense. You know, they were thinking much bigger. And I'm like, wow, you guys are really wide awake what's happening out here.

Sima Vasa: I mean, I mean the younger generation also is really, um, strongly concerned about AI and its impact on the environment. Um, you know, I, I get dinged by my children quite often in terms of, you know, do you like your drinking water? Um, you have a role here in terms of how you contribute to the climate. But you know, it's all, it's all learning. Um, so Kelly, tell me, like, I'm a leader, you're a leader. There's so many leaders out there that are really struggling to connect generations, like connect and you know, not. Maybe we've evolved in terms of saying, you know, people are lazy and they need micromanagement, but you want to uncover and motivate Gen Z to kind of come along in terms of corporate goals and, uh, objectives. And I know you work with a lot of leaders. What advice could you give leaders as they think about this?

Kelly Monahan: Yeah, I think, um, I'll give you a preview of what I talk about in my new book because it's called the plot Frame. Okay. So it's called Reclaim the Plot. So it's a plot framework. And here's the four ways that I'm trying to help leaders rethink the way that they're showing up every day, especially with the younger generation. The first is power. And so sharing power and I. That's really hard for us as leaders is because we're, you know, the ones with the power expertise. But the very first thing that AI is going to democratize is our expertise and intelligence. Right. Knowledge. And so it's like, we have to understand our position of power is actually already being somewhat softened with AI, and we have to accept that and share that with the younger generation coming up. Don't wait until 10 or 15 years to start sharing power. The second thing is listening. We have to do a better job listening. And it's not just, oh, let me have a pulse survey, it's what do you do as a leader when truth is surfaced? So as people are onboarding into organization, having a new point of view, and they're speaking truth outside in perspective, how do you respond? And so is making sure that you're listening. Third thing is ownership. It's really beginning to own the outcomes for the next generation and making sure that the decisions we're making today, that we feel a sense of ownership, not just for our careers, but for the people coming up behind us, that's our legacy. And the long game again, going back to the chess checkers, like, let's start playing chess here for them. And then the fourth thing is trust, which we've already hit on. And that is, what if we start from a position of, uh, we're going to trust this next generation is going to do things differently, and that's okay. And we're going to trust that where they're focused on and where they want to go may be the right direction. And how do I, as a leader, help cultivate, Maybe put up guardrails and watch outs from our years of experience, but trust that they are going to lead and usher in a new world of work and that be okay with that. So that's a lot of what I'm talking about in the new book and when I'm on the keynote circuit right now is unpacking the plot framework and Helping leaders rewrite their story.

Sima Vasa: And I guess the fundamental, um, principle there is that you have, quote, unquote, the right people on the team.

Kelly Monahan: Oh, my goodness, Absolutely, yes.

Sima Vasa: Because in a world of AI, I think people are really wondering, like, what kind of talent do I need? Like, what's the role I don't have at the table right now that I might need in the future? And can, can people traverse this kind of ambiguity as part of the team? Um, so go ahead.

Kelly Monahan: Yeah, I was gonna say that's a fantastic point. And I'm just responding because I'm, um, working on a thought leadership piece is gonna be released next month. And it's actually addressing this question of, like, what are the skills? Like, who do I need on my team to navigate this? PwC has provided a really cool framework. They've got 30 skills. They've began to actually track and chart out for human AI collaboration. But I think to your point, it is a combination of technical skill sets as well as scenario planning, strategic planning, complexity. And that's where my concern is. We haven't taught either of those very well in university settings. Everything has been pretty rote. Here's. There's an answer to everything and we actually need a different sort of skill set. Again, I think the freelancer market is a great place to look because anyone who has had to learn how to be entrepreneurial is going to have some resilience and grit to figure things out and deal with. I don't know where my next paycheck's coming from. Um, so that's kind of the mindset though, that you want, you want someone who's thinking like that and not just expected that this is going to happen just because I show up every day, you know, And I think that's probably part of the challenge we've got to overcome.

Sima Vasa: Yeah, it's interesting because I think when we talk about the democratization of knowledge and learning, um, I still feel like there's so many differences that people come to the table with content that's depending on which LLM they're like querying. And so you get to the table and there's like asymmetric information because people have queried whatever their best tool is. And I don't know if you've seen companies kind of create a. I don't want to say governance, because that sounds overarching, but a model where like, this is truth, this is how you get truth in terms of knowledge. And let's work on a common foundation of truth, um, and, and build from there. Have Companies focused on that.

Kelly Monahan: I love that you're pushing on that. Um, the one thing that I'm helping leaders with right now that companies, I think are beginning to realize that they don't have what you just described. And so is principles, um, to at least have a set of principles around to your point, kind of a common vernacular. This is what truth is within our organization. This is how we're going to use the tools. And I think, you know, when you talk about the asymmetry, depending on the tool you use, you know, when anyone asks me, well, Kelly, how would you define AI skills or AI literacy? The very first thing I start with has nothing to do with AI. It's domain expertise. Because no matter what tool you have, if you don't have domain expertise, you're going to end up with wild asymmetry information, and you won't even be aware of that. And that's what keeps me up at night, is how much is being produced. We have a uptick in quantity, and, you know, we're lowering quality. You know, you just go on LinkedIn and you can see it. The second thing is then just having a basic understanding of statistics. All these large language models are operating on probabilities, and yes, they're getting fancier and learning from themselves, but the underlining mechanics still, if you have a basic understanding of statistics, helps demystify a bit of where the probabilities are headed. And then finally, I think where people are going to need to figure out is where do you build your own AI tools and then where do you buy, you know, and I think making those decisions. Most organizations haven't figured that part out yet.

