AI is Replacing the Career Ladder with the Career Lattice Causing Companies and College to Rethinking Traditions

Wendy: This is Talent in the Age of AI, the podcast, helping leaders navigate what AI means for their people, their culture and their future. We talk with the thinkers and practitioners shaping how we work, learn and lead and what it takes to keep talent growing in a world that's constantly changing. We create, curate, and connect the insights and the community that helps leaders build AI confidence in themselves and in their teams. Let's dive in. Hello and welcome to the Talent in the Age of AI podcast, where we seek to bring you relevant, current, timely information on what's going on in this age of AI. It's like a speeding train that we've all jumped on and we're just holding on for dear life because things change all the time. I mean, our, our kids will be called AI natives. It won't be anything strange to them. But, uh, we're going, what is this all about? How do I navigate it? And especially, especially for those of you who are running organizations where you have a lot of talent and your goal is to bring everybody up to speed or, uh, maybe determine what people you need, what butts and seats, as we say in this business, and what skills do you want them to have? And, um, I'm so proud of our producer, uh, Brianna Jovan at what's Good Productions. She's an amazing asset and partner to us, so I want to extend some thanks to her. Today is part two with a very, very special guest, Larry Durham. He's the president of St. Charles Consulting Group. Wealth of experience that Larry brings from working at big, uh, four accounting firms and then consulting with him through the years and other companies as well. And he and his partner have identified the way maybe to think about what we're not even thinking about, you know, what we don't know is what we don't know. But Larry brings it through with vision. St. Charles Consulting Group, uh, works to maximize the value of talent with strategic counseling, learning solutions and managed services. And it's just so, uh, it's just my pleasure to introduce him today. Part one of our three part series with Larry dealt with the coming judgment void. And if you haven't had a chance to listen to that, I encourage you to. And on all of our podcasts, if you'd like and share and comment, we'd really appreciate that. So part two with Mr. Durham, and he's so patient to let me rattle on in this introduction is called the career lattice. And that's a turn of phrase that Larry and partners have created, kind of modifying the career ladder because as Larry will discuss, and I agree Everything's changed. I mean, all bets are off in talent today. AI is going to be wonderful and we're all going to use it and enhance it as we learn it. But things are change. So if you think of a career lattice, how do we help talent make that leap, particularly from college to career? The old days are over, where we could hire a senior from a great college, put them in an entry level job and they had time to learn, adopt, absorb, observe, uh, not only for their judgment, but for uh, what they're expected to do to be productive on the job. And when you're productive on the job and successful, there's career fulfillment and, and of course we want all of our employees to feel fulfilled, welcomed, that they have a voice and that they'll stick and stay and be productive for us. I'm pleased to introduce you to Larry Durham. Hi Larry.

Larry Durham: Hi Wendy. Thanks for having me again. I look forward to it.

Wendy: We're back. So first of all, what do you mean career lattice?

Larry Durham: You know, the term has come up more recently and a while back individuals were using it as well. Many of the organizations that we work with have a very specified career path. And I think all of us, you know, the term career ladder has been around for a long time. In some industries though, there's only one progression, right? You don't go from associate to manager to something you, and you don't skip a rung, you have to go up every rung. Most of it's time and role, all these kind of things. And so the career ladder, I think everyone knows, even if you're not in an organization that has a very structured ladder, there's this mindset of progressing forward and up, uh, and getting more pay and more responsibility and those types of things. As I mentioned in our last uh, podcast, as work is changing, as early career work is changing, uh, all of a sudden the work that you do, when you do it, what AI agents are doing, what does that mean? And what we found was those the early roles weren't just economically efficient, meaning that organizations paid people less in the early days. I mean, that's just the reality of when you're coming out of college. But they were also developmental. And as I mentioned on our last podcast, the, the challenge is that they've lost something, right? What's cheaper than paying a first year associate to do something that a third year would do is to have AI do it well. Okay, but there was development that was happening with that. So to your question, as soon as, as soon as AI starts taking on roles it's not just taking a rung out of the ladder where I can't get from the ground to the second rung. It's actually re architecting what that looks like. And so the latter was uh, one. It was known, it was well understood, it was easy to compensate for. You could align competencies to felt good because you knew where you were at in the process. But if you look at AI, all of a sudden everything is getting disaggregated. The career path, the skills you have, where you want to be deployed, how you're working at these things. And so the last thing I'll say on this is we're seeing new technologies where it's almost a skill matching. I uh, used to say it's like match.com for work, right? Like I like doing these things. And we say, oh, well, you have these things and you start putting them together. The mobility that before seemed like a nuisance is now a necessity, if you will, because it's putting people into roles that they want to develop skills in either proactively or reactively. And before you know it, that ladder doesn't hold together anymore because AI uh is taking it away. And the desire to be more lattice like is what's starting to be propagated.

