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Lead The People is your guide to unlocking your true potential as an authentic leader. Hosted by Dr. Matt Poepsel—The Godfather of Talent Optimization—this podcast dives deep into the art and science of what it takes to lead at the next level. With insightful conversations and practical strategies, each episode equips executives, strategic HR pros, and aspiring leaders with the tools it takes to boost performance, inspire teams, and drive meaningful impact. Whether exploring the latest workplace trends or tackling real-world leadership challenges, Lead The People offers an enlightened approach to leadership. Embark on a rewarding journey to become the leader your people deserve—the leader you were meant to be.
Lance Neuhauser (00:00):
It's not AI that's going to take your job. It's someone who uses AI that'll take the job. That's scary, that's daunting. And adaptability has since the existence of humankind been the trait that has led to us being here or not. So long as you have that curiosity, that ability to provide the context as to what's in your mind and what you're trying to achieve, that you bring that critical thinking and you come with that confidence, there is more potential opportunity for the individual than ever before.
Matt Poepsel (00:42):
Lance Neuhauser has spent his career leading companies through moments where the old playbook stopped working. He knows what a real inflection point looks like and he's been saying for a while now that the workplace inflection we're going through now, it's different. Not incrementally different. The kind of different where the assumptions leaders have been operating on for decades are actually up for debate. As the CEO of the Predictive Index, he sits at a specific and unique intersection. It's a company built on a deep understanding of human behavior at work, but it's also in a moment where the role of humans at work is genuinely in question. He's watching AI reshape the question of what work even means. That's the conversation we're going to have today. Lance, thanks so much for being on Lead the People.
Lance Neuhauser (01:21):
Matt, thanks so much for having me here. It's a joy to talk to you.
Matt Poepsel (01:24):
Well, I mentioned in the opening that you've built and led companies through a lot of different shifts, but you've been clear that there's something different about this moment that we're in right now. What is it that you're seeing that characterizes that viewpoint of yours?
Lance Neuhauser (01:36):
I think the easy answer is to just say AI. I think it goes certainly significantly deeper than that. It's affecting the individual who's right for what role and what role they play in the organization in total. It's affecting the way that teams are actually built. It's affecting the way that organizations as a whole are designing their financial and strategic plans. It is affecting the market and the competitive pressures that are being applied to just about every institution, government, education and commercial. And so perhaps never before in history how all of those institutions have to redesign the way that they work at the same time and do so using new technology that caught mass adoption faster than anything else and do it in a way in which the humans need to work and rely on this, but also not break the human system that is required to actually bring the work to market.
(02:43):
And so yeah, I think there's a lot going on.
Matt Poepsel (02:45):
It's so true and it's not as if humans were in a great place to begin with when all this stuff started happening. We were coming out of the pandemic. We still had not even learned and still haven't learned, in my opinion, how to do remote work super well. And then all of a sudden we're getting these economic headwinds for a while, so there's been some concerns. Now it's like, "Hey, I got an idea. Why don't you just figure out how to adopt this thing that looks and sounds a lot like you? " And people are like, "What are you talking about? " And it's so pervasive just as you pointed out.
Lance Neuhauser (03:11):
The trust, the institutional trust was already relatively challenged for the factors that you mentioned, Matt, and it was just starting to be built back up and that trust was broken in two ways as AI started to be rolled out. One was the trust in oneself that oftentimes the biggest issue that's standing in the way from people actually adopting and understanding the benefits of AI is confidence, that it requires really not much more than curiosity, context, and critical thinking. And if you bring those three things to AI, then your confidence will boost. And people who do that have a tendency to see how much it can actually free up a lot of the cognitive load that they are facing in order to put that very precious cognition time on the things that we need or prefer depending on where you are in your life. Organizationally broke trust when most institutions saw optimization as the way to leverage this as a way to very quickly improve the numbers in their organization and presume that we could do a lot more with a lot less, which in some instances is very true.
(04:36):
To think that that is uniform and then oftentimes have the middle layer of the organization who has now been thinned expecting to do significantly more in terms of management, expecting to institute these new processes and technologies to adapt themselves to an entirely new way of working is causing the organizations to be hollowed out not just in numbers, but also in spirit and productivity. And so there are ways to actually do this to where you're taking advantages of what's available and you are setting up the organization for a higher likelihood and degree of successful implementation and using these tools to gain trust not to break it.
