Kory Kantenga: typically for job postings on LinkedIn, we see the median salary range around 80,000. For AI, it's about 177,000. When we talk about how many people are working in AI and taking AI engineering jobs, we're barely talking about 1% percent of the workforce. when we have young people a entering a weak labor market, it can potentially scar them for the rest of their careers. Hi, I'm Kory Kantenga, Head of Economics for the Americas at LinkedIn, and you are watching Macro Talk with Hope King.
Hope King: Kory welcome back.
Kory Kantenga: Good to be back with you, Hope.
Hope King: So we have to stop meeting like this on Friday afternoons in the summer. But there is urgent data that you and I've been talking about in the past. and this report, you know, to me around AI jobs has been very validating around some of the intuition that I felt around the gender divide in the AI, salary gaps. But let's start with just from your perspective. What was the one thing that maybe struck you the most out of all the findings?
Kory Kantenga: For me, the finding that struck me the most was the fact that Young people are actually benefiting significantly from the AI boom. We see that a lot of the new jobs that have been added, two thirds of those AI engineering, machine learning engineering jobs, they're actually coming to Gen Z. It's young people who are taking a lot of these positions. And we even see millennials benefiting. You know, there's always a lot of discussion about millennials and how they've suffered in the labor market and how every crisis seems to hit them at the right time and in the worst way. They've actually been able to step into leadership positions as a result of the AI boom. 60% of the head of AI roles, they've gone to millennials. So that struck me that while we're talking a lot about how young people are. having a lot of challenges in the labor market today and that is true. AI is actually if you are in the AI labor market itself, it's actually a boon for you.
Hope King: That that's pretty counter narrative to everything that we'd been hearing around how AI was impacting entry level work. So square that for for us.
Kory Kantenga: The broader labor market has seen a slowdown. When we talk about how many people are working in AI and taking AI engineering jobs, we're barely talking about 1% percent of the workforce. It's that other ninety per 99% of the workforce that is worried about the potential impact of AI to their job. And we have seen a slowdown among younger workers and entry level workers. On LinkedIn, though, we see that the hiring rate for younger workers is on pace with the overall hiring rate, but both are slow. They have fallen
Hope King: Okay.
Kory Kantenga: 30% since 2022. So this is a slow market that disproportionately affects young workers because older workers who are employed, they can hang on to their job. But if you're young, you don't have a job to hang on to.
Hope King: The age divide in AI is more complex. I'm reading from the report. Unlike gender and education, where the patterns are clearer, generational representation varies substantially by role. And you mentioned the stat around a Gen Z. I'm thinking about the FDE role, forward deployed engineer. There's been a lot of stories written about this type of role, AI engineers, and the conclusion here is that these newer AI roles. maybe providing strong entry points for younger workers. Why are Gen Z specifically positioned to take advantage of these roles in particular?
Kory Kantenga: Part of it is that they are learning these tools as we go along. They're starting out their careers working with AI and having it integrated into their workflows. They're not already trained up to work a certain way, as many of us are. So they don't have to unlearn anything. They are learning AI natively in their roles. And when we talk about forward-deployed engineers, we mean people who are working with integrating whatever software, a tool, or product you have. into the customer zone technology stack. So they're they're very much focused on a customized solution. And they're AI native, they're data native. And so creating these customized solutions, if you or someone who's digitally native and you've built an app in your life, that kind of role is very accessible to you.
Hope King: If we were to Break down this report into like great news, good news, and worrying news, which of these trends would fall into each of these categories?
Kory Kantenga: Great news, there is a section of the labor market that has a lot of momentum that is booming. In a world where hiring is down 25% compared prior to the pandemic, where healthcare added all of the jobs to the economy last year and there's no momentum outside of the healthcare sector for the most part, having an area where there is something that has momentum where there is a boom, that's great news if you are in that area. The sort of so-so news, the good news. That if you happen to be able to get one of these jobs, you were gonna be able to make a good living. We haven't seen salaries increase significantly, but if you are in an AI role, you're probably making double than what the typical worker would make. So typically for job postings on LinkedIn, we see the median salary range around 80,000. For AI, it's about 177,000. That's not going to be true for every single role in the AI economy, but for a lot of roles, it is going to be above that typical pay. So you can expect that you'll get a decent pay. It's a there's a lot of momentum there. You say, well, what's the bad news? The bad news is that it's not available for everyone. If you do not have a bachelor's degree or higher, it's probably not the most successful role for you. On LinkedIn, we do see employers using skills more to vet workers and select workers. But ultimately, Over 90% of the people we see who are working in AI today, they have a bachelor's degree or higher. And in fact, if you're looking For those higher level roles, you might even need a doctorate. 20% of the hires that we've seen for those top AI roles have had a doctorate degree. So in education seems to be a big entry-level filter. So you may need to consider going back to school if you're looking to move up in AI leadership. So that's certainly one of the challenges. The ugly, when we look at how how women are represented and the availability of opportunity, not just from an I can go to school, but even if I went to school, is there something that would still be potentially problematic? we see that there are not a lot of women working in the field. Now, some of that has to do with early in the pipeline, but at every stage of seniority, we see women dropping off. When we look at women working in AI AI companies. In AI roles. They start out at 30%, but by the time they reach the C-suite, it's closer to 10%. So we don't see a lot of representation there. We don't see a lot of momentum at the top of the pipeline. And it's just a significant drop-off by the time we get to the end of the pipeline when in those leadership positions. So while the AI economy is creating a lot of jobs, there are twice as many job postings on LinkedIn as we saw over the last few years. They're Clearly not creating enough opportunity for everyone to participate.
Hope King: How worrisome are these trends? in this specific sector given the outsized impact it has on the rest of the economy, on the stock market, on how other businesses are thinking about their labor and hiring?
Kory Kantenga: It's still a relatively small industry. So while the value being added to the economy from AI is very outsized, the workforce, the AI workforce, is actually quite small. In fact, if we look overall, the number of us who have AI skills explicitly and we explicitly list those on our LinkedIn profile, we're not more than two percent. So even though it is the case that this is a they're very much punching above their weight in terms of the value they're adding to the economy, they aren't having, they aren't. really employing most workers. So from that side, it's not too concerning overall that we don't see a lot of momentum there. But I would still like for it to be the case that everyone would have access to to those kinds of opportunities where there's very strong wages and strong momentum. If it's not necessarily in AI, but in other areas, but we just don't see any momentum there.
Hope King: So the other reason I'm asking about this is because if this industry grows in in impact and in size potentially, this could become a a bigger, more worrisome trend and it could become more entrenched. Do you see that scenario as being very high or low risk in the medium to long term?
