The following is a rough transcript which has not been revised by The Jim Rutt Show or Lisa Buckingham. Please check with us before using any quotations from this transcript. Thank you.
Jim: Today’s guest is Lisa Buckingham. She is the chief people and culture officer at Vialto Partners. Vialto helps companies and people move, work, pay, and stay compliant across countries, both using advisory teams and managed services. They are essentially a service organization to companies that have a lot of expat employees. Prior to joining Vialto, Buckingham served as chief HR officer at Lincoln Financial, US Soccer, and Thomson Reuters. So let’s dig into the meat of the conversation here with Lisa. Let’s hear your thoughts on how the kind of people that we need to hire today has changed with LLMs being more and more part of everybody’s business roles. I’ve talked to CEOs and chief technology officers at relatively big AI companies, and they’ve thought about this a little bit, but less than you might think. And I said, well, let me see if I can get the HR queen supreme on my show and get her thoughts on what we should be looking for in the age of AI for the people that we’re hiring.
Lisa: Thank you, Jim. It’s so nice to be here. This is the ultimate question on everybody’s mind. And I would say that it’s not just about your skills. It’s not about your passion for your domain. From my perspective, it’s really around where is the intellectual curiosity? Where is the learning agility? Are you really willing to adopt the change and work differently?
What I’m really hoping for is that when people are learning to work differently and they see the value of LLMs—or, for some folks listening today, the advent of AI—they embrace it. Jim and I worked thirty years ago in natural language processing labs, so it was a very interesting time, and the scientists were very interesting. But today, everybody can be an AI expert. It’s really about what you’re doing to divide your workflow and what you’re going to release into a machine. Trust the machine, but always validate. Having the intellectual interest and curiosity, knowing what your learning agility is, is really, really important.
You know, Jim, you mentioned 2022. In 2022, and previously in 2020, we had a really important time around the advent of working from home and a lot of things that were happening with COVID. Every generation—but let me just focus on boomers—had to learn how to work with online banking, with telemedicine. I do think that accelerated some of the adoption that we’re going to talk about today, Jim. And now it’s really about how does that work going forward? From my perspective, it’s a really, really exciting time.
My main message here is that there’s a shared responsibility with an organization as well as the person, because the organization cannot bring them along 100%. They have to be willing to do it as well. So I’m pretty excited about it. It’s a really interesting, fast-moving time. I think it’s moving faster than it even was moving six months ago, Jim.
Jim: It certainly feels that way to me—that every week you can feel an increase in the capacity and things that you wouldn’t want to turn over to an LLM six months ago, now you can. Though, of course, as you mentioned, you definitely want to verify it. How are you feeling with the people that you already have on board, their willingness to dig into this new way of thinking about their jobs?
Lisa: It’s an optimistic answer, I will tell you. And it definitely varies around the world, from the standpoint of what people want and what we need to do from a works council perspective and all of that. But what I would tell you is we’re really listening to our workforce. They want more tools, so we’re giving them those tools. We’re giving them the learning and development. Where I would say I want to see more is the actual going online, doing it yourself, or taking a course.
Again, I’m going to lean into that shared responsibility because we can’t make people do this. Their world is going to be different whether it’s Vialto or another organization, because that’s just how the world is moving. I would say that the adoption rate is super high. We segment our data in a lot of different slices. I can’t tell you that there’s one generation or a different role that’s adopting faster. What I would say is there are the evangelists and then there are the pessimists. So we have to keep working on that, and that’s the change management side.
Where I would lean into change management, Jim, it’s really the communication of it. I remember years ago leading a digitization effort at Lincoln, and we would have focus groups and people would say, “Well, I just don’t want to see robots running around the organization.” I was like, that’s never going to happen. That’s not what we’re doing. What we’re trying to do is take the manual, standard processing things off your plate so you can then work on your customer service with the policyholder or whatever.
So from my perspective, this is really about taking the myths out of the work environment and talking about where we’re really trying to go. In professional services, our organization is our people and our clients. It’s all about being a global citizen. So how are we handling expats? How are we handling their taxes? Sure, AI is going to help us accelerate some of that manual work, but there is still a huge human component here, which is what’s so exciting—because it’s now about how do we untap what else we can get from them and what they enjoy and excel in.
