Speaker 1Hello and welcome to Don't Stop Us Now AI Edition. I'm Claire Hatton. And I'm Greta Thomas. AI has been described as
Speaker 2the most transformative technology since the harnessing of electricity. And we are here to keep you in the loop for what you
Speaker 1need to know and do in order to stay relevant in this fast changing world. Each episode we bring you leading experts and together we explore how you can stay ahead of the curve and in the know for what skills will be valued in the future, how jobs may change and how industries will evolve. So why not subscribe to stay in the loop and without further ado
Speaker 2enjoy this week's episode. Hello and welcome to this week's episode. We've got a bit of a different one today because we're lucky to have two guests.
Speaker 3That's right. Mark Winter and Laura Gordon are co-founders of Libra Collective, a New York based consultancy focused on how leadership and work should be changing in the age of AI. Prior to this, Mark spent 15 years at a transformation consultancy and has lived and worked in more than a dozen countries. His now co-founder Laura also spent 10 years at the same transformation consultancy, as well as consulting in brand and marketing strategy, along with an MBA. And Laura and
Speaker 2Mark founded Libra Collective at the start of this year after realizing something. Some of the most searching questions about where AI was taking business were coming from leaders inside big tech. So that sent them into deep research around AI native companies, the ones built from the ground up around generative AI. And Mark and Laura have agreed to share some of what they've learned with us today, which is great.
Speaker 3Absolutely is. So in this conversation, you're here. What surprised the most about how AI native companies actually work? Why it's so often the C-suite holding back internal AI transformation? The surprising thing that one CEO with a PhD in machine learning forbids his company to do with AI? How a legacy financial institution is building an AI native version of itself? And why a fashion brand with six people is outpacing rivals five times? I really love how Mark
Speaker 2and Laura have this unique perspective that spans both legacy and AI native businesses. So without further ado, let's get into it with Mark Winter and Laura
Speaker 3Gordon. Mark and Laura, welcome to Don't Stop Us Now, AI edition. Fantastic to have you. I know you're going to have lots to say and lots of really interesting insights into the, world of the AI native. So the first question is we always like to ask our guests, and we'll ask you both this. So I imagine you're at a dinner party sitting next to somebody you've never met before, and they ask you, what do you do, Mark?
Speaker 4What do you say? Oh, I go first. Okay. I say I founded a leadership firm for the AI era, and I help leaders make choices about their business. And I say, I'm going to go first. I'm going to go first. I'm going to their business, and their workforce in the era of AI.
Speaker 3Brilliant. I'm sure they either glaze over and say, what was the football score? Or they say, wow, that is fascinating. And I know our listeners would be in the second bunch.
Speaker 4They usually have follow-up questions.
Speaker 3Brilliant. And Laura, what about you?
Speaker 5Well, Mark's just given a very good summary of our experience but I think if someone gives me a funny look or if I think they maybe don't care too much about my line of business, I will sometimes say I'm focused on empowering humans in this era of rapid AI transformation.
Speaker 3Yeah, brilliant. And that's what you both do with your company, Libra Collective. What led you to actually start Libra Collective?
Speaker 5So it was sort of a convergence of a few different factors. The first being Mark and I have spent collectively decades in professional services and consulting specifically. And in the past several years, I think what we've been noticing is that from the leaders that we work with every day, this consulting model has not really been serving its purpose, especially in this age of rapid transformation. And leaders can barely plan for the next six weeks, let alone sign up for a six-month transformation project. And also with the proliferation of AI tools around us, if you were to design a consulting model of the future, it would look very, very different from what you have today. The other sort of data points that are important to our story are that given the rapid pace of change, what we're hearing from leaders in this moment is that we're actually all concerned about the future. We're all concerned about the future. We're all kind of grappling with the same questions, no matter what industry you're in, no matter what side of the AI maturity spectrum you're on. We're all asking ourselves the same questions and they're all fairly existential. And so leaders are actually looking for insights and advice from their peers more than they ever have been. And so that's something that we realized actually requires a different approach to creating and collecting intelligence from leaders. It's very human. It's very relational. And then. I think the third is that we really had some interesting questions put to us by leaders in big tech who presumably are the ones leading this AI transformation, but who are also, again, grappling with the very same questions. So we realized, hey, you know, if they're asking themselves these questions, everyone's asking themselves these questions. And that's really what led us to create our hybrid think tank and advisory model.
Speaker 2It's, yeah, it's disconcerting, isn't it? When the guys who are inventing it, you hear are also struggling organizationally with the implications internally for their own businesses, which we know is true. Mark, you know, what does the collective in Libra Collective mean? Laura talked about leaders have a hunger to learn more from their peers these days. How does that kind of play out? It sounds fascinating.