Kory Kantenga: It's certainly a concern. There have been concerns voiced already about will AI increase inequality? Will there's be equity issues around that in terms of the jobs that people can access, the work that they can do, the way that the algorithms work. It's much bigger than just the fact that we don't see women able to take on leadership positions in a significant way in AI companies. It's much bigger concerns around equity when it comes to AI. And we would be concerned that if this, if this expands, say the AI industry becomes 3% of the workforce, 5% of the workforce, will that be expanding inequities. expanding inequality? And also when we look at pay, pay is significantly higher if you're working in an AI company. And if that's where all the momentum is, those folks who have degrees, who have higher education are likely to be paid more. That's likely to potentially drive inequality up. But this isn't just a when we think about Inequality and equities. This isn't just a story about AI. What's going on with the other industries? We know that you probably need a college degree to work in AI. You don't necessarily need it, but you probably do. But there are likely other industries where you won't. How are those industries faring? Are they benefiting from some of the boom coming from AI? How is leisure and hospitality doing where most people can start and get an entry-level role? If that industry is not doing well, even if AI wages are flat. even if AI doesn't have any momentum, that inequality is still going to be there because we're just not seeing any momentum elsewhere. So we want to see broad base growth, broad base momentum in the labor market that's going to translate into the economy, translate into broad base consumption growth. And that will support other industries.
Hope King: Okay, I want to go back to the report and talk about the methodology. This data set was drawn from, I believe, from 2023 to 2026 job postings for US listed jobs only on LinkedIn. Is that right?
Kory Kantenga: That's right.
Hope King: and I think across your base of of users, most of your users are in the US. So it's important just to focus on the US. Is that right?
Kory Kantenga: Most of our users are actually outside the US. LinkedIn has over cl upwards of one and a half billion members. Only around two hundred million of those are in the US. So most of our members are actually not in the US.
Hope King: So then can we extrapolate anything from this data to the rest of the world or we should just talk about it from a US perspective?
Kory Kantenga: On the pay side, we should focus on the US perspective. There's a lot of different things we need to consider when it comes to pay. There are regulatory issues in Europe and the way pay is regulated and the way pay is set is actually quite different depending on where you live. Even within the US itself, it can be a little bit different. So from the pay side, we should definitely focus on the US. When we think about the side of who's working in AI and who's not and how they can access opportunities, that's very much global. When we look at this gap for women, that is a global gap that we see across many advanced economies and some emerging economies as well. That women just aren't moving forward into leadership positions at AI companies. And broadly, we don't we of course see this leaky pipeline of women starting out as about half the workforce. And then by the time you get to leadership, they're closer. to 30%, but that is much more severe when we look at the areas where there is momentum and growth, which is AI.
Hope King: And then for the roles themselves, how are you determining which roles are AI? Because a lot of job postings and descriptions now probably use like AI in the skills required. So how are you categorizing it for the purposes of this report?
Kory Kantenga: So you have to first see what are the set of job titles with AI. Then you want to expand that definition and see which jobs are actually had those skills listed. And not just one skill, but at least a couple of skills in order to filter and say, are these AI or not? And then of course we do a manual review to make sure that these make sense, that they are very much aligned with how we see things more broadly.
Hope King: Something that struck me when I was going through the salary data was this idea that The writer Jasmine Sun has been talking about, which is like a permanent underclass. When you look at the salary ranges and differences of AI roles and non-AI roles, Do you feel the same worry? about the potential of some type of underclass that emerges because you have a disproportionate number of jobs that are so high paying in AI and that there's a lot of wealth also being created by the owners, the founders.
Kory Kantenga: I think it's important to break down where some of that salary is coming from. First and foremost, there's an education premium. As I mentioned, a lot of the workers in these particular roles, they have bachelor's degrees, they often have higher education degrees, master's degrees, and doctorates. So they're getting that education premium. And we know that there's a significant premium to education, which is why we keep seeing people enrolling college, no matter how many articles come out about how it's not worth it. And then there's this additional AI premium that they're receiving because this is an industry that has a lot of momentum, a lot of investment. So there's certainly a boost coming from AI, but a lot of that boost as well when you look at these median salary ranges, is for these companies to be competitive with other employers who hire people with advanced degrees. That's really some of it. And if you worry about what are the dynamics that are going to generate a set of people who will be making a lot of money and a set of people who won't. What's the incentives? If the incentives are to go to university, to get a degree, or to skill up and be able to do some of these roles, that's what people will do. And If there are more people who are willing to do these roles, who are in the position to do these roles, that's going to actually drive the pay down in these occupations. So the economy has ways of adjusting. if you incentivize if there's a lot of pay there, a lot of people are likely to move there. That's going to bring the wages down, and that will hopefully compress some of that initial inequality. The question is, how do we set people up for success so that they have access to these roles? it's not a question of should we have these roles or not because they pay too much, but how do we enable these roles, people to join. this particular set of the this labor force and be competitive. If we allow that to be the case, then we are likely to have more pay equity across the board because you will be able to transition into this role. And it'll attract people with higher wages. And by the way, other employers, they'll have to raise their wages to attract people as well. At the moment, not everyone can work in AI. You have to have a particular set of skills, you have to have a certain education level. But if more people can work in AI, if it's more skill based or there's more accessibility to working there, then other employers are gonna have to compete harder for workers and they will have to raise pay accordingly.
Hope King: From your perspective, does it seem like we're at the early stages of most of these cycles where when a new industry, you know, blossoms, you have this high concentration and a small number of people and roles, and then as the industry grows, all of the things that you just said happens and and diffuses.
Kory Kantenga: What we're seeing right now about AI companies is that they're not actually an industry in and uninto themselves. They're spread across multiple industries. There are some that are working in the financial services space. Most companies that we would call AI firms, they're working in the tech space. Some of them are working in the media space. So AI as a concept is really spanning across different products and services. It's certainly a labor market. These different industries are competing for a similar pool of talent. But one of the things we do see is that it is very much embedded in different products and services. It is more of an underlying foundation for a lot of industries. That's what we're seeing happening at the moment.
Hope King: And and that's what a lot of like academics and people who have been early on and trying to kind of quell fears have been saying. It's like this is a tool. Like AI is not some like entity alien that comes in and it's like its own power, right? Is that kind of what I'm also hearing is that it that d the diffusion is already happening.
Kory Kantenga: We actually get to make a choice about how we will and will not use AI. We as an elephant
Hope King: Who's we? See, I I love when academics say we, it's like, but but no, but like who in society has the power, right? Like that's something that I think about a lot is w you know, if enough of us are boycotting against data centers, for example, then then some part of the we is controlling how the AI grows. So I'm always, always curious, like when when we say this very, you know, ambiguous like first person article.
Kory Kantenga: Yes.
Hope King: that that like I don't like who who are those people who will ultimately have the largest impact on the we?