That’s the wise company that figures out how to empower their people rather than replace them, at least in higher-level functions. Make it easy and make it fun. I was at a dinner last week and this one organization that I admire a lot, they’re doing—not hackathons, but it’s really around empowering people with different AI tools and giving them an opportunity to have contests, almost like Shark Tank, and come back and say, “This is why I think we should change this process. This is how we can.” And, Jim, you remember our one-pager we always used to have to write—our MBDI, major business development initiative—and say how we were going to change something, and you would invest money in it and then measure the heck out of it.
So it’s a new world of competition from the standpoint of the now of work. I don’t want to even talk about the future of work anymore. That’s so dead, and I know I’ve been quoted on that. But it’s really about capturing the hearts and minds of people at every point in their career and making their lives easier. Work hard, have fun, but also let’s become partners with our agents.
Jim: One of the things I’m finding with some of the more forward-thinking companies is fundamentally changing job descriptions—what’s in jobs. For instance, in some kinds of businesses, it makes sense to combine the programmer and the product manager jobs, because the product managers can now do an awful lot of their own development, at least up to the prototype stage. That shrinks not only the nominal time it takes to get a prototype out, but with the product managers I know, you know the frustrations they have in getting the programmers to do what they want. If they’re doing it themselves, then they can get what they want. Are you seeing that kind of reconfiguration of jobs?
Lisa: Yeah, Jim, I’m seeing everything is changing. So first, job architectures, the hierarchies—everything’s flattening. What I would tell you here, and it just makes my heart so warm, is when you hear that our head of product development is invited to go to a client and they also bring an IT partner, and they’re coming back and they have ideas or they’ve offered what we are working on from a development perspective. It’s definitely our differentiator.
So I think that the job architectures are changing. I think everybody has to have some level of technology background or understanding of how workflows work. But bringing the right people in the room and showing those partnerships—Jim, I don’t know if it reflects in an org chart, but it does in the workflows in the organization. Break those barriers down and those silos. We’re a follow-the-sun organization because we’re in 55 countries, and we have a lot of people in a lot of different places. But it warms my heart to see that there are people who are really working differently and understanding.
And we’ve talked about this for thirty years, Jim. The customer signs your paycheck. So they’re looking to see where Vialto is going. They’re looking to see what we’re doing differently than our competitors, and that’s our edge. So that partnership is really, really important.
I will predict that job descriptions are going to become way more fluid in the future. We’re working with a really cool company that’s helping us with our job architecture and doing a skills-based inventory of what people have today and where we could develop them. It will all be optional for people to opt in on this. But from my perspective, Jim, it’s time for transformation of ourselves, not just in the organization, if that makes any sense at all.
Jim: Oh, yeah. I understand exactly what you’re talking about, particularly in this huge change that’s occurring. I mean, people say, well, is AI as important as the internet, or is it as important as personal computing? And when I look at where it could go, it could be more important than either of those. It could be as important as electricity, which fundamentally changed our world. It hasn’t gotten there yet. But if it does, the amount of personal change people are going to have to make to keep up is tremendous.
Lisa: And I would argue with you a little bit on that, from the standpoint of I do think it’s as pivotal as electricity. There are obviously questions around data farms and all the electricity that’s being used, but the advent of how we’re bolstering technology and what’s next—I genuinely don’t know. Like, who am I to be able to say that? But that’s the most honest, most curious, most human answer I can probably give.
The world is changing faster than our frameworks, but that doesn’t mean that we can’t all pace ourselves at the same time. Our job—my job, really, as HR leaders, as educators, as humans—is to stay curious enough to keep asking the right questions even when we don’t see the answers yet. And from my seat, Jim, I don’t know all the answers. I argue that nobody really does, because we don’t know how this machine learning is really growing and what’s manifesting.
But what I can say is if we’re not thinking about it, looking around corners, and—as you always would coach us—taking some time, turning off your computer, unplugging your phone, going to think about it, and coming back with ideas of what else you think could happen, we’re never going to get there. The thinkers and the doers are so important, because what I really hope my legacy is is that I’m helping people manage their own careers—we’re not managing it for them. And that’s a really big statement at the end of the day, because you’ve got to love where you’re going. And if you’re unhappy coming to work every single day, what a terrible life you have. So I think the intellectual curiosity is really important.