Matt Poepsel (05:32):
I think that that's delightful to know that that's possible. It certainly doesn't resemble the experience that I hear most often today. I think that the availability of the technology caught a lot of people off guard. And at first it was the generative capability because for the first time we had access to technology that could do things that historically only we could do. It could write poems, it could do songs, it could do things that were kind of exclusively our domain. I think when it got into the hands and then CEO started looking at it and saying, oh my gosh, in a market where our top line is somewhat capped, we hadn't seen growth like we had before, we still need to provide a tremendous amount of return. How can we get efficiencies and optimize, as you pointed out? I think it's this weird thing where there's a sense of loss.
(06:18):
It's the psychology of loss in some way happening at a time when the things that rationally make sense, they just don't land in the spirit in which they might be intended sometimes.
Lance Neuhauser (06:27):
There's certainly a lot of organizations that are facing organizational loss grief as a result of the identity of the organization changing. Now my job is to work with humans, sure, but also work with agents to have agents work with one another as part of the team. And that new dynamic means the old way has ended and there is a new. And when there is a new, it can be very joyful and we oftentimes grieve what was. It's also happening at the individual level. One of the most salient examples that I heard was think about a junior analyst role from 2022 versus 2026. 2022, you went to school to be that genius spreadsheet navigator. You were amazing at coming up with processes in order to produce output very, very quickly. You figure out ways to eliminate risk and error and be super, super compliant. That's 2022.
(07:28):
And then all of a sudden 2026 shows up and the AI is more machine-like than we treated the humans and trained the humans to be. And so what does the human role become when the machines have become more machine-like? And so now that junior analyst needs to have judgment around all the output that comes, it needs to have the curiosity to dig and find new ways to examine whether we are really being as thoughtful as we need to be. It needs to be able to architect loads of context in a way that could be truly understood by the agent. And it requires this set of critical thinking to bring other sources of information to the table to help the AI connect some dots that otherwise wouldn't. I think it's Arthur Brooks that calls it crystallized intelligence instead of fluid or intelligence. And that's a completely different behavioral profile of that individual.
(08:31):
It might be that someone went for business on the one hand. Now you need someone who is fluent in the liberal arts for some of that work output. And in the agent creation, you might need someone who is really, really great at understanding formal systems. But in the idea generation, you need someone who has the ability to socialize concepts and get people rallied in order to put the effort behind it and the capital allocation there as well. It's a total redesign of the way that work has been done.
Matt Poepsel (09:00):
It truly is. And I wrote a piece for Forbes recently and it was exactly this. A lot of times we go to people who had detail-oriented work that could be done better and faster and more error-free by the machines and we say," Isn't this great? Now you can be strategic. "And they're like, " No, this isn't great. I love doing that kind of work. "And then how do you say to somebody," I'm sorry, but now there's a capability. "You might've had a relative that was a toll taker back in the day. Well, those are gone now. So you have to respond with empathy to look and say," I'm sorry that you're experiencing this loss because the thing that you really enjoyed doing for the last 20 years is now gone the way of the machines, but there's still valuable work for you to do. And I think that's where we haven't really connected those dots, so to speak, to saying there's still tons of things in the company that are a fit for your personality type and we need you to do those things because it's actually better for everybody involved yourself included.
(09:51):
How do you help them bridge that? And especially at a time when you're thinning out those middle management ranks that can actually pull that off.
Lance Neuhauser (09:56):
That's exactly where I was going too, that same middle layer that has the institutional and domain knowledge. The example that is common here is that if I pick up a knife and a chef picks up a knife, the chef's going to do wondrous things that I cannot do. If I go to Excel versus an accountant going to Excel, they're going to do extraordinary things that I will not know how to do. If you put an accountant into AI to try and figure out ways in which to do better accounting, to understand better capital allocation, they are going to do that much better than the average individual. AI can make good very accessible. It makes good very accessible to the average human being. What is extraordinarily difficult still is excellent and what requires excellence in this day and age though, cannot just be the human thinking because you're not evolving at the speed in which thought and work and government and education needs to evolve, but you also need machine.