Kory Kantenga: S so getting at what academics mean when they say we, we mean it's a social decision. It's not a decision that that w that is being made aggregated at an individual level. We have social channels to direct things. Part of that is public policy, government policy. Part of that is public and private partnerships, what private and nonprofit entities and public you know, public companies and private companies agree to on together. They can get together as and form civil society organizations to talk about and agree on how we want to handle the AI transformation. So there's the government side, there's also the civic engagement side. And then there is just the general decision about how do you want to use it or not. If you want to use AI in your home, that's a choice that you can make. If you want to use AI at work, that's often a choice that's more in the hands of your employer. And I think that's what you're getting at. Hope is that the employers who are adopting the technology today, they have a lot more decision-making power over how it's used and where it's used. And that is the case at the moment. But as that as AI grows beyond those 20% of companies that l that tell the Census Bureau that they are using AI, once that gets much bigger, it's going to be a broader conversation. You're going to have a conversation that's going to include academics, it's going include the private sector, it's going to include civil society more broadly. And so we'll be able to have a broader conversation about how and where and when we use this tool. And of course, the how you decide to use the tool in your individual life will matter. Because AI is not just the intention is not that it's just going to be something that you use at work. It's also something that you use generally in your regular life. And if we all decide, you know what, I don't really want to use this technology because there are these this this effect and that effect and that effect. And we all Collectively make that decision, that is going to change how these businesses think about what they want to do with AI, how and why. That being said, it is hard to coordinate people. That's something, that's the reality. It's difficult to coordinate people, it's difficult to coordinate decision making. But we do as a society have the ability to make decisions about how we want to use the technology, where we want to use it.
Hope King: I'm wondering how you are reading two very different sets of headlines, If you're if you're enterprise AI, it's like you're just thinking about how you're doing the deals and how you're gonna. implement AI and then if you're on like I'm worried and I feel like I have no power and agency, you're fully on the other side, you know, wanting to like move into the woods and and just be totally off grid. is is that being reflected at all in actual data or is it right now just living in separate narrative silos?
Kory Kantenga: I haven't seen any data about people saying they're moving into the woods, at least not yet. It could be
Hope King: No one's asking those questions. Maybe you should ask in the next one. Idea.
Kory Kantenga: it could be a survey that we do. At the moment, I do think there is a lot of talking past each other. They're the optimists, the folks who are very excited about it. They're really focused on the potential of AI. And then you have folks who are worried, who are more skeptical. We've seen a lot of this at college commits commencements. You have the speakers who were, it's just the microcosm of the of the of the somewhat two sides of you could call it a debate, but it doesn't feel like there's really a debate happening. It just feels like there's two groups of people talking past each other. I think from the side of the group who's very excited and pushing forward and looking at the opportunity, I think the message for them is to take the concern more seriously. What are we doing to prepare the workforce for potential transformation, transition? Right now we don't see massive job displacement due to AI. But but no one has ruled that out. we can't definitively say because we don't fully understand what the technology is capable of, whether it can fully replace a large number of workers or not. We don't know that today because it's still evolving and still advancing. So taking that more seriously, I think, is the message that that group is the the other group is hoping that the Optimus group will receive. And for the group that is fearful. There's a lot of potential there. There's of course broad concerns about environmental impact, about abuse, about trust. And I think that the opportunity there is to raise those concerns. If you're concerned about AI today, you should be raising those concerns and voicing them and providing that input so that we can end up in a better place overall of how we're using it and taking advantage of it in a way that's going to create positive outcomes for a larger group. of people. So I don't have any concerns about people voicing those concerns there. I think you have to also be realistic about what businesses are focused on and what they're doing. They are relentlessly focused on cutting costs at the moment, protecting margins, preserving their market positioning. So the question is how do you then create incentives for businesses to have this broader conversation about impact, about use? about what is going to feel appropriate for a for a particular particular community versus what the business feels is appropriate for itself. How do you work more in partnership and less in competition? So there's certainly there's certainly a discussion to be had here. I just think the the narratives so far have been cast in a way of which these two sides are pitted against each other, rather than having two sides of a debate that are rate both raising valid Opportunities and concerns.
Hope King: I love the way that you explained that. it was is it was very clear and I think you know, I I I I I mean I don't know what else there is to say about it other than I I don't see it moving just yet, but you do see signs of it with some of the CEOs of these big AI companies pulling back on their dramatic proclaiming other dramatic proclamations that there's gonna be massive
Kory Kantenga: I thought you were gonna say Fu Foukovian.
Hope King: no. I I mean listen, I d what what was your reaction when you saw that? I mean you had you had a couple I I wrote about it in Macro Talk. I know that you're a subscriber, so thank you. And you see them saying, Hey, maybe we were maybe jumped the gun a little bit or maybe we are like, yeah, not seeing it in the data. I mean, to to you is that sort of an admission of what you guys have been saying all along? I feel like those voices just get outsized attention and then like conversations like this where, you know, you've been encouraging calm and and just sort of like a patience, they they don't rise right to the top.
Kory Kantenga: Loud voices and alarmism gets headlines. We all know that. So the question is how do we find a way to look past the headlines and try to search for the truth of what's going on? In our data, we have yet to see any evidence of mass displacement due to AI. There are certainly areas that are more AI exposed that are a bit weaker. But by the way, there are areas that are weaker and weakening where there isn't a lot of AI exposure. And it's broad-based slowdown. So it's hard for us to say, well, why is the unemployment rate rising for teenagers? Is it AI? Have they been displaced from restaurants because of AI? Last time I went to a restaurant, I didn't really see a bot serving me. It was still a person. So it probably is much more it is probably is much more broad than just AI. That isn't to say that AI has an effect in the decision making. It's so it's it's it has such potential that of course it probably does. But there's a lot of other things going on besides AI. So I think that's something that we that tends to get lost in the conversation. My job is to focus on what's the reality. And the reality on the ground is that. We haven't really seen much of an impact there. That isn't to say that there isn't potential there for there to be impact, and that's a conversation to be had.
Hope King: let's go back to the data really quickly. You talked about some of the reasons why the head of AI is looking at, you know, like a median midpoint of two hundred and thirty-six thousand. because there's all the premiums of education. And so I guess I wanna just ask you point blank, if you were talking to a younger person today who is contemplating going to college or not, with all of the mixed mixed messages and signals, what is your general advice to those groups of folks who are still on the fence?
Kory Kantenga: Understand the potential payoff and the trade-off. So the potential payoff that you get when you go to college is that you're less likely to be unemployed and you will have higher lifetime earnings. What's the trade-off? It's a lot of time, potentially, depending on how far you go. It's a lot of time that you could be spending doing other things. Maybe there's something else that you're more passionate about that doesn't require you to have a degree that you're more interested in. These decisions are not just about the money or about less likely to be unemployed, when you decide to work and where you decide to work, it is a very personal decision. No one can tell you whether you should or should not work somewhere. You have to decide those things for yourself. It's about what you want, how you what kind of quality of life are you striving for, how is this going to affect your family? Where are you likely to be able to find positions for some people? They want to stay in their hometown. And if there aren't tons of roles there for college degree holders, then maybe that's not the best decision for you. We can make projections going forward based on how we think things are going to evolve in certain occupations. The Bureau of Labor Stystics provides a projection. Going out 10 years to to see which occupations are going to grow, which are unlikely to grow. So you can take all that information and make a decision about whether what a potential career could look like. But that may not actually mean that much because we do see that people are less likely to follow linear career paths now than what they were 10 years ago. A lot of people have changed careers and made career pivots in the younger in the younger generations among the millennials and zillennials. And So your the career path you pick right now may not be as definitive as it was 10, 15, 20 years ago. So in that sense, it the decision about where you actually start out is not may not be quite as deterministic. So you want to just make the decision that's going to be best for you at the time. And it's okay if you don't make a decision that doesn't quite work out the way you wanted it to. You still have the opportunity to. To pivot and move around. Our labor market is quite dynamic. It's slow today, but overall it's still quite dynamic. It's at least in the US, it's one of the most dynamic labor markets in the world where you can start out a career in one position and end up somewhere completely different.