Jim: When I talk to end-user companies—not the technology companies—I’m finding a lot of AI projects, particularly big ones, that failed. Either they tried to do too much or they tried to do too little, which I find interesting. So I’ve coined that little expression: what, when. And it seems to me that that is going to be one of the most valuable skills to have in an organization today—someone who understands the business, understands how much change the organization can actually take, and what LLMs can really do. Because consultants come in and oversell what they can do—that’s attempting to do too much. Or technology organizations can do little projects that don’t move the needle at all in the business and are trivially easy to do and hard to fail. That’s what I call the attempt to do too little. And so figuring out what to do and when to optimize—moving the needle for the business—is a kind of specialty skill, and I’m not even sure what that person looks like. Does that resonate with you at all?
Lisa: It does. And I guess I’m going to slice it into two answers if you’ll humor me on it. My first would be there are hidden opportunities inside those test-and-learn transformations or opportunities, and that’s extraordinary. Nobody wants to spend money on something that’s going to fail. But if you don’t test and learn, what are we doing in this world?
I think we really have to think about it as an opportunity to accelerate the human experience while we’re also accelerating technology—not replace humans. This is what I’m really trying to make sure of. I was using the term “keep human in human resources” for a long time, and I do mean that. But I also think that human resources professionals need to really embrace technology as well.
In that example of going in at an end-to-end situation like that, if there is a fail point, my belief is that we’re really going to learn from that, take a step back, and be better the next time we go out if there’s a there there. Think about the startups in the .com era. Now we’re seeing so many people—different archetypes of folks who never ran a business—building technology to support businesses and accelerate different things. So it’s a really heavy question, Jim. That’s a heavy question.
Jim: Yeah. That would be, if I were a senior exec at a company that depended substantially on technology, my number one question for 2026: what, when? With the figure of merit being what has the potential to actually move the dial for the next two or three years on the business. Otherwise, you’re missing opportunities if you’re not doing enough, and you’re wasting resources and opportunity costs if you try to do too much or the wrong thing and don’t nail some projects that are realistic and can really benefit the business.
And it’s not entirely obvious whose responsibility that is. At the end of the day, it’s kind of the CEO’s, but they don’t really have the background to make that call. And partially the CTO’s, but they don’t understand the business well enough usually to make that call. So it seems like it’s a team project between the sales organization, the CEO, and maybe the CTO who work on that one question. That’s what I’d do.
Lisa: Yeah. I love it—I’m going to steal “what, when” for sure. And the question is the what, when, and who, to your point. Because if you don’t have a coalescent team working on this, it can go really sideways. But what I would just say is this has hit us in a way that, from the standpoint of getting super, super clear on where are we trying to go, what are we trying to achieve, what is the impact in the organization—the future has hit us already, and I am really clear on that one. But the question is not whether to embrace it. It’s really, to your point on this team question, whether we have the wisdom, the courage, and the humanity to shape it and have the courage to really get it collectively organized right.
Jim: Even what—I think I remember you always saying—get it approximately correct and let’s test it. Do you remember that?
Lisa: I know I say that kind of thing all the time. Get it sufficient for the task, but not necessarily perfect. Get it out there and then improve it.
Jim: Just a couple of—you know, I wouldn’t do a good job speaking with you on this if I didn’t talk about what’s already happened in just the past twelve months. 1.1 billion jobs have been transformed by technology, and more to come. 93 percent of HR leaders are now prioritizing soft skills over hard skills, and they’re saying that we’re saving seven and a half hours per week because of AI. I’d love to hear your view on that. And there’s also the fact that 56 percent of folks are now living in the now of work with AI, and the wage premium for workers with strong AI fluency is there and real. So how do you respond to that from the standpoint of what we’re talking about?
Lisa: Oh, I mean, I think it varies tremendously by the nature of the job. The pure computer coders—mamas, don’t let your babies grow up to be programmers. It is indeed true that for people who know what they’re doing, and particularly for early-stage projects, you can get seven to 10x improvement in productivity. So it may well mean that the demand for programmers will go down very substantially while the productivity goes up. Though I did write an essay on Substack that argued the opposite—that just as electricity got cheaper, the world consumed more and more dollars in electricity. It all depends on how much software the world actually needs. If it needs a lot, then we may oddly end up with more programmers who are far more productive than we ever were.