(10:55):
But machine doesn't have that institutional knowledge. It certainly doesn't have the ways to yet crystallize topics and bring new examples and thinking into its logic. It needs the direction. Once you put those two things together, then all of a sudden you have extraordinary new opportunities that start to emerge to use those skillsets to generate new value. Again, depending on the institution we're talking about, value can mean very, very different thing.
Matt Poepsel (11:24):
And it's the biggest adjustment I've had with using AI too is that sometimes you have to look at the tasks that you used to do and say, I still have value to add on top of this, but it's actually not in my best interest to do some of this stuff. I'd be better served developing a skill, teaching it how to do certain things that, well, if I make that investment, it's going to make us both better because of it. And it's not going to eliminate me or make me redundant or anything like that. But if I continue to do things that the machines can do just because it's familiar to me, that's not the right reason to keep doing it.
Lance Neuhauser (11:57):
That is true. The phrases that we've been using have been in the loop versus above the loop. The work that has been in the loop is starting to go away at, I think, an alarming rate to certain sectors of industry, especially the lower rung of organizations drying up these junior level roles, they were in the loop. The problem there obviously is that's how you cut your teeth. That's how you gain the institutional knowledge so that you can end up having the ability to impact the organization. One way, by the way, to still bring in that junior talent, this is certainly going to sound self-serving. I don't mean it to be, "I just believe what I'm doing. I believe in what I'm doing." One way to do that is to actually realize that there is some very real behavioral characteristics of someone that might not even have the institutional knowledge yet that would be super, super advantageous to the new creation of output and work.
(12:58):
The ability to actually look at that output and QA it on a regular basis to see if it is being consistent, the ability to create new constructs for connecting different data sets and prompting together so that the loop is actually designed in the most effective way. These are roles that people without the institutional knowledge can play a very real element in designing and helping. Oh, by the way, they end up learning the institutional knowledge along the way. So the difference there is matching work and work output needed to behavioral characteristics. And then you'll find a whole new way to include the junior rung. And then the other sliver that is getting hit relatively hard are those that are not adapting. Just your point, not adapting and realizing that there is this possibility of moving from in the loop to above the loop and using their institutional and domain knowledge to push these tools further, faster, make them more applicable to more settings inside of their organization or institution and actually be able to train these skills and point these skills in a direction that will, again, return most value.
Matt Poepsel (14:15):
There was a time when job market was so tight, it was hard to find talent and pull them out of other organizations. So you ended up hiring people that maybe weren't a perfect fit in terms of their experience and you just were taking on the responsibility to train them or get them up to speed. And that was an expensive proposition then. Now it seems that it's more fruitful than ever because you might say, "Well, I don't have a big L&D department. How am I supposed to come up with training programs?" The answer is, "Well, you've got AI and you've got five minutes, so guess what? You're a lot further along than you used to be. " And it seems more feasible and reasonable than ever to hire people that don't have that full skillset. It breaks my heart to see what's happening to those entry-level workers who are graduating from college, coming in and finding the job market is either frozen because some executives are saying, "Let's not hire for this yet.
(15:02):
Let's see if AI can do it. " Or saying that, "I don't have that kind of work for you. I'd love to hire you, but what am I going to have you do? " And I think that it's just that's a reflection of our creativity of that excellence you talked about earlier, understanding what really does add value to your company. I think there's an entire absorption that we have to make about how value even works in the future.
Lance Neuhauser (15:22):
We have some internal phrases that we've been using as some strategic tenets, guidepoints, whatever you want to call them, which is let's hold for a second that everything we've talked about in this so far is true. I realize it's a lot of editorial, but let's assume it's true. There's enough smart minds, certainly outside of myself that I'm learning from that are saying some of these same things. It means that the hard work has nothing to do with AI, has nothing to do with AI. The hard work has to do with focusing at first on what problems is this new shifting landscape creating for our business and what processes do we now need to put into our business as a result of these transformational shifts as well? So you focus on the problem before you focus on the technology and you focus on the process before you focus on the automation.