Hope King: you know, as a as an elder millennial at this point, it it seemed easier because the the path was laid out in front of you. And so comparing it to the nonlinear matrix career people are talking about now, like it just seems more complicated, seems a little bit harder, but that's just a a perspective thing for me. you know, where I'm going with this really is if you Think about the level of anxiety that young people do have right now. Like it it it seems to me like they would want a more linear path, or at least like the things that they had s been promised or seen other generations been promised and can follow is gone. And that seems like quite distressing overall. and I do wonder if that like has an effect on the labor force participation rate. There's been speculation about why people are dropping out of the the workforce. and looking for jobs because of this anxiety? How are you making sense of all of the you know, d various and very personal reasons to your point that impact the the bigger pie, the the you know, the greater share of the the labor force?
Kory Kantenga: Well, you don't want to compete with millennials for trauma. I think we have that one. I think we have
Hope King: Accurate. Accurate.
Kory Kantenga: that one won Hope Is there not elder but states states person millennials we could call ourselves if we like. So let's not compete with us for trauma, but
Hope King: Okay. All right. All right.
Kory Kantenga: yes, it is going into a slow labor market, particularly for young people, it is it's not just distressing. We know from research, from evidence that it does have an effect on your lifetime earnings. It does have an effect on the chances of you being employed versus being unemployed, or even the possibility that you would commit a crime in the future. These, your initial starting point in the labor market does matter. Now, the choice of your career is a different question, but generally, if you're starting out in a weak position point in the labor market, that can have a negative impact over your lifetime. So that is important for us to keep in mind. That is important, I I imagine for For folks who are starting out today, they're not so worried about are my lifetime earnings going down. They're just, how do I make ends meet? How do I pay my student loans or at least pay the interest and get some of the principal down? So they're focused on those immediate important concerns around affordability and around creating a life that's sustainable for them. And those are all quite important. And we know from the research that they out that there is a long term impact when you enter a weak labor market. So we should be concerned about that today. it's a really significant issue when we have young people a entering a weak labor market, it can potentially scar them for the rest of their careers. And we should pay attention to that now and think about but but that's why it's so important for us to get it right. it's not good enough for us to just say, it's AI or it's the economy. And and not actually try to figure out what it is or how much it is of each piece. We have to get it right because we can't address it if we don't actually diagnose the problem correctly.
Hope King: so well said and s so many scars. last question on the gender divide. Is this more acute, more pronounced, sort of with the AI roles than the rest of the economy, or is this sort of mirroring what's happening in the rest of the economy?
Kory Kantenga: It's more acute. We see that this pipeline starts out, we have about 30% women. By the end, you're closer to 10%. So 13% of women are working in AI leadership roles at AI firms. When we look at the overall economy, we actually start around f closer to 40% globally of women who are working in positions, and that slows down because we have this leaky pipeline of women, that goes down to about thirty percent who end up in leadership positions. So there is a big disparity between how we look at how we see overall leadership that represent with representation among women and versus within AI itself. So in the AI domain, they are not on par with what we are seeing overall.
Hope King: and last question here. on the jobs report from July, If you had to sum up the state of the US economy or the US labor market, pick one, in sort sort of three big trends that are happening and maybe trends to watch, what would those three be?
Kory Kantenga: Slow. Hiring is slow. It's down significantly compared to what we saw prior to the pandemic, and much more significantly compared to what we saw over the last few years. Employers are being much more cautious. The other trend we see, Unemployment is holding relatively steady. Some of that is that people are aging out of the workforce. Some of that is we don't have as many people entering the workforce. But overall, the people who are looking and who are who are looking for work or who are employed, they are managing to stay employed because layoffs are relatively low. And that keeps the economy going. If we don't have people working, they don't have income, what can you? You have nothing to spend. If you have nothing to spend, that slows the economy further. So that steadiness is supporting. Our overall consumer spending, that's supporting the overall economy. But the third trend, this is one that worries me, disposable income is actually falling. So we've seen consumer spending gr grow quite significantly. It's very robust, but the labor market isn't keeping up with inflation at this moment. Inflation is picking up. The labor market is not provide has doesn't have enough momentum to have To incentivize employers to raise wages. And by the way, most of us don't get away a a rate a raise in our wage in a given year. So the people who are driving that 3% to 4% wage growth, that's not the majority of people working today. That's actually a small number each year relative to the overall population in the US. So wages not keeping up, that has potentially significant consequences. One, if your pay isn't keeping up with what Prices are, and say you have to pay for childcare, what incentive do you have to work? You might as well stay home and watch your kids. It actually might be cheaper, more cost-effective. So we have concerns around wages being able to keep up with inflation. We saw it prior to when we had this big resurgence in the labor market coming out of the pandemic. Prior to that, there was a lot of concern about why is the median wage not really growing? It's kind of flat. And today we're saying, okay, there's possibly a big productivity boom happening from AI. It's not showing up in wages and what people take home. We got a big buffer of savings during the pandemic. We've kind of drained that down. Disposable incomes falling. How much longer can we keep consumption up? Because if we can't, if if consumers are exhausted, If they're tapped out and the labor market isn't giving them enough to keep up with how they want to consume, at some point consumption is going to turn. And that's going to slow things down even further. That's going to harm the broader economy. That's going to harm the labor market. So wages and pay, people being able to keep up there, being able to change jobs because that's how most of us get a pay raise, these things are going to be critically important going forward.
Hope King: Is the K-shaped economy over?
Kory Kantenga: There were always some issues with this concept of case shaped economy that we we don't need to get into today.
Hope King: c wait, we need to get into it in another episode. you never were subscribed to the K shape economy,
Kory Kantenga: Not entirely. Not entirely. It's a little more I think it was a little bit more complex and the data was a little bit more complex. But the K-shaped economy was a nice way of messaging the fact that we did see growth on the high end and slowdown on the lower end. But at the moment it does seem that consumption, at least on the lower end, the lower tiers of income, does seem to be holding up a bit better. Part of that might just be that people have kind of hit the bottom of their discretionary rotation. So there was discretionary income that they were spending before. They've kind of decided how they're going to spend that now. And maybe that's stabilized. But that doesn't necessarily mean that we are going in the right direction. If you have leisure and hospitality, losing 80,000 jobs in June and July, that is a big income driver for those of us who aren't making as much money. And if that industry is slowing down, If they're shedd jobs and they're not hiring, that's likely to to affect these numbers going down the road if we're if we're saying, Okay, the bottom of that K is starting to to level out. But if you have a labor market that is not supporting the people who are doing that spending, then you shouldn't expect that to continue.