Other jobs, like sales jobs, are probably not going to be particularly AI-able anytime soon. But the ability for those people to work with the product teams and communicate what they’re hearing from the field on what the customer needs—that skill is always going to be there, but perhaps more important now when everything’s moving a lot faster.
Lisa: Yep. I agree. And it’s how you bring people along, right, and train them, and what are people best suited for. People who are not willing to change are not going to make it long term—maybe they’ll go start their own gigs, and then they’re going to be mad that people aren’t changing.
Jim: Right. And you bring that up—I was going to say one of the main roles of HR is to not let resistance to change in the organization stop necessary change.
Lisa: Yeah. I mean, Jim, at the end of the day, I think AI will transform everything that can be automated, and smart people will figure that out and get there. It will make permanent everything that cannot really be automated—the guidance, the human element. I read a book called <i>Living and Working with AI</i> by Ethan Mollick. And he asked a really good question: what are the 12 things in your life that, if you think about it for a week, can be automated? And why aren’t you automating those things, because it will give you time back in your life. I think we have to think about that every single day, not once a week.
So my question is, are we training people to be agile? How do we handle folks that aren’t able to have a high level of learning agility? Those are really important questions for me as a human resources leader. There are gifted people in so many different areas, but if they’re not embracing AI today in an organization, what I would just say is everybody has a job to do right now. And AI is being inserted in a lot of places. And to your point, maybe on the sales side, you don’t want to give up that relationship with your client. Maybe you want to have conversations with your client about what we can put more technology to so we can have a better relationship.
Jim: That would be a question I would have if I was in sales. And one of the things that AI—particularly the newest AIs—can do for the customer is that you can much more easily than in the past produce visual output. Essentially, dashboards are at least a tenth the price, maybe a hundredth the price, that they were before LLMs. And many customers may not even know it. So if the company has the capacity to provide those kinds of services quickly and easily, then the salespeople need to understand what they are and how to communicate them.
Lisa: 100 percent. And that’s going to require at least a little bit of familiarity with the technology. Isn’t that our job—to know the technology and to sit down with our clients and our CEO? What do you want me to measure? Because they’re like, I’ve seen so many data analytics reports, Jim, that we can hit a button and measure. But nobody wants to see that. They want to see x, y, or z. There are certain things. And now in the advent of AI, you can co-partner with Claude or Copilot 365. I can throw a report in and I am measuring stuff so differently today on the people side than I did six weeks ago. My life has changed. It’s given me the opportunity—and by the way, that actually helps me with my employees—to go back and, you know, employee engagement surveys used to be like a six-week process and all of that. Not anymore. I can come out with action plans in a minute or two, and then we have to test it and really pressure-test it. But, Jim, we’re saving weeks on this. So then I can go focus on people.
Jim: Now, the statistical data analysis—are you doing it yourself, or do you have someone who does it for you?
Lisa: No, Jim. You know I’m not doing it myself. You know that answer. We use our people analytics software through Workday, and there are programs that come out of that. And now you just take that and you can put it through Claude and say—and, you know, I think the advent of AI, and with your guidance I took that AI class at MIT—learning how to prompt is one of the game-changing things that you can do. I put it in there, so my analytics come out very differently today than they did six weeks ago because I have the baseline data. But if I’m just curious about something, I can get great trends. It’s awesome. And it’s all in our firewall, so it’s fine.
Jim: Again, do you do that piece yourself, or do you have to call the data analytics guys?
Lisa: Absolutely not. I do it myself, 100 percent.
Jim: You see, that is going to change the kind of people that you’re going to need, because there are a lot of people who are just not capable of doing that themselves. They just don’t understand the idea of statistics. It’s just over their head.
Lisa: So, Jim, I don’t know if you remember this, but you made me go back to college and finish my degree. And I did that. I did it at Georgetown, and I did pretty well. And you gave me a beautiful gift of a Mossberg shotgun, and I still have it. But what I would tell you is even a liberal arts major like me can dive deep into this—from, like, Aristotle or philosophical conversation. But if you can understand being analytical and really dissecting questions in your mind, even about a sentence, I think that you will be way better set for learning how to write your prompts and all of that.