Wendy: I'm a visual person and I can see a person. It's almost like rock climbers. They can pick the next holder to move over. And so much has changed. You talk about the architecture, I mean, we just have to acknowledge everything has changed and bust paradigms. And it's probably pretty hard in established HR organizations. Like you said, they have levels and you have to work at this level and before you can move up to that level. And by the way, your pay is completely, you know, uh, organized based on the level that you're in. You can't go any further than that. There's a range within it, but you cannot ascend. Well, we got to start thinking differently here. And I love how you call them AI agents. I know they are called that, but in this context I feel like they're helpers and they're co workers.

Larry Durham: They are. In fact, I was just talking to a colleague earlier today and he said, uh, the company he was speaking with, they have 40,000 employees and they have 20,000 agents, which you're thinking, wow, a third of what they have are AI agents. But what we don't account for, Those agents run 24 7, right? They're not on an eight hour shift, they're on a 24 hour shift and they work far faster. Than we do on the declarative knowledge and procedural tasks. So if you really think about it, it's probably three times more agent productivity than they have people productivity. And that seems far fetched. But I think most organizations are starting to get to that point where we're already in a place that more work's being done by AI than is being done by the human element.

Wendy: Well, and one agent isn't one agent because they go out there and reference millions of agent points. I mean, you know, right. What they're accessing is untold amounts of information and lessons learned by others and they put it in there. It is a phenomenal space and place. So, um, what should an organization do to not only acknowledge and build toward a lattice, but help their employees? Um, I love it used to be where businesses said what can employees do for me? And I think we're shifting to say what if business is going to do for employees? Because I, I'm a believer we still need the human element in all of this. And what can we do? We got a. I'm looking at, you know, big buildings here in Omaha, Nebraska, where I'm from, five Fortune 500 companies and a lot of Fortune 1000 companies. They gotta change, I think, don't they Larry?

Larry Durham: Yeah, I mean everyone has to evolve. Um, you know, sometimes we're exceptionally bad as humans as thinking about what the future is going to look like. We're not always right in the way it looks. I think there's a couple things. I think there's the ladder will break down because once the early rung of the ladder goes away, there's no way to get to the second or the third rung. And even if I could, I don't even know how to keep my balance. Maybe for that analogy. I don't know how to even balance on rung one. And here I am, um, three rungs up. So that ladder begins to break down and the lattice starts to take hold. So we're already seeing with skills the ability to port people or migrate people through short term assignments, through experiences. Right. That are experiential. And what I love about that is it's building the muscle of judgment, exposure experience across a number of domains and areas of expertise which makes someone more fungible and usable in the future and the ability to oversee and direct agents and other things better. So I think there's the lattice piece that's super important. Then I think the other part that most organizations need to start thinking about is the, the gap that we talked about in episode one, which Is what does that begin to look like? Uh, when I think about the problem, sometimes we think, okay, everything stays the same except the part we're talking about. Well, when we go upstream, they're coming out of college. Are they perfect coming out of college? And what have been the challenges that we've seen of individuals coming out of college? I actually think there's a period of time where the formative work is going to look radically different. We're not there yet, but on the back of the judgment void that we talked about, we're going to have to create environments where individuals can upskill and do the work. And I think the best analogy, there may be two. One is aviation, right Before I ever get to get in the plane, I get in the simulator and I do it time and time again to develop that experience before I do it with the full consequence of it. And then the same thing in medical. Right. Um, I'm in a residency, I'm always overseeing. You know, we have this in, in aviation and medical, which are both highly consequential now. Audit, tax, consulting, other law, those are all consequential. But very few people die as a result of a poor audit. Right. Someone loses money. It is consequential. These are things that need to be addressed. Yeah.