Speaker 4Yeah, collective has evolved from, it's a collective of leaders doing the sense-making, but it's really at the heart of it about collective intelligence. Knowing that I think that we're at year zero, in terms of how work happens. We're all, as Laura alluded to, asking ourselves some very deep existential questions about how work happens. And, you know, to add to your point, those that are making the shovels have no idea what people are doing with them or the work that they're making. And I mean that respectfully, it's just a mad era. And to that end, we believe that we could add value in our very vast networks between the AI natives. Those are organizations that are kind of making the future. I'm into existence post-2022. And those that are wrestling with it, those who, you know, from legacy organizations who are navigating that transformation. And together, I think they will answer how work happens in the future. It's not going to happen from one, I can guarantee you that, or the other. That's the collective model that we think is really, really relevant right now. And because I think wisdom itself is essential to guide how the future will be made and those that are actually, really making it right now, they're so young. They don't have the context, right? That they need to understand what's really great there. But that's ultimately, I think, part of the intelligence that we hope to bring forth.
Speaker 2And how does that play out practically? Do you bring, you know, small groups of people together, for example?
Speaker 4Yeah, well, we're in constant interview mode. So we are always meeting organizations from across the AI maturity spectrum, from the AI natives to the AI first. We talk about what that means. And what we do is we take very singular organizations through a journey or an experience where we present a lot of the data of what we've learned and use that data to help them make choices about their own individual business and organization. I would say there's one theme that they often bring and insight is this idea of agency. Leaders are really craving it. They feel like AI, the AI era is happening to them versus they're using AI to actually shape their business. And so that intelligence that we're understanding every day signals from org structures to automation wins to ethics. You know, all that comes to the forefront out of which we bring to readers so they can make their own choices.
Speaker 3It sounds like a really fascinating process. And we're really interested in what you're learning from the AI native companies that can really help inform the AI first companies. And first of all, let's, sort of talk about what does AI native mean?
Speaker 5So I think this was actually sort of critical line in the sand that we had to draw when we were thinking about sort of how we define the AI maturity spectrum because the term AI native has been thrown about in many different contexts. And I think it's sort of subjective depending on who you speak to. But for our purposes, we've defined it as company that has been founded post generative AI. So both their product and their ways of working are inextricable from generative AI. And their business model relies on it and their ways of working are fundamentally shaped by it. And that's different from AI first, which are companies that are, you know, potentially just self-identify as such or have really made meaningful progress in enabling their core product with AI and also have made progress against using AI first ways of working. But as one of our collective members quipped the other day, like, it really is more of a mindset than it is a definition. And what we also joke about is when you look across the AI maturity spectrum, sort of early in the journey in transformation, AI first, AI native. And some companies, they're all of that, depending on the function, depending, you know, the tenure and the sort of roles of people who are in within each. So it's not necessarily usually exclusive and it can contain amplitudes.
Speaker 3Yeah, that's really interesting. And yeah, I can imagine that there's such a different level of maturity across organizations. And this is probably a big question, but what surprised you the most about what you learned from the AI native companies?
Speaker 5Well, I think two things. One is that, to be honest, they're asking themselves. The same big questions that we all are. They're using this technology meaningfully and it's baked into their products. But even as they're adopting it in their own ways of working, it's bringing up really existential questions for them of essentially, like, what is my role, not just in the workplace, but what gives my life meaning if it's not the work that I do every day? So, you know, we are speaking to a chief product. We are speaking to a chief product officer at an AI native cybersecurity company. And he basically said, you know, the AI has gotten so good that I have to ask myself, am I going to be babysitting this thing? Or is this actually going to be representative of a sort of step change in my own skills? And ultimately, I think the big concern is that there's some amount of cognitive rot or what we call kind of the dopamine deficit where we as human beings get a lot out of problem solving at work. And if we're working with tools that kind of take away that element of our day to day, what's left? That's one thing that we found super interesting. Mark, do you want to jump in?
Speaker 4Yeah, I'll add to. So I think the fact that they're young, fast, that's no surprise. But I will say that when you inhabit that space for so long, I feel like those founders enter a different paradigm. It is more about what won't this thing not touch as a thing eventually. So the way they think about shape a firm, for example, like maybe it's just four of us who need to be running this, you know, $10 million business. You know, we might do it 30 now. Eventually, we'll automate that. And it'll just be a proliferation of other types of businesses that'll be wider, more efficient, etc. And that to me is really interesting to it. Because I think when you spend enough time. Talking, building agents, talking to them, etc. It's hard not to be awed by its power, but also you take for granted some of that power itself. You were speaking to an artist today. He's like, yeah, to me, it's just like a calculator, you know. And I found that really interesting because when you see these agents calculators, then it's like it's just a utility to go build the next thing and the next thing and the next thing. So they're very much like seeing a world that's fully agendified in a way, you know. And see possibilities everywhere. That to me was really inspiring. You can see the power of just being in that space 24-7.