I don’t think humanities have ever been opposed to technology. I know there are a few clips I’ve seen on social media recently about it, but I think that we liberal arts majors learn to be more interpretive. Now the question is, who has the curiosity, the adaptability, and the human wisdom to work alongside AI, trust your agents for sure, but without losing yourself in that. I can get really, really good statistical data now. I do have people who will test it and make sure that I’m not building a conclusion on what I wanted to hear come out of my agent. But it really is game-changing, Jim. It’s leveling the field. I think STEM is incredibly important. Everybody should take an AI course—whether it’s online, go to class, do whatever—but it is the wave of the future. 100 percent.
Jim: Yeah. You mentioned liberal arts. Well, I’ve been saying this since November 2022 that if companies are smart, they will be picking out the best liberal arts students for entry-level positions. Because people—especially philosophers, historians, people who use words very precisely, English majors—are naturals to be prompt engineers or to structure the inputs into AIs in the form of prompts. In fact, for one project I did, a pretty big project, I hired a guy with an MFA in short story writing as our prompt engineer. And he was brilliant because he understood how to have a conversation with somebody and then to convert it into extremely precise language. I think that companies that aren’t looking at top liberal arts graduates for some of their entry-level AI positions are making a mistake.
Lisa: I am so happy to hear that. I did pull a few quotes from some of your different podcasts. Jordan Hall said—and he’s the cofounder of NeuroHacker Collective—”The humanities aren’t in opposition to technology. They’re the interpretive layer that makes tech meaningful. Without them, we build faster without knowing what we’re building towards.” That’s one.
The other one that I really did like was—and I hope I’m saying their name right—Joscha Bach, cognitive scientist and AI researcher. You did their segment in ’26. “Consciousness and intelligence are not the same thing. AI can be extraordinarily intelligent without being conscious, without having inner experience, without caring about anything. The question for the workplace is, does it matter?” And I believe it does profoundly. That’s what Joscha said.
So the whole humanities thing I think is really important. Jim, I’m not sure if you remember—I had to write a thesis for that degree, and it was in 1999. And the question that you helped me draft, and you got me 100 CTOs to answer, was: are liberal arts majors the answer to the .com era worker shortage? I’ve forgotten about that. We should pull that out at Georgetown and get excited about it again. The answer was yes, and it was an overwhelming yes. And I remember that people said, “But we’re going to forget about this. We’re going to forget about it because there are going to be a lot of smart technologists.” And guess what? In 2026, there’s this huge argument around humanities, and from my perspective, bless anybody that’s going to any academic study and pursuit that they’re doing. Make sure you finish it. Jim made me finish it. And that was one of the biggest gifts of my professional career, Jim. So thank you.
But it really is the education paradox. If you start thinking about that—come on. What are we teaching people to be able to do when they leave college? My biggest thing is my son is at Virginia Tech. He’s not allowed to use AI, but his internship this summer, he has to be an AI expert to do his job.
Jim: So where are we? I’d love to hear your answer on that, Jim. This is a huge question that I have conversations with people about all the time. What is the role of AI in education? The other extreme is my alma mater, MIT, which has decided that AI is everything, so they absolutely allow AIs in any coursework. And that’s got some things that scare me a little bit. Like, do you actually learn how to reason with words? If you write your essay on the <i>Iliad</i> using AI rather than writing it yourself, have you lost something in your cognitive working set? They had come to the conclusion that no, or at least that the gain in productivity and quality is such that it’s worth it. And I will say, most MIT undergrads hate humanities and do as little as possible to get through their humanities courses, and probably writing their essays with ChatGPT or Claude, they’d probably be a hell of a lot better. The question is, is their brain a hell of a lot better? I don’t rightly know.
In K–12 education, it’s really become a problem. A woman I know who’s an English teacher at a middle school in an economically lower area has basically had to do all the writing in class. Otherwise, it’ll all be really bad LLM writing. But she has found that the kids actually like it and are reasonably good by the time they finish the year with doing all their writing in class.