(16:19):
If you do these two things, if you realize what's happening in the marketplace, if you realize what's happening to your competitive set, if you realize what's happening to your industry to your role, to your team, to your role, all those different layers and ask yourself the hard questions and do the work that says, what is the problem now and how do I solve this? Then the joy that AI will bring because of how much faster you can solve those do issues, the ways in which the work can get done quicker, more effectively, less error-prone, more secure just allows us to free ourselves up. There's a lot of pessimism out there as to what can happen. I can paint that picture with the best of them. What I don't think is there's a lot of folks painting the optimistic picture and I think there's a few stats that I'm hearing, one of which is the consistent decline in working hours per week that we have been in since the industrial era just continues to come down.
(17:24):
And I am optimistic that people will find uses for their time that bring us back to almost more of a Renaissance age. I don't think we're there yet. We're still certainly beholden to things like social media and gaming and what have you. But I do think there is more of a craving for the arts as everything becomes AI produced, what is actually handcrafted. I think there could be a Renaissance era on the cusp. Also, as we see AI's ability to go back and look at errors of the past and things like coding and scientific study design in order to actually reach new breakthroughs because things were written off in the past, but there was biases or some kind of element that was hidden in there that no humans are able to find. Now AI is able to find it so much faster. It could be ushering in what I'm hearing is an age of honesty when you know that these will be found, these issues will be found, you try to hide something, it will be found that people bring a new level of integrity and ethics into all that they are doing.
(18:25):
And then the last thing is this moment in time that we are almost coming to from a crescendo perspective needing as globalization as the supply chain for the materials that are needed for this technology to even exist becomes the new gold, new nuclear, new insert here, potential mass capitalization or mass destruction as that becomes more readily available and there's now this new time that's available and these hard questions being thrown on the table that we usher in this new moment where philosophy and ethics becomes one of the higher studied orders and we finally put on the table some topics that we've been delaying putting on the table for a long time.
Matt Poepsel (19:11):
I think that the bringing the balance is so important. It's so much easier to push headlines with that dystopian view of what's going to happen because that gets you the clicks and all these types of things. But I think that the equal opportunity as you're pointing out that we could see something very positive, this renaissance you're talking about is going to, it's a choice really. It's going to come down to us. But I think we're not far away from an employer being able to say to candidates that you come here and we use so much AI so that you can have a life, that we are trying to find a way to get some of that work-life balance that a lot of candidates want these days in an increasingly mechanized world. I think it'll be a real employer brand asset and position to take when we start to get good at the other parts.
(19:55):
We're clearly in the earliest phases of AI where we're trying to just figure it all out. But I think that renaissance that's going to happen potentially for us societally could become a competitive differentiator for our companies too.
Lance Neuhauser (20:07):
100%. I think for our companies, our educational institutions and the governments that embrace this as well. This is what I meant earlier when I said every one of these institutions needs to redesign how it's working. Yes, there could absolutely be corporate entities that help draw in the greatest talent because they provide the greatest ways in which AI can elevate your personal self and your life that help you achieve your aspirations that help you impact the way that you want to impact that the educational institutions say, "Oh my goodness, by the time the kids walk into this world, what world are they walking into?" And ask that question and start teaching them the subjects that are required for them to be successful in those areas, things like critical thinking, things like ethics and philosophy and how to be curious, how to think on your own, how to use assisted thinking.
(21:07):
And there are methods by which very smart advisors are coming up in all those institutions, that's actually what's happening right now. People continue to be like, "Oh, the machines and machines." That is true. And there's this Jevon's paradox is making its way around every circle right now. People thought the coal industry was going to collapse when steam engines came around because it was so much more efficient, but because the efficiency of the Steam Engine, there were so many more uses for the Steam Engine and the Steam Engine ended up booming so the coal industry ended up growing instead of coming in. That's what people are projecting that is actually happening with AI and the need for services, advisory and consulting, that this may be the number one advisory moment in the history of industry because of the amount of institutions. We've seen it in our own organization.
(21:56):
We instituted AI organizationally. Why? Using a subset of experts. And guess what happens as soon as people actually got over, because we measured confidence, that's what we were going for. The kickoff was all about, are you feeling more confident? And all of a sudden as people started gaining more confidence in these tools, what ended up happening? The demand for questions going back to the actual people who knew this best grew, grew. Now, ideally you also grow in your curiosity that says, "Hey, I go back into the tools and I ask them as well." But then you need to bring, again, new insights to these tools. So you have to engage with all these human beings who are studying other things, who are experts at different things, who have different profiles that you do so that we can think through these things from all the angles and then allow the technology to ultimately bring the best of what it can bringing its thousand interns into play its thousand different points into play process quickly than we ever could.