Hope King: I hear ya. All right, we gotta talk about that another time. Corey, thank you so much for being on. Always a pleasure, always so fun. Thanks for thanks for joining us.
Kory Kantenga: Always happy to join Hope.
Hope King: Kory welcome back.
Kory Kantenga: Good to be back with you, Hope.
Hope King: So we have to stop meeting like this on Friday afternoons in the summer. But there is urgent data that you and I've been talking about in the past. and this report, you know, to me around AI jobs has been very validating around some of the intuition that I felt around the gender divide in the AI, salary gaps. But let's start with just from your perspective. What was the one thing that maybe struck you the most out of all the findings?
Kory Kantenga: For me, the finding that struck me the most was the fact that Young people are actually benefiting significantly from the AI boom. We see that a lot of the new jobs that have been added, two thirds of those AI engineering, machine learning engineering jobs, they're actually coming to Gen Z. It's young people who are taking a lot of these positions. And we even see millennials benefiting. You know, there's always a lot of discussion about millennials and how they've suffered in the labor market and how every crisis seems to hit them at the right time and in the worst way. They've actually been able to step into leadership positions as a result of the AI boom. 60% of the head of AI roles, they've gone to millennials. So that struck me that while we're talking a lot about how young people are. having a lot of challenges in the labor market today and that is true. AI is actually if you are in the AI labor market itself, it's actually a boon for you.
Hope King: That that's pretty counter narrative to everything that we'd been hearing around how AI was impacting entry level work. So square that for for us.
Kory Kantenga: The broader labor market has seen a slowdown. When we talk about how many people are working in AI and taking AI engineering jobs, we're barely talking about 1% percent of the workforce. It's that other ninety per 99% of the workforce that is worried about the potential impact of AI to their job. And we have seen a slowdown among younger workers and entry level workers. On LinkedIn, though, we see that the hiring rate for younger workers is on pace with the overall hiring rate, but both are slow. They have fallen
Hope King: Okay.
Kory Kantenga: 30% since 2022. So this is a slow market that disproportionately affects young workers because older workers who are employed, they can hang on to their job. But if you're young, you don't have a job to hang on to.
Hope King: The age divide in AI is more complex. I'm reading from the report. Unlike gender and education, where the patterns are clearer, generational representation varies substantially by role. And you mentioned the stat around a Gen Z. I'm thinking about the FDE role, forward deployed engineer. There's been a lot of stories written about this type of role, AI engineers, and the conclusion here is that these newer AI roles. maybe providing strong entry points for younger workers. Why are Gen Z specifically positioned to take advantage of these roles in particular?
Kory Kantenga: Part of it is that they are learning these tools as we go along. They're starting out their careers working with AI and having it integrated into their workflows. They're not already trained up to work a certain way, as many of us are. So they don't have to unlearn anything. They are learning AI natively in their roles. And when we talk about forward-deployed engineers, we mean people who are working with integrating whatever software, a tool, or product you have. into the customer zone technology stack. So they're they're very much focused on a customized solution. And they're AI native, they're data native. And so creating these customized solutions, if you or someone who's digitally native and you've built an app in your life, that kind of role is very accessible to you.
Hope King: If we were to Break down this report into like great news, good news, and worrying news, which of these trends would fall into each of these categories?
Kory Kantenga: Great news, there is a section of the labor market that has a lot of momentum that is booming. In a world where hiring is down 25% compared prior to the pandemic, where healthcare added all of the jobs to the economy last year and there's no momentum outside of the healthcare sector for the most part, having an area where there is something that has momentum where there is a boom, that's great news if you are in that area. The sort of so-so news, the good news. That if you happen to be able to get one of these jobs, you were gonna be able to make a good living. We haven't seen salaries increase significantly, but if you are in an AI role, you're probably making double than what the typical worker would make. So typically for job postings on LinkedIn, we see the median salary range around 80,000. For AI, it's about 177,000. That's not going to be true for every single role in the AI economy, but for a lot of roles, it is going to be above that typical pay. So you can expect that you'll get a decent pay. It's a there's a lot of momentum there. You say, well, what's the bad news? The bad news is that it's not available for everyone. If you do not have a bachelor's degree or higher, it's probably not the most successful role for you. On LinkedIn, we do see employers using skills more to vet workers and select workers. But ultimately, Over 90% of the people we see who are working in AI today, they have a bachelor's degree or higher. And in fact, if you're looking For those higher level roles, you might even need a doctorate. 20% of the hires that we've seen for those top AI roles have had a doctorate degree. So in education seems to be a big entry-level filter. So you may need to consider going back to school if you're looking to move up in AI leadership. So that's certainly one of the challenges. The ugly, when we look at how how women are represented and the availability of opportunity, not just from an I can go to school, but even if I went to school, is there something that would still be potentially problematic? we see that there are not a lot of women working in the field. Now, some of that has to do with early in the pipeline, but at every stage of seniority, we see women dropping off. When we look at women working in AI AI companies. In AI roles. They start out at 30%, but by the time they reach the C-suite, it's closer to 10%. So we don't see a lot of representation there. We don't see a lot of momentum at the top of the pipeline. And it's just a significant drop-off by the time we get to the end of the pipeline when in those leadership positions. So while the AI economy is creating a lot of jobs, there are twice as many job postings on LinkedIn as we saw over the last few years. They're Clearly not creating enough opportunity for everyone to participate.
Hope King: How worrisome are these trends? in this specific sector given the outsized impact it has on the rest of the economy, on the stock market, on how other businesses are thinking about their labor and hiring?
Kory Kantenga: It's still a relatively small industry. So while the value being added to the economy from AI is very outsized, the workforce, the AI workforce, is actually quite small. In fact, if we look overall, the number of us who have AI skills explicitly and we explicitly list those on our LinkedIn profile, we're not more than two percent. So even though it is the case that this is a they're very much punching above their weight in terms of the value they're adding to the economy, they aren't having, they aren't. really employing most workers. So from that side, it's not too concerning overall that we don't see a lot of momentum there. But I would still like for it to be the case that everyone would have access to to those kinds of opportunities where there's very strong wages and strong momentum. If it's not necessarily in AI, but in other areas, but we just don't see any momentum there.
Hope King: So the other reason I'm asking about this is because if this industry grows in in impact and in size potentially, this could become a a bigger, more worrisome trend and it could become more entrenched. Do you see that scenario as being very high or low risk in the medium to long term?