Speaker 3And I guess for those companies that are transforming and, you know, companies that have been built, say they're at least 10 years old, perhaps, you know, much older. Is that mindset something that is very hard to grapple with? I would imagine it would be.
Speaker 4Massive. Massive. You know, my work. It's always been, you know, at the heart very often working with really older legacy companies, getting clarity on purpose, honoring that and using that as a platform for transformation. And very often I used to say it's about connecting the business strategy to the people strategy was our past work. The work of today is connecting the business strategy, the people strategy and the technology strategy. And the people are very much like friction, I think, in the change. And that to me is really interesting. Because those that are really holding back the transformation are very much the C-suite, right? They don't understand those tools. They understand it's power, but it's not something you can delegate away. It's not like I think like what was a digital transformation in the past where, OK, there's the Internet, there's cloud, like we understand how it can affect our business. I think this you really need to get your head around to understand what the shape of the firm should be and also what you should hand over to the technology. What? Where you need to build a motor out. It's a very interesting time.
Speaker 2It certainly is. And Laura, with AI native companies, my assumption in order for them to kind of move so fast and if you like outsource so much to AI, is that probably the founders come from that technology background to be so comfortable with tech and the like. But is that right? Or what are you seeing?
Speaker 5Yeah, I think we're seeing kind of one of two. So there are, you know, AI natives that are highly focused on, you know, tech or engineer focused solutions that tend to be, again, very tech forward founders. But then there are also a lot of AI natives that are focused on role or function specific expertise like legal finance and accounting. So those types of AI natives like the Harveys. So those types of AI natives that are focused on role or function specific expertise like legal finance and accounting. That makes sense.
Speaker 2And, you know, when it comes to those of us who are not in AI native companies, and let's face it, certainly the majority of us, I suspect, still are in that boat in one way or another. What are the top two or three key lessons that you think we can extract from those? Who have been born into the post generative AI world?
Speaker 5Yeah, I think one of the biggest first lessons, and I know this is applicable to all leaders who are trying to navigate this AI era is AI doesn't actually need to be used for everything that we do. And in fact, there are things that we believe should be unautomatable about the work that we do and things that should never be delegated to AI because they're. Things that humans will continue to do better than the technology, at least for now. And one of the things that actually surprised me was I met with the lead marketer at an AI native and she said, you know what, our CEO, who has a PhD in machine learning, actually forbids the marketing team from using AI in our work because he doesn't believe that it's good enough at creative tasks. And our team brainstormed.
Speaker 3I guess the leaders of AI native companies are just automating everything and they're not really sitting back and thinking about what to automate and what not to automate.
Speaker 4Well, maybe I'll flip a counter example to Laura's great one. One of the more fascinating AI natives I think we've met is a fashion company. And it's basically, there was a lesson I had to think about is like they sensed very quickly what needed to be reimagined in fashion. And in particular, large. Organizations that are basically merchandising companies, right? I mean, they're basically deciding at any given rate how big the logo is for the season, what's the color of the time, what's the cut, etc. And they saw very quickly, you know, like a lot of these organizations are bloated. They have 20 designers, 30 designers doing something that should really, really grow. Like how, what's the color of the season, really? Let's just have AI go back. Here's what we did the past 30 seasons, you know, seasons. We just need the core creative director. And, you know, I spoke to the designer who had come from a pretty renowned firm we would all know and asked her, like, okay, you're the designer of this organization. Like, how big are you? She said, oh, we're about six people. How big were you? We're about 50 in my previous job. And they're doing end-to-end manufacturing in a super smart way. Like thinking about sizing. Sizing gets really screwed up. Okay, well, like, why can't AI do that? Like, that'll, like, get more predictable size. So they sensed all. And I think what they did is, I mean, towards, they did focus on, like, they still have creative directors. they still have taste they're still deciding what's good but they are also realizing gosh like like some of these old systems that held us back like we need to liberate ourselves of that to build new so i to me that's a great lesson like like sense what could be reimagined like what are what's bureaucratic like why do we do these things this way and do it fast because some of these these newer firms they're much faster than you think yeah
Speaker 3and actually on the speed thing i'm really intrigued because i think speed is something that traditional companies really struggle with or even fear or fear yeah absolutely you know what are the different sort of systems and and ways of thinking that ai native companies have that allow them to speed up that non-ai native companies could actually utilize there's
Speaker 4no precedent on how