Matt Poepsel (22:55):
And I always say that every business is a people business and AI doesn't change that. It actually, in some cases it levels the playing field because if AI can do it, it's already commoditized in my view how you utilize the AI, the human system you build around it, that will be the basis of competitive differentiation in the future and you don't just get to have that. And one thing I'm really encouraged in this conversation is that it is forcing all of us to change. I think when you talk to workers as individuals, they feel like I'm being put through a lot, I'm being asked to change, it's only me. No, we're already hearing that the managers are being impacted and you hang out with CEOs, they're being impacted too. CEOs are having to have an entirely new capability and way of thinking about their own business.
(23:38):
I think sometimes we discount how scary that is. If you're a CEO and you've been running your company for a long time, you got it just the way you want, here comes AI, you're like, "I didn't ask for this. " That sounds a lot like what individuals down on the floor are saying too, but it just feels different, but it is true.
Lance Neuhauser (23:53):
There's a phrase that I think it was Jeff Bussgang who made popular in his book where he said, "It's not AI that's going to take your job. It's someone who uses AI that'll take you the job." And so that's scary, that's daunting. There's grief there. We talked about all that on this already and adaptability has since the existence of our humankind been the trait that has led to us being here or not. It is arguably one of the most important skills that needs to continue to be honed and taught in a different way than ever before. Change is happening at an accelerating rate and own adaptability and you are set for light. And now the ability to change direction faster into more topics more easily, the ability to pursue what comes naturally to us is all there more readily available than ever before so long as you have that curiosity, that ability to provide the context as to what's in your mind and what you're trying to achieve, that you bring that critical thinking and you come with that confidence, there is more potential opportunity for the individual than ever before, than ever before.
Matt Poepsel (25:12):
And I think that this is the best part about work is the human system that makes it, that creates value not just for the economic value of the firm, but also for the career value, sending people home to their families better. All that stuff is there for the taking and AI doesn't make that go away. It changes how we're going to get that. But I think for people that lean into leadership and the people practices, it's never been a better time to get really good at those things. It's exciting.
Lance Neuhauser (25:40):
That's right. And yes, there are the warnings all over the place, misguided, overused, misused, not thoughtfully done and this type of power exacerbates issues. It doesn't solve them, it exacerbates them. So there's a responsibility that comes with all this power at the individual level, at the team level, at the organizational level, at the industry level, at the global level. There is a responsibility that comes here. It is hopefully an awakening to that reality of the power that we all hold as individuals and how we can use it to actually become more human, not less human, more human.
Matt Poepsel (26:28):
And I think that really is attractive to the listeners of this podcast for sure. We talk incessantly about the opportunity, if not the responsibility to get the people part right when we're leading organizations, et cetera. So this is really a timely conversation for us to be having. But as we're moving toward the close here, I do want to ask you the question, Lance. You've taken over the predictive index. What role do you want PI to play in shaping the future of work based on everything we've talked about today?
Lance Neuhauser (26:56):
I want that positive track that we talked about to be helped and accelerated by Predictive Index. It sounds lofty. It sounds lofty. And there are very few companies that have the right to play in the space of being a behavioral intelligence layer that for the most important conversations, the most important moments inside of an organization, especially as you go through all this redesign, especially as you look at the human element that's here and yet Predictive Index has a right to play there due to its 70 years of history playing there. There are very few organizations that will have the trust and the history of trust that's required in moments where trust is so needed. If you're going to say, "I'm now going to have a conversation with Matt that's really, really challenged and I want something, this is where we can evolve ourselves, become more human, where I want to be able to say to Matt things in a way that he will hear it, how it was intended, especially as interactions get shorter, augmented with AI, especially as the amount of humans that are doing this work becomes more focused, that translation layer so that we can understand one another becomes so critical.
(28:21):
And so I do see Predictive Index playing a role at helping one another understand our behaviors from human to human, from human to AI, from AI to AI so that the whole system has the ability to actually understand one another better. And I think we have the right to play there. I see it in the people and in the data and science that exists inside this organization that we have the foundation from which to bring that and we have the mission and the drive to make better work in a better world. And so I feel so grateful and lucky to be inside an organization that has all those things and can make, even if a sliver, a meaningful impact in all those areas.