Kory Kantenga: It's certainly a concern. There have been concerns voiced already about will AI increase inequality? Will there's be equity issues around that in terms of the jobs that people can access, the work that they can do, the way that the algorithms work. It's much bigger than just the fact that we don't see women able to take on leadership positions in a significant way in AI companies. It's much bigger concerns around equity when it comes to AI. And we would be concerned that if this, if this expands, say the AI industry becomes 3% of the workforce, 5% of the workforce, will that be expanding inequities. expanding inequality? And also when we look at pay, pay is significantly higher if you're working in an AI company. And if that's where all the momentum is, those folks who have degrees, who have higher education are likely to be paid more. That's likely to potentially drive inequality up. But this isn't just a when we think about Inequality and equities. This isn't just a story about AI. What's going on with the other industries? We know that you probably need a college degree to work in AI. You don't necessarily need it, but you probably do. But there are likely other industries where you won't. How are those industries faring? Are they benefiting from some of the boom coming from AI? How is leisure and hospitality doing where most people can start and get an entry-level role? If that industry is not doing well, even if AI wages are flat. even if AI doesn't have any momentum, that inequality is still going to be there because we're just not seeing any momentum elsewhere. So we want to see broad base growth, broad base momentum in the labor market that's going to translate into the economy, translate into broad base consumption growth. And that will support other industries.
Hope King: Okay, I want to go back to the report and talk about the methodology. This data set was drawn from, I believe, from 2023 to 2026 job postings for US listed jobs only on LinkedIn. Is that right?
Kory Kantenga: That's right.
Hope King: and I think across your base of of users, most of your users are in the US. So it's important just to focus on the US. Is that right?
Kory Kantenga: Most of our users are actually outside the US. LinkedIn has over cl upwards of one and a half billion members. Only around two hundred million of those are in the US. So most of our members are actually not in the US.
Hope King: So then can we extrapolate anything from this data to the rest of the world or we should just talk about it from a US perspective?
Kory Kantenga: On the pay side, we should focus on the US perspective. There's a lot of different things we need to consider when it comes to pay. There are regulatory issues in Europe and the way pay is regulated and the way pay is set is actually quite different depending on where you live. Even within the US itself, it can be a little bit different. So from the pay side, we should definitely focus on the US. When we think about the side of who's working in AI and who's not and how they can access opportunities, that's very much global. When we look at this gap for women, that is a global gap that we see across many advanced economies and some emerging economies as well. That women just aren't moving forward into leadership positions at AI companies. And broadly, we don't we of course see this leaky pipeline of women starting out as about half the workforce. And then by the time you get to leadership, they're closer. to 30%, but that is much more severe when we look at the areas where there is momentum and growth, which is AI.
Hope King: And then for the roles themselves, how are you determining which roles are AI? Because a lot of job postings and descriptions now probably use like AI in the skills required. So how are you categorizing it for the purposes of this report?
Kory Kantenga: So you have to first see what are the set of job titles with AI. Then you want to expand that definition and see which jobs are actually had those skills listed. And not just one skill, but at least a couple of skills in order to filter and say, are these AI or not? And then of course we do a manual review to make sure that these make sense, that they are very much aligned with how we see things more broadly.
Hope King: Something that struck me when I was going through the salary data was this idea that The writer Jasmine Sun has been talking about, which is like a permanent underclass. When you look at the salary ranges and differences of AI roles and non-AI roles, Do you feel the same worry? about the potential of some type of underclass that emerges because you have a disproportionate number of jobs that are so high paying in AI and that there's a lot of wealth also being created by the owners, the founders.
Kory Kantenga: I think it's important to break down where some of that salary is coming from. First and foremost, there's an education premium. As I mentioned, a lot of the workers in these particular roles, they have bachelor's degrees, they often have higher education degrees, master's degrees, and doctorates. So they're getting that education premium. And we know that there's a significant premium to education, which is why we keep seeing people enrolling college, no matter how many articles come out about how it's not worth it. And then there's this additional AI premium that they're receiving because this is an industry that has a lot of momentum, a lot of investment. So there's certainly a boost coming from AI, but a lot of that boost as well when you look at these median salary ranges, is for these companies to be competitive with other employers who hire people with advanced degrees. That's really some of it. And if you worry about what are the dynamics that are going to generate a set of people who will be making a lot of money and a set of people who won't. What's the incentives? If the incentives are to go to university, to get a degree, or to skill up and be able to do some of these roles, that's what people will do. And If there are more people who are willing to do these roles, who are in the position to do these roles, that's going to actually drive the pay down in these occupations. So the economy has ways of adjusting. if you incentivize if there's a lot of pay there, a lot of people are likely to move there. That's going to bring the wages down, and that will hopefully compress some of that initial inequality. The question is, how do we set people up for success so that they have access to these roles? it's not a question of should we have these roles or not because they pay too much, but how do we enable these roles, people to join. this particular set of the this labor force and be competitive. If we allow that to be the case, then we are likely to have more pay equity across the board because you will be able to transition into this role. And it'll attract people with higher wages. And by the way, other employers, they'll have to raise their wages to attract people as well. At the moment, not everyone can work in AI. You have to have a particular set of skills, you have to have a certain education level. But if more people can work in AI, if it's more skill based or there's more accessibility to working there, then other employers are gonna have to compete harder for workers and they will have to raise pay accordingly.
Hope King: From your perspective, does it seem like we're at the early stages of most of these cycles where when a new industry, you know, blossoms, you have this high concentration and a small number of people and roles, and then as the industry grows, all of the things that you just said happens and and diffuses.
Kory Kantenga: What we're seeing right now about AI companies is that they're not actually an industry in and uninto themselves. They're spread across multiple industries. There are some that are working in the financial services space. Most companies that we would call AI firms, they're working in the tech space. Some of them are working in the media space. So AI as a concept is really spanning across different products and services. It's certainly a labor market. These different industries are competing for a similar pool of talent. But one of the things we do see is that it is very much embedded in different products and services. It is more of an underlying foundation for a lot of industries. That's what we're seeing happening at the moment.
Hope King: And and that's what a lot of like academics and people who have been early on and trying to kind of quell fears have been saying. It's like this is a tool. Like AI is not some like entity alien that comes in and it's like its own power, right? Is that kind of what I'm also hearing is that it that d the diffusion is already happening.
Kory Kantenga: We actually get to make a choice about how we will and will not use AI. We as an elephant
Hope King: Who's we? See, I I love when academics say we, it's like, but but no, but like who in society has the power, right? Like that's something that I think about a lot is w you know, if enough of us are boycotting against data centers, for example, then then some part of the we is controlling how the AI grows. So I'm always, always curious, like when when we say this very, you know, ambiguous like first person article.
Kory Kantenga: Yes.
Hope King: that that like I don't like who who are those people who will ultimately have the largest impact on the we?
Kory Kantenga: S so getting at what academics mean when they say we, we mean it's a social decision. It's not a decision that that w that is being made aggregated at an individual level. We have social channels to direct things. Part of that is public policy, government policy. Part of that is public and private partnerships, what private and nonprofit entities and public you know, public companies and private companies agree to on together. They can get together as and form civil society organizations to talk about and agree on how we want to handle the AI transformation. So there's the government side, there's also the civic engagement side. And then there is just the general decision about how do you want to use it or not. If you want to use AI in your home, that's a choice that you can make. If you want to use AI at work, that's often a choice that's more in the hands of your employer. And I think that's what you're getting at. Hope is that the employers who are adopting the technology today, they have a lot more decision-making power over how it's used and where it's used. And that is the case at the moment. But as that as AI grows beyond those 20% of companies that l that tell the Census Bureau that they are using AI, once that gets much bigger, it's going to be a broader conversation. You're going to have a conversation that's going to include academics, it's going include the private sector, it's going to include civil society more broadly. And so we'll be able to have a broader conversation about how and where and when we use this tool. And of course, the how you decide to use the tool in your individual life will matter. Because AI is not just the intention is not that it's just going to be something that you use at work. It's also something that you use generally in your regular life. And if we all decide, you know what, I don't really want to use this technology because there are these this this effect and that effect and that effect. And we all Collectively make that decision, that is going to change how these businesses think about what they want to do with AI, how and why. That being said, it is hard to coordinate people. That's something, that's the reality. It's difficult to coordinate people, it's difficult to coordinate decision making. But we do as a society have the ability to make decisions about how we want to use the technology, where we want to use it.