Lisa: Yeah. So, Jim, I have, like, the angel on one shoulder, the devil on the other. When I think about this from the standpoint of AI—if we did allow people to use it at the primary education level, are we not teaching them how to learn and how to think? Are they just relying on their agent, and is that going to be their partner for the rest of their life? I’d love to, in ten years, listen to this podcast and see where we are again. But what Aristotle did say is the roots of education are bitter, but the fruit is sweet. So I do wonder, is there a happy medium in this? We’re sending really mixed messages to these very vibrant young kids learning around the world—working their tails off in college and high school, being told they can’t use AI, and then to get a job, they have to be an AI expert. I’m challenged with that.
Jim: Yeah. That’s a real interesting challenge. Of course, we’ve faced this before with calculators. When I was an undergraduate, calculators were banned from tests. And since we were a very STEM-oriented school, there was a lot of math necessary in exams, and you could use your slide rule—nerd alert—which we all became quite good with. But no calculators. The reason was they were very expensive, like $500, and a lot of people, including myself, couldn’t afford one. So it was considered to be an unfair advantage. And yet today, I’m sure they allow calculators in exams because no one would probably put up with having to use slide rules or doing it with pencil and paper.
So there’s an example of where we ended up coming down on one side or the other, which was: okay, we will start to get weaker at doing math in our head and being intuitive about math, but our error rates will go down and we’ll be a lot faster. As you know, you’ve seen the writing produced by most employees—most people are terrible writers. Awful. And if you take ChatGPT and tell it to go into professional copy-editing mode and to review this—review it for structure, review it for rhetoric, review it for clarity, for grammar and spelling—what comes out the other side will be better than 99 percent of your employees can do on their own, probably at least 95 percent.
Lisa: Jim, I agree, and I feel like some of it—the art of the word—is a really important thing that we all need to hold on to. When I’m writing emails, it always offers me Copilot 365 and I’m like, it makes me mad and I don’t take it. But if I have something really important to write from a bigger-picture standpoint, I’ll do that. It changes my voice. And even my agent—and I do have a question for you about agents in the future—they do try to pick up your voice, but do they always? Nothing in technology is 100 percent. So you better audit everything that you’re using.
But here’s my question, Jim. Do you think that in the future, your agent will move with you through different companies?
Jim: I think the answer to that is yes. And if it doesn’t, it should. It would be a very weird thing for your agent to be firewalled inside each employer. But it could happen. And I would say that’s a thing that we as citizens should demand—that as our agents get smarter and more idiosyncratic to ourselves, they be portable.
Lisa: Yeah. I wonder, is there a copyright to it then? And also, what about intellectual property protection? Is this a leak for intellectual property? If it’s just your voice, that might be one thing. But if it’s the big library of content that you use all the time, that might not be portable for reasons of intellectual property.
Jim: I will tell you how to get a better voice with LLMs. Depending on how much you’ve used them already, you could actually get a jumpstart by saying, “Please write a style guide that captures my voice as you’ve been watching me work over the last couple of years.” Then edit that document and attach it to an LLM prompt and say, “Write this business letter and do it in the style of the attached style guide”—and name the file “style guide.”
In fact, I have several of them. One of my favorites is “Jim Big and Bouncy,” which has things in it like, “Make sure you cuss a lot,” and “Be sarcastic and vary the lengths of sentences a lot.” It basically produces my most outrageous style, suitable for engaging in flame wars on Twitter or something. And then at the other extreme, I have one that I custom-designed that implements the Strunk and White style, which is one of the truly great styles for serious nonfiction writing. I have several other ones for different purposes. And that little trick will make you think differently about using LLMs for things like business correspondence, because you can tune that little style document till it sounds like you pretty damn well. Just play with it a little bit.
Lisa: I learned a lot just—I mean, I’ve learned a lot this whole conversation, but tonight I’m going to play with that. And I like the style guide because I know in Claude it does try to capture your voice and all of that. I’ve become—I started with ChatGPT, I used Perplexity, all these different tests and learns. But I will do that, Jim, because sometimes I’m like, gosh, that doesn’t sound like me, and I’m so about authenticity. So that’s really, really important.
Jim: And as I say about authenticity, once you can fake that, you can fake anything.