Wendy: Ah, well. And medicine gets a break because they call it the practice of medicine. They don't call it the practice of aviation because none of us would fly.

Larry Durham: That's true, that's true.

Wendy: But you're absolutely right. Uh, my personal story, as I was married to a doctor in his residency, he got to really do a lot of things. He was expected to do a lot of things at fourth year. Um, and we met, uh, we made good friends with a fellow physician who had gone to very renowned medical school where they weren't letting students do anything because they're treating executives and sheikhs from other countries and things like that. So, you know, when mine graduated, he had so much more experiential, real impactful experiences that mattered. And he wasn't going to screw up as an intern because he really wanted to graduate. So maybe that's an analogy that comes to mind. You just have to have the consequences that matter to motivate you to apply your judgment based on your knowledge and what you've seen and heard and done. Yeah, um, I love that you're talking about, uh, we're talking about long held traditions, long held ladders and compensation structures and talent and development structures. You're going to take course A and then B and then C and well, it's like. And the other institution that is lifelong and established is university level learning 100 level, 200 level, 300 level, 400 level. And never the twain shall meet. And you got to, you know, reach these accomplishments before you can move on. But if those traditions hold, those aren't the organizations that will enhance and succeed through the use of AI in my opinion. And I think that's what I hear you saying. We've just got to bust a lot of tradition here.

Larry Durham: Well, you know, when I think about the, the problem, even, even before AI, a lot of the audit firms that I work with, they would say we get individuals from top rated schools, they have an accounting degree, they're top of their class, they get their CPA designation or certification. Uh, they still need to do work, but then we still have to train them, right? On how we do things, what's unique about what we do and all those kind of things. But what's happening now? Think about this, right? You go to college, uh, for three, four, five years, however long it takes you. It's interesting today, right? Colleges face a very difficult challenge, right? Uh, I love that old saying. Someone used to say, like 50% of the jobs that first graders will take don't yet exist, right? And so that makes you scratch your head. And now I'm sure it's probably 80% and it'll be 100 one day. I wonder, is it 50% of the jobs that freshmen in college are going to take don't yet exist, right? When we get to that speed, how do you have a degree program that's meaningful, right? That you continue to build on? And here's what I, here's what I think is going to happen if I take what we talked about in the last episode around. I can't just jump over. I can't just pass over the formative work that has to happen. I can't just get good judgment and not have any clue how something works because I can't even apply the judgment, right? So I believe there's, there's an element. I don't know if it sits in the colleges, I don't know if it sits in third parties. It might sit in the organizations themselves or they get a two year accounting degree. And then on the back end of that is something that we're starting, and I don't love the term, but for lack of a better word, I'll say synthetic work. Uh, synthetic sounds fake, but the reality is it's real, formative work where you bring people in, they do the Work in parallel. They're doing it as if they always would have done it. Which seems a little bit ironic, right? Because AI is over here doing much of the work. And so they're getting the feedback, they're getting the apprenticeship. We're rebuilding what this synthetic work looks like through declarative knowledge, procedural tasks, judgment and relational. All of that comes together in a simulated environment. Not just for judgment, but for all those things. So that by the time I, you know, maybe can even get into the lattice, not the ladder, but the lattice, I know how this actually works. Because here's what I'll tell you. As long as organizations can use AI to do the work cheaper, faster and maybe even better and broader, there's no other way around it. That uh, that's not a problem to solve. That problem been solved and that one's been determined. Right. It creates a new problem we have to solve. And that is individuals don't have the developmental formation, uh, or the developmental density of work that they need to come into judgment. And so the question is, in a strange way, there will be, I believe, something that sits as synthetic work in between maybe as part of college, in between college and when you start. But it's actually replacing maybe year one or year two. Um, and that could be through a consortium, it could be independent. Don't know the answer to that yet. But we're starting to do a lot of research on what simulated real consequential work looks like. Because when you do simulation without consequences, it takes the development piece away. Your brain is not in overdrive trying to figure it out because you're like, I get it wrong, no big deal. It has to be consequential. So I think there would be something that changes massively there around synthetic work.