Hope King: I'm wondering how you are reading two very different sets of headlines, If you're if you're enterprise AI, it's like you're just thinking about how you're doing the deals and how you're gonna. implement AI and then if you're on like I'm worried and I feel like I have no power and agency, you're fully on the other side, you know, wanting to like move into the woods and and just be totally off grid. is is that being reflected at all in actual data or is it right now just living in separate narrative silos?
Kory Kantenga: I haven't seen any data about people saying they're moving into the woods, at least not yet. It could be
Hope King: No one's asking those questions. Maybe you should ask in the next one. Idea.
Kory Kantenga: it could be a survey that we do. At the moment, I do think there is a lot of talking past each other. They're the optimists, the folks who are very excited about it. They're really focused on the potential of AI. And then you have folks who are worried, who are more skeptical. We've seen a lot of this at college commits commencements. You have the speakers who were, it's just the microcosm of the of the of the somewhat two sides of you could call it a debate, but it doesn't feel like there's really a debate happening. It just feels like there's two groups of people talking past each other. I think from the side of the group who's very excited and pushing forward and looking at the opportunity, I think the message for them is to take the concern more seriously. What are we doing to prepare the workforce for potential transformation, transition? Right now we don't see massive job displacement due to AI. But but no one has ruled that out. we can't definitively say because we don't fully understand what the technology is capable of, whether it can fully replace a large number of workers or not. We don't know that today because it's still evolving and still advancing. So taking that more seriously, I think, is the message that that group is the the other group is hoping that the Optimus group will receive. And for the group that is fearful. There's a lot of potential there. There's of course broad concerns about environmental impact, about abuse, about trust. And I think that the opportunity there is to raise those concerns. If you're concerned about AI today, you should be raising those concerns and voicing them and providing that input so that we can end up in a better place overall of how we're using it and taking advantage of it in a way that's going to create positive outcomes for a larger group. of people. So I don't have any concerns about people voicing those concerns there. I think you have to also be realistic about what businesses are focused on and what they're doing. They are relentlessly focused on cutting costs at the moment, protecting margins, preserving their market positioning. So the question is how do you then create incentives for businesses to have this broader conversation about impact, about use? about what is going to feel appropriate for a for a particular particular community versus what the business feels is appropriate for itself. How do you work more in partnership and less in competition? So there's certainly there's certainly a discussion to be had here. I just think the the narratives so far have been cast in a way of which these two sides are pitted against each other, rather than having two sides of a debate that are rate both raising valid Opportunities and concerns.
Hope King: I love the way that you explained that. it was is it was very clear and I think you know, I I I I I mean I don't know what else there is to say about it other than I I don't see it moving just yet, but you do see signs of it with some of the CEOs of these big AI companies pulling back on their dramatic proclaiming other dramatic proclamations that there's gonna be massive
Kory Kantenga: I thought you were gonna say Fu Foukovian.
Hope King: no. I I mean listen, I d what what was your reaction when you saw that? I mean you had you had a couple I I wrote about it in Macro Talk. I know that you're a subscriber, so thank you. And you see them saying, Hey, maybe we were maybe jumped the gun a little bit or maybe we are like, yeah, not seeing it in the data. I mean, to to you is that sort of an admission of what you guys have been saying all along? I feel like those voices just get outsized attention and then like conversations like this where, you know, you've been encouraging calm and and just sort of like a patience, they they don't rise right to the top.
Kory Kantenga: Loud voices and alarmism gets headlines. We all know that. So the question is how do we find a way to look past the headlines and try to search for the truth of what's going on? In our data, we have yet to see any evidence of mass displacement due to AI. There are certainly areas that are more AI exposed that are a bit weaker. But by the way, there are areas that are weaker and weakening where there isn't a lot of AI exposure. And it's broad-based slowdown. So it's hard for us to say, well, why is the unemployment rate rising for teenagers? Is it AI? Have they been displaced from restaurants because of AI? Last time I went to a restaurant, I didn't really see a bot serving me. It was still a person. So it probably is much more it is probably is much more broad than just AI. That isn't to say that AI has an effect in the decision making. It's so it's it's it has such potential that of course it probably does. But there's a lot of other things going on besides AI. So I think that's something that we that tends to get lost in the conversation. My job is to focus on what's the reality. And the reality on the ground is that. We haven't really seen much of an impact there. That isn't to say that there isn't potential there for there to be impact, and that's a conversation to be had.
Hope King: let's go back to the data really quickly. You talked about some of the reasons why the head of AI is looking at, you know, like a median midpoint of two hundred and thirty-six thousand. because there's all the premiums of education. And so I guess I wanna just ask you point blank, if you were talking to a younger person today who is contemplating going to college or not, with all of the mixed mixed messages and signals, what is your general advice to those groups of folks who are still on the fence?
Kory Kantenga: Understand the potential payoff and the trade-off. So the potential payoff that you get when you go to college is that you're less likely to be unemployed and you will have higher lifetime earnings. What's the trade-off? It's a lot of time, potentially, depending on how far you go. It's a lot of time that you could be spending doing other things. Maybe there's something else that you're more passionate about that doesn't require you to have a degree that you're more interested in. These decisions are not just about the money or about less likely to be unemployed, when you decide to work and where you decide to work, it is a very personal decision. No one can tell you whether you should or should not work somewhere. You have to decide those things for yourself. It's about what you want, how you what kind of quality of life are you striving for, how is this going to affect your family? Where are you likely to be able to find positions for some people? They want to stay in their hometown. And if there aren't tons of roles there for college degree holders, then maybe that's not the best decision for you. We can make projections going forward based on how we think things are going to evolve in certain occupations. The Bureau of Labor Stystics provides a projection. Going out 10 years to to see which occupations are going to grow, which are unlikely to grow. So you can take all that information and make a decision about whether what a potential career could look like. But that may not actually mean that much because we do see that people are less likely to follow linear career paths now than what they were 10 years ago. A lot of people have changed careers and made career pivots in the younger in the younger generations among the millennials and zillennials. And So your the career path you pick right now may not be as definitive as it was 10, 15, 20 years ago. So in that sense, it the decision about where you actually start out is not may not be quite as deterministic. So you want to just make the decision that's going to be best for you at the time. And it's okay if you don't make a decision that doesn't quite work out the way you wanted it to. You still have the opportunity to. To pivot and move around. Our labor market is quite dynamic. It's slow today, but overall it's still quite dynamic. It's at least in the US, it's one of the most dynamic labor markets in the world where you can start out a career in one position and end up somewhere completely different.