Matt Poepsel (29:04):
I'm excited because it's very powerful. PI has been a part of my life for 20 years. The science allowed us to be better humans to one another, but we also built better businesses along the way. That's why we have 10,000 clients. That's why it has 70 years of history because it works. And while the next 20 years is going to make the last 20 years look like, I don't know what, that opportunity's there just as you painted it. So I love that. That's very well said. I want to do something here, which is to give us a completely hard shift to something I truly enjoy doing, which is to have a trivia question. And there was a time when you and I were having a conversation recently, you were telling me about a Saturday, you were doing some car shopping, car buying, and I think AI kind of counseled you that this might not have been the best use of your time.
(29:47):
So what I thought we would do here is have this question for us, which is about famous cars because I'm not a car guy. We'll see how this works, but it's a multiple choice question for you. Here it is. Which famous British Secret A Agent is most famously associated with driving a sleek gadget filled Aston Martin DB5. Is it Ethan Hunt? James Bond or Jason Bourne? There you go. AB or
Lance Neuhauser (30:09):
C. James Bond.
Matt Poepsel (30:11):
James Bond. Okay, there you are. Audience, you're playing along at home. Who drives the sleek gadget filled one? We're going with James Bond and I have a feeling we're right spot on, nailed it. The Aston Martin DB5 made its appearance in the 1964 film Goldfinger. There you go. Smoke screens, oil slicks. Is this what you got in your car, Lance? Did you get all that stuff? Passenger ejector seat? You got all that. Yeah. Nice.
Lance Neuhauser (30:32):
I just haven't had to use it yet. Not yet. Well,
Matt Poepsel (30:35):
I got a much better question, which is where can my listeners go to learn more about you and about their Predictive Index?
Lance Neuhauser (30:40):
They can come to predictiveindex.com. You can find me, you can find about a company. You can stay up to speed on how we are going to help make the better work and better world. You can reach me on LinkedIn, Lance Neuhauser, N-U-H-A-U-S-E-R. I'm happy to talk about this and any of the other topics that we talked about on this pod. Matt, I can't thank you enough for having me on.
Matt Poepsel (31:05):
I really appreciate it, Lance. Listeners, I'm going to have those links for you in the show notes. You're only one click away from getting connected to PI and to Lance. Lance, it's been amazing. Thanks so much for making the time.
Lance Neuhauser (31:14):
Thank you.
(31:19):
Here are my top three takeaways from the conversation that I just had with Lance Neuhauser. So the first was all about culmination. When you heard Lance talk about how the explosion of these new AI capabilities and a bunch of other forces all came together at the time and that's what's resulting in this tectonic shift that we're seeing in the workplace. So much is changing, but I think sometimes we shorten it down to just, oh, it's all about AI or it's all about this one thing. It's actually a lot of things that just happen to come together, but it is having a tremendous impact quite obviously about the way work gets done, how we define our role within it. And that leads me to the second takeaway, which is all about adaptation. Being able to honor the past, recognize when we're having to move on from something perhaps that we used to love to do or we're changing a structure of how a team works, whatever it might be, it's a very natural thing to go through that.
(32:11):
But to be flexible, to adapt, to be willing to have the courage to redefine the way that we approach the work, the way that we define what value is, the way that we relate to one another, all that has to adapt. And as Lance pointed out, that's something that we're really good at as humans. We've done it for a millennia. So now's our latest chance to prove just how adaptable we are. And the final one is opportunity. I think just as Lance said, there's so much doom and gloom, there's so much dystopian and fears related to all the workplace changes that we're absorbing right now, but that's not the only story that remains to be told. We do have this opportunity to enhance the positive aspects of what work can be and how we can relate to one another and how we can be more human even in an increasingly technical world.
(32:55):
And we might see that renaissance, Lance talked about this flourishing and a return to things that we're super passionate about that compliment the work we do. How do we bring some of that philosophy and liberal arts and other types of things into our work because that's the domain where value will continue to live even beyond a very robust investment in technology and process and all of those things. So I really enjoyed my conversation with Lance. I certainly hope you did as well. If you're a PI lover out there, I think you can tell PIs in good hands. So that's it for this week. As always, don't just manage the business when you can Lead the People.