Wendy: I think you're right. Another big idea. Hold that thought, Larry. We're going to stop for a quick break. Um, listeners, watchers of the Talent in the Age of AI podcast, I'm so pleased to tell you more about the St. Charles Consulting Group. Their mission is to help employees navigate change and experience success by delivering comprehensive of talent development solutions that focus on, quote, preparing your people for your tomorrow. And you'll see from listening to our three part series with president Larry Durham that this is exactly what they do. And they're not resting on laurels or doing what happened in the past. They are big visionary future thinkers. So they help mid to large size organizations maximize the value of their talent. And who doesn't want want that? That's why we're all here together. Through strategic consulting, innovative learning solutions and managed services. The roots are in real world renowned Anderson Worldwide Training and Development center, located in St. Charles, Illinois. So they come at this from 30 plus years of deep experience, real world boots on the ground, training, consistency, consulting, thinking about what's next and identifying the real problems to be solved through human talent interventions. For our podcast report series is President Larry Durham. And I'm so pleased to have stopped for a pause to let you know more about this incredible company available@stccg.com stccg.com as in the St. Charles Consulting Group. And now we'll go back to our interview with President Larry Durham. Okay, I really appreciate that. What we were talking about with the president of St. Charles Consulting Group is Larry Durham. And I'll call him one of the biggest thinkers I've come across for a very long time. I know that I think 10 or 20 years ago, one of the forerunners in our world of talent wrote the Future of Work. But that book is probably obsolete today. I mean, what Larry and his partners are doing are talking about the future of work because of AI and how it changes things. And there's a theme that says it's probably not a career ladder anymore, but a career lattice. And the path we were on, Larry, we were talking about before the break was you still have to have foundational knowledge and, you know, the core information to apply to your judgment. Because we're being, uh, we probably will ask employees to make a big leap to level three of the rung or something and grab onto the lattice. Lattices are still strong because they're built with a crisscross pattern and they're, uh, relying on each other to be strong. And so it's almost a better framework than a ladder because every cartoon we saw growing up, if the top ladder broke, the, you know, the Wile E. Coyote fell down every other rung and smashed to the bottom. So I really like the, I like the visual lattice because there's lots of safety nets in there, but it's a web of knowledge, a web of skills, a web of understanding. But it's just going to cause organizations and universities and people to change, right?