Lisa: I know. But then you’re going to get called out. You’re going to be asked to go stand on stage and talk. And if you can’t talk the talk—come on. We’re all tested.
Jim: As I say, the way to get started with this style guide thing is particularly with Claude—as you say, he’s already learned something. Tell it to write a style guide for your voice and then go through and edit that carefully. And then you can have something with the minimum amount of work that’s pretty good. You can gradually add to it. Then the other thing is, as these things see more of your work and get smarter, periodically you can say, “Please review the style guide compared to what you think you know about my style and suggest any improvements.” Do that every two or three months.
Lisa: All right. I’m doing it. I’m doing it tonight. I love it.
Jim: In talking to my AI executives—especially ones who are end-user types and are trying to do things in the context of an existing bureaucracy—they say that probably the biggest loss that especially larger companies are having with the introduction of AI is that the costs of slow-moving, frictional bureaucracy are very largely increased by small, agile, fast-moving development teams. It used to be a team that would take a year with five people; now it’s a team that gets the work done in a month with two people. The amount of drag caused by bureaucracy is way higher. And the urgency of minimizing frictional drag from the bureaucracy has gone up tremendously as development costs have gotten lower and development times have gotten faster.
I know that’s something as an HR person you’ve always been concerned about—just making sure the bureaucracy doesn’t get in the way—but the stakes are now higher, would be what the people I talk to say. Does that resonate with you?
Lisa: Yeah, it totally resonates. And what I would say is working in a PE company, you can’t have bureaucracy. You have to have pace, speed, and execution. So my answer might have been different if I was in a Fortune 500 company. But what I would tell you, Jim, is you always had a rule that when a company got more than 50 people, there would be a lot of drama, culture problems, and bureaucracy.
What I would say here is there’s a lot of communication, a lot of racy model discussions. And I do think you’re right, because there are organizations—and I talk to a lot of CHROs every day just to make sure that I’m not losing my mind, because it is moving so quickly while we’re trying to do all the right things—where that bureaucracy piece becomes really problematic. From a standpoint of your leadership expectations and the attributes of people that you hire or keep, get rid of that. It is like a cancer in an organization because it’s going to hold up progress. Yes, you can have your say. Yes, bring up these things. But bureaucracy is a problem. And the problem is because people don’t want to change, or they want to keep their organization a certain way, they don’t want to share between different organizations—that creates really bad cultural problems.
So from my perspective, one of our leadership behaviors is “talk straight.” At the end of the day, people will preface difficult discussions by saying, “I’m going to talk straight,” and that’s great. But then it can also be used in a way where people are talking straight and they’re just really mad about something. We have to call that out and say, let’s have candor in that discussion.
But I hope that in the advent of the AI transformation and LLMs, we really are getting rid of bureaucracy, because we’re shaping the future. The machines can help us, but we’re shaping the future. So the people who are conceived as bureaucrats are going to be a problem.
Jim: Yep. Of course, I’ve disliked the bureaucrats from when I was 22. But maybe now we have a way to reduce—they do do important work, but can we compress it and use LLMs as much as possible and realize now that the costs are much more significant when the rest of the organization is moving fast, when things are being held down by friction in the mill. This is a little out there, so humor me.
Lisa: I went on a safari with Phil and Andrew just a couple of months ago. And the safari really taught me a lot about work. I learned a lot because we had an amazing guide and a tracker. That world is not going to change. I was in a very privileged range—I’m very blessed that I was able to go. But my learning was about the lion. The lion will fight until he isn’t strong enough, until the next one is there. It was magical. It was sad. It was unbelievable. But it really brought me back to the basics.
And the really key point I want to tell you about my learning on a safari—you didn’t have your phones, you didn’t have anything—it was really sitting in the bush watching ancient dynamics play out that stripped away all the noise for me on this AI transformation. The guide doesn’t need to have a dashboard. They’ve got their walkie-talkies and they’re tracking animals and all of that. But they’ve accumulated wisdom, Jim, that built across years of presence, attention, and the love of their domain. No AI is going to replace that.