Sima Vasa: Yeah, yeah, I think it's, it'll be interesting because, like, even with prompts, right? Like, if you democratize, let's say, research and people can create their own prompts, they're going to get different results. And so how do you create that common vernacular, even just in market research and the, the historical data of how people query the tools?

Kelly Monahan: Oh, 100%. I don't know if you guys got into this world, but this whole, like, surveying AI agents and using them as Personas, you know, I was talking to my, um, old colleague over at Accenture Research, and he wrote a fascinating piece because they're not performing well in terms of validating and replicating human responses. Like, there's quite, quite a bit of divergence when you do the same survey to humans versus AI agents. And that to me, just is the chasm of, like, why AI? I think there's going to have such a hard time replicating a true human job because we are actually irrational, we're not that linear and oftentimes what we say may mismatch what we do. And so anyways, I think it'll be a really interesting time in the research space. But I'm like, please God, don't have a whole bunch of research come out that's like AI agents is telling us what we want.

Sima Vasa: It's like that many truth. Yeah, exactly, yeah. Um, well, I want to ask you in terms of if you had a crystal ball, which I know you don't, um, what do you think the future looks like in terms of the workforce? Is it less people, more? Give me your own kind of thoughts on that.

Kelly Monahan: I think what we're going to see is a rebalanced workforce. So I think for the last, call it, 10, 15 years we have over rotated towards stem, which has been great. It has been. That's where the premium wages have been. That is where a lot of we tell a lot of kids, go get a computer science degree, you'll have a future proof career. Well, computer science degree is the third most unemployed college degree out there right now if you're 21 and 25. And so to me, and you see all the mass layoffs happening in the tech industry and tech benefited from the pandemic. I mean I was at MET at the time because customer behavior, we had to all move online if you wanted to still interact. So now we're kind of right sizing. And so I think what's going to happen is you've got all this great STEM educated workers and I think the best thing is to go into health care, to go into education, to go into manufacturing, construction, to go into the physical world, industries, retail, hospitality that are evergreen. We will always need people doing great things. And as I think through that, so I see a future where the, the market's going to get labor market anyways will be rebalanced to better match supply and demand. The problem is going to be is do wages follow? Probably not. And so that's going to be part of the rebalancing is what becomes a new premium career pathway. It is probably going to continue to be technology and working with AI. However that that labor share is going to be much smaller. And so I think we look at either optimistic or pessimistic future is how do we deal with an uh, inequality that's going to continue to grow between the small share of workers who work along and build AI products versus everyone else and then everyone else is probably 75 to 80% of the workforce. And so in some ways I'm optimistic because when I work with hospital systems right now, they cannot wait to get this tech talent. You know, they've been waiting for it, um, but they also know they can't pay the same wages. And maybe the long term, that's okay, but it's going to be a bumpy transition.

Sima Vasa: I do worry about the people that are, um, you know, getting laid off and, you know, potentially not being able to get a job and to a certain degree have to retool their skills. And can they retool fast enough to be able to get employment and be able to support families? Because it does feel like the labor market will shrink, um, given AI and technology enhancements. But I don't know where those, where, where the, where that workforce goes.

Kelly Monahan: Yeah, I mean, the only hope I have is like, the ones that I go Back to is 6 out of 10 of us are working in a job that didn't exist before 1940. So 60% of us are in jobs that weren't even created. And so I am still hopeful. It's a little unclear of what that kind of new work is going to look like. I mean, according to my nephew, it's all about like YouTube influencer,

Sima Vasa: right? Yes.

Kelly Monahan: Um, so I am looking to see as much as we're going to have creative destruction is where does the creative value begin to emerge? And that won't emerge if leaders keep using AI to just take cost out of their business. And so that's my other concern is leaders. How do we actually make this a creative opportunity tool, not the creative destruction tools we can see as clear as day. Where is that offset and that rebalancing? I don't see enough people asking that or actually focused on that.

Sima Vasa: Yeah, I love it. And also the other thing is humans are resilient, right? They, they, they, they, they. Do we, we do what we need to do to survive. And so, um, yeah, it's not all doom and gloom to your point. I Love that stat. Six percent of the jobs weren't here prior to 1940.

Kelly Monahan: That's correct. That's correct. Yeah. That's 100% correct. Yes.

Sima Vasa: So. Well, Kelly, thank you so much for joining me. This is fascinating. I feel like I could talk to you for hours about this topic.

Kelly Monahan: Oh, same. It's been so fun. Thank you so much for having me back.

Sima Vasa: And let me ask you, when your book comes out, where can people find it?

Kelly Monahan: Yes. So you can go to reclaimtheplotbook.com um, there's previews out there. Um, you can see who's endorsed all that fun stuff and learn more about it. And by all means, find me on LinkedIn. More than happy to connect that way as well.

Sima Vasa: Awesome. Thank you so much. Thanks for joining me.

Kelly Monahan: Thanks so much.

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