Larry Durham: Yeah. It's interesting, Wendy, because, uh, as, as, as, because as we've thought about this, we live in a world of constraints. A lot of the things we put in place, we don't put in place because they're optimized. There's a world of constraints. And so how long does it take someone. Well, four years sounds good, right? Four years of college has Been a standard for a long time. I'm not sure four years is the right answer, but it seems right. And then you can get, you know, graduate school and go on, et cetera, et cetera. I think this is interesting. The, uh, the reason that career lattice and the bottom rung of the career ladder coming out may be the beginning of the lattice is because the constraints within organizations have often been, how would that even work? Right? How many years has it been since someone said, we're going to start seeing flatter organizations? We're going to see broader span of control? Well, now with AI, uh, you're going to most certainly see a broader span of control. People say an individual might oversee five to ten times the amount of work that they used to, and the cognitive load is going to be different. They're going to multitask, and they're going to do this. But I can tell you, working in a lot of very large firms, the reason that you don't let people be more mobile and develop and go across different roles, it's a nuisance. It's like, well, I'm trying to run a business here. Larry's development is secondary. I can't have Larry off doing something else. Or we hunt and pack. So I like this team of people, and I always want to keep them together, and I don't want to be disrupted. The constraints aren't. Historically, they were. Well, the system doesn't allow it, and our compensation, and then development, et cetera, et cetera, I think the place to work, of mobility and skills, uh, intelligence. What skills are we going to need? What do we have? What do people want to do? Uh, internal marketplaces. We're seeing the beginnings of it. But the ironic part is some of the efficiency that AI is bringing to us is freeing up the resources, the time and the dollars to actually enable what that would look like. And strangely enough, the systems and the AI are removing some of the constraints, um, for what it would be. I'll give an example, this kind of an unusual example in a parallel path. You know, about six, uh, to nine months ago, every large organization has this enterprise system or tool that it uses, right? Everyone has an ERP, they have PeopleSoft, Oracle or, or even, you know, their CRM systems like HubSpot and things like that. If you look at those companies in the last nine months, most of them are about 60% less than they were nine months ago. And you say, well, that must be a rough streak. You know what happened? An AI tool came out. Claude code came out, and people said, we could develop our own software, we could disaggregate this highly structured network. And if you take that analogy and you say we don't need an industrial strength ladder truck, right, that only does one thing. We could have a litany of ways, we could have lattices of ways of going about this. Now we're not there yet, but I think that idea of, you know, universal, one large, everything has to go in one place, disaggregated, decentralized, the AI construct is taking away those constraints and I think we're going to start seeing some of that. If you're like me, that makes my head spin really fast to say how does it all work? But the reality is the structure, the governance, the oversight, the compensation, the development, all those things can be managed because those constraints are starting to go away. And I think you might actually see people better enjoy their work, get the right developmental things and do the things that the organization needs as opposed to staying in the construct we have today.

Wendy: Uh, I love that insight because I don't think people pointed to organizations like the ERPs that would be affected greatly by AI. It was all about all the individuals going to lose their jobs. But when you stop and think about historic organizations built to support historic models,

Larry Durham: we always do that though, Wendy. We take our current frame of reference and then we say, what do we know? Just one thing, right? I read an article many, many years ago about the death of car insurance. If you had self driving cars, right? If cars were 99% less prone to accidents, the whole business of car insurance would probably decline if you had self driving cars. Now the reality is we have regulation, we have all sorts of other things that would take a long time. But uh, it's interesting how industries can rise and fall. You know, if you look at the top 10 industries, top 10 companies by net worth today, and go back 10 years ago and see which ones are the same, you have names on there that you didn't even see. They were just small, you know, AI related, uh, processing companies that are now the number one largest you would never would have thought of. And then you have big companies whose industry has sunsetted. And if you're not a tech company, unless you're oil and gas or a couple other healthcare things, there's no way you're going to be in the top 10. And I suspect in the next 10 years every company on the top 10 will be AI or technology related. That's just the way the business is going.

Wendy: I think that the big companies again, didn't see it coming, you know, well, we're too big to fail, you know, and then they, they just get eaten alive by someone that was more alive than did adopt what they saw coming.

Larry Durham: The challenge is, for many years, while I was doing learning at PwC for client facing work, we were doing large scale change management. It's the hardest thing for human nature and for organizations is to pivot. And it's, it's not because you can't look ahead and see what being proposed is better. It's different. Right, that's, that's the adage around change management. I don't pivot because what you're presenting is not better. It's different. I don't fully understand it. It seems like there could be risk, but most of the time my human nature calls me back to, I'd rather do what I'm doing today. It's easier. Let's just see if it plays out. I don't think anyone is sitting around saying, let's just see if our business model survives AI as a passing thing like Covid.

Wendy: Right.

Larry Durham: They realize it's going to have to be transformed. And ironically, as we said on the last episode, they're like, let's double down on it. Let's be more profitable. And they're making some decisions that are ultimately affecting their people and their judgment. That might be the crisis that they're going to run into is they over indexed on AI and didn't take care of their human talent or their human resources in the process.

Wendy: Um, to your analogy, what do you think Zoom thought the six months when they founded and then Covid hit and like, they're probably so grateful for Covid, right?

Larry Durham: Yeah, yeah, it's quite interesting. Uh, even the podcast and the meetings we have today, it's rare that I have a meeting that's not a face to face meeting. I often think it would have been a decade before we got that type of adoption had, uh, Covid not come about. So that might have been one of the very few good things that came out of COVID But, yeah, fair. Sometimes it takes a catastrophic event for people to do something different. Otherwise you often have a generational type thing for something to take effect if it's not mandated, such as the use of AI or other things like that.