But no AI is going to replace that strong lion either. He’s going to get old and he will be killed, maybe even by a son. And so for me, the organizations and leaders who thrive will understand their own cycle. We really have to get very deep in ourselves to think about how we’re going to activate that future and choose to evolve or be overtaken. That is something I really wanted to say to you today because it really does connect to our humanities discussions that we’ve had for years. So anyway, I just had to throw that out there.
Jim: I love it. Eat or be eaten.
Lisa: That’s right. One last topic. We’ve talked almost exclusively about organizations as they are and doing change management and training and things. Let’s talk about the other end of the pipeline—new hires, fresh hires. What has the LLM revolution caused you all to think differently about your entry-level hires?
Jim: Yeah. So a lot. This is like a really big question at the end of this meeting. The first is we don’t know if they’re using AI prompts or not when they’re being interviewed from a virtual perspective. I think that you cannot ever discount in-person meetings with people, especially early talent, because they’ve just been developed differently. They might not have the same 7,000 internships or jobs that you and I had even before we got a job. Or have they been prepared for it?
I do think that really making sure that grades are important, clubs are important, whatever your passions are—those are incredibly important. But I am never going to lose, Jim—and I don’t want my talent acquisition team to ever lose this either—in a professional services organization, do you have the gut for what we’re asking you to do? Do you have the learning agility? Talk to me about how you’ve learned something different. How do you feel about change?
Jim, it’s still the basics. It’s still—close your eyes and think about when you’d send me out to Silicon Valley at job fairs, and I would talk to these kids from Harvey Mudd and Stanford and all those great schools. I just think they’re prepared differently. They have great talk tracks, but do they have it in them? So you’ve got to test that out.
Now, I always said to you I didn’t believe in psychometric testing. I do today for more senior-level and team assessments. My only reason—I won’t use, well, I will just say the WonderLic—I know what they test too, but I would prefer to use assessments that really help me understand what I need to develop you in. If we believe in you enough to hire you, I want you to be successful. So I want to know your flat spots, your weak spots, your strengths. And then I’m going to overlay that on your team, and then we’re going to see how it’s going to work and where there’s potential conflict.
So, Jim, for me, I think all these early-talent folks are learning differently. It is like the Hunger Games of getting internships. But it’s really about who’s going to take a shot on you. You took a shot on me thirty years ago.
Lisa: There was no reason why you hired me, but you did. I could tell you were a quality person. I did an awful lot of eclectic hiring. I would have long interviews with people—ninety minutes at least. And I asked all kinds of weird questions. At the end of that, I would make a call: is this the kind of person I want on our team or not? I didn’t pay nearly—in fact, I couldn’t even tell you the grade point average of anybody I hired. I didn’t give a damn at all. I looked at the courses that they’d taken, the jobs that they’d had, and if they were a new hire, other activities that they’d done, et cetera. But yeah, there is some imponderable which formal process will just never catch—the top performers. Remember how we always talked about we’d do anything to get the A-pluses? We would fly to them, we would drive to them, we would do whatever it took.
Jim: And the A-plus also had to really work in our culture and not put sharp elbows on people. And from my perspective, it was really: be part of the team, be a good human, be a good colleague, have fun, work hard.
Lisa: And you were rewarded for that. You really were. Yep. And those skills are still going to be hugely important—probably more important than anything else, particularly for young hires. But is there a specific thing you’d be looking for today with respect to people’s AI skills?
Jim: Yeah. I mean, having that intellectual curiosity—from an AI skill perspective, I think they need to really have and hold on to that curious side of being intellectually honest about whether that actually fits what they’re trying to solve. Because don’t be lazy. You can just cut and paste now, and that could get you in really serious trouble. So from my perspective, I’m going to do this—your style guide idea and the prompts is really, really maybe a game-changing comment from what we’ve talked about today.
Because I think that I’m not confused that AI is transforming work. I’m not confused on that. But what I’m curious about is whether it’s going to transform how people think and work. You can save seven and a half hours a week—that’s what the statistics say—just using a few agents. That’s great. But do you own your work? That’s a really big piece of it for me. And do you believe in what you’re saying and putting in writing?
Lisa: Absolutely. Alrighty. I want to thank Lisa Buckingham for an exceedingly interesting conversation at the intersection of AI and the human factor in work.
Jim: Yes. Thank you so much, Jim. I am really lucky that I got to have this conversation with you. I love this.