Hope King: you know, as a as an elder millennial at this point, it it seemed easier because the the path was laid out in front of you. And so comparing it to the nonlinear matrix career people are talking about now, like it just seems more complicated, seems a little bit harder, but that's just a a perspective thing for me. you know, where I'm going with this really is if you Think about the level of anxiety that young people do have right now. Like it it it seems to me like they would want a more linear path, or at least like the things that they had s been promised or seen other generations been promised and can follow is gone. And that seems like quite distressing overall. and I do wonder if that like has an effect on the labor force participation rate. There's been speculation about why people are dropping out of the the workforce. and looking for jobs because of this anxiety? How are you making sense of all of the you know, d various and very personal reasons to your point that impact the the bigger pie, the the you know, the greater share of the the labor force?
Kory Kantenga: Well, you don't want to compete with millennials for trauma. I think we have that one. I think we have
Hope King: Accurate. Accurate.
Kory Kantenga: that one won Hope Is there not elder but states states person millennials we could call ourselves if we like. So let's not compete with us for trauma, but
Hope King: Okay. All right. All right.
Kory Kantenga: yes, it is going into a slow labor market, particularly for young people, it is it's not just distressing. We know from research, from evidence that it does have an effect on your lifetime earnings. It does have an effect on the chances of you being employed versus being unemployed, or even the possibility that you would commit a crime in the future. These, your initial starting point in the labor market does matter. Now, the choice of your career is a different question, but generally, if you're starting out in a weak position point in the labor market, that can have a negative impact over your lifetime. So that is important for us to keep in mind. That is important, I I imagine for For folks who are starting out today, they're not so worried about are my lifetime earnings going down. They're just, how do I make ends meet? How do I pay my student loans or at least pay the interest and get some of the principal down? So they're focused on those immediate important concerns around affordability and around creating a life that's sustainable for them. And those are all quite important. And we know from the research that they out that there is a long term impact when you enter a weak labor market. So we should be concerned about that today. it's a really significant issue when we have young people a entering a weak labor market, it can potentially scar them for the rest of their careers. And we should pay attention to that now and think about but but that's why it's so important for us to get it right. it's not good enough for us to just say, it's AI or it's the economy. And and not actually try to figure out what it is or how much it is of each piece. We have to get it right because we can't address it if we don't actually diagnose the problem correctly.
Hope King: so well said and s so many scars. last question on the gender divide. Is this more acute, more pronounced, sort of with the AI roles than the rest of the economy, or is this sort of mirroring what's happening in the rest of the economy?
Kory Kantenga: It's more acute. We see that this pipeline starts out, we have about 30% women. By the end, you're closer to 10%. So 13% of women are working in AI leadership roles at AI firms. When we look at the overall economy, we actually start around f closer to 40% globally of women who are working in positions, and that slows down because we have this leaky pipeline of women, that goes down to about thirty percent who end up in leadership positions. So there is a big disparity between how we look at how we see overall leadership that represent with representation among women and versus within AI itself. So in the AI domain, they are not on par with what we are seeing overall.
Hope King: and last question here. on the jobs report from July, If you had to sum up the state of the US economy or the US labor market, pick one, in sort sort of three big trends that are happening and maybe trends to watch, what would those three be?
Kory Kantenga: Slow. Hiring is slow. It's down significantly compared to what we saw prior to the pandemic, and much more significantly compared to what we saw over the last few years. Employers are being much more cautious. The other trend we see, Unemployment is holding relatively steady. Some of that is that people are aging out of the workforce. Some of that is we don't have as many people entering the workforce. But overall, the people who are looking and who are who are looking for work or who are employed, they are managing to stay employed because layoffs are relatively low. And that keeps the economy going. If we don't have people working, they don't have income, what can you? You have nothing to spend. If you have nothing to spend, that slows the economy further. So that steadiness is supporting. Our overall consumer spending, that's supporting the overall economy. But the third trend, this is one that worries me, disposable income is actually falling. So we've seen consumer spending gr grow quite significantly. It's very robust, but the labor market isn't keeping up with inflation at this moment. Inflation is picking up. The labor market is not provide has doesn't have enough momentum to have To incentivize employers to raise wages. And by the way, most of us don't get away a a rate a raise in our wage in a given year. So the people who are driving that 3% to 4% wage growth, that's not the majority of people working today. That's actually a small number each year relative to the overall population in the US. So wages not keeping up, that has potentially significant consequences. One, if your pay isn't keeping up with what Prices are, and say you have to pay for childcare, what incentive do you have to work? You might as well stay home and watch your kids. It actually might be cheaper, more cost-effective. So we have concerns around wages being able to keep up with inflation. We saw it prior to when we had this big resurgence in the labor market coming out of the pandemic. Prior to that, there was a lot of concern about why is the median wage not really growing? It's kind of flat. And today we're saying, okay, there's possibly a big productivity boom happening from AI. It's not showing up in wages and what people take home. We got a big buffer of savings during the pandemic. We've kind of drained that down. Disposable incomes falling. How much longer can we keep consumption up? Because if we can't, if if consumers are exhausted, If they're tapped out and the labor market isn't giving them enough to keep up with how they want to consume, at some point consumption is going to turn. And that's going to slow things down even further. That's going to harm the broader economy. That's going to harm the labor market. So wages and pay, people being able to keep up there, being able to change jobs because that's how most of us get a pay raise, these things are going to be critically important going forward.
Hope King: Is the K-shaped economy over?
Kory Kantenga: There were always some issues with this concept of case shaped economy that we we don't need to get into today.
Hope King: c wait, we need to get into it in another episode. you never were subscribed to the K shape economy,
Kory Kantenga: Not entirely. Not entirely. It's a little more I think it was a little bit more complex and the data was a little bit more complex. But the K-shaped economy was a nice way of messaging the fact that we did see growth on the high end and slowdown on the lower end. But at the moment it does seem that consumption, at least on the lower end, the lower tiers of income, does seem to be holding up a bit better. Part of that might just be that people have kind of hit the bottom of their discretionary rotation. So there was discretionary income that they were spending before. They've kind of decided how they're going to spend that now. And maybe that's stabilized. But that doesn't necessarily mean that we are going in the right direction. If you have leisure and hospitality, losing 80,000 jobs in June and July, that is a big income driver for those of us who aren't making as much money. And if that industry is slowing down, If they're shedd jobs and they're not hiring, that's likely to to affect these numbers going down the road if we're if we're saying, Okay, the bottom of that K is starting to to level out. But if you have a labor market that is not supporting the people who are doing that spending, then you shouldn't expect that to continue.
Hope King: I hear ya. All right, we gotta talk about that another time. Corey, thank you so much for being on. Always a pleasure, always so fun. Thanks for thanks for joining us.
Kory Kantenga: Always happy to join Hope.