Wendy: Yeah, I mean, the microchip changed this century. I mean last century. I mean, it does take quite a motivator toward change. Um, okay, our next topic, our part three is going to be about blending human skills and AI skills. And I think there's a takeoff here. About when you talked about succession planning or I heard you say those words, or maybe that's how my brain thinks, but in my corporate experience, and I had a great corporate life, um, it was pretty evident who was on a, on a succession path track. And it was few and far between is how evident it was. Those were the people that got to work in operations and then finance and, you know, they were, they were getting their feel for all the departments on their way up. But I wonder if I hear you saying that the lattice in helping people experience the departments where they need to be, that they may have leapt is creating more succession planning for more people.

Larry Durham: That's a great question. Think about how many people have left a role because they couldn't see a path forward. Right? Like, they either didn't have a path forward or, you know, something like that. I do think for the last, uh, two years or maybe even the year before AI came about, when you said the word personalization in HR or in training, it was like, let's do this, uh, let's put their own industry or let's put their own. It was mass customization. Right. And now all of a sudden we're saying, what if your career path could be personalized? One thing I would say the future of an effective worker and then an effective manager and a director and a leader and a chief, uh, executive is really understanding business models and how things work together. And I think exposure and education and experience and engagement across all those areas, all the areas of the business is super important. And so if I have the one thing, I've been in industry, I've had startups, I've worked in consulting. One thing I really appreciated about consulting was it just continuously threw complex problems at you, uh, that others might not have been able to solve. And then you had to apply judgment, critical thinking, decision making, all these kind of things at solving problems. Um, and so a lot of my time now, as you said, is spent thinking about what the problem is, where we're likely going, what this begins to look like. But I love the idea that individually people have broader exposure and one, they can either lead and manage better, but think about the future. You know, I've had people, I've had younger people who say, I don't really want to manage my people. I like where I'm at. I don't want, I don't want the hassle of managing people, which is an ironic thing. Yeah, we're in a business now where individuals might be managing a cadre of agents. Right. Can you manage this team of 20 agents and direct them and guide them. Right. You, maybe you won't get the negative feedback or the uncomfortable conversations, et cetera, et cetera, but there's real opportunity to manage agents, a cadre of agents or even a team of agents or, uh, an agent of agents. Right. It just goes on and on and on. I think that's a really interesting thing you said, though, around succession is you can progress and you can solve problems. And it's almost like not only one, what is the problem? What's the work we can do to solve it? But how do we build solutions, solution architecture? The engineering comment you made in an earlier episode. We're all engineers to think about the system where we use humans and AI to solve a problem as quickly and as effectively as we can. And that's very, very powerful.

Wendy: There's agency for a human in this transition.

Larry Durham: M. I like that. The agency of agents. I like that thought. Agents aren't a threat. They should be your own agency if you know how to use them and direct them.

Wendy: Right. Uh, that's the book I'd like to write with you.

Larry Durham: All right, we'll do it.

Wendy: Well, thank you so much for being with us. I look Forward to part three again. My guest is Larry Durham, the president of St. Charles Consulting Group and just such a delight to spend time with today. And you're not going to want to miss part three if you missed part one. You can always go right back to Apple, Spotify, or our website to take a listen. And don't forget to like and comment and share, because we'd really appreciate that. Because what we're doing here is spreading the word about what's going on in AI today and real solutions and real things to think about in this day and age of great change. Larry, thank you so much for being with us.

Larry Durham: Thanks for having me.

Wendy: Thanks for listening to Talent in the Age of AI. If this conversation gave you new ways to grow in your own work and to better support your people, follow the show and share it with others in your HR and talent. Network members get even more full episode, uh, transcripts, extended show notes, and companion resources to help you put these insights into action. Learn more and join us at talentintheageofai.com we're here to help leaders create, curate, and connect what's needed to build tomorrow's workforce today. See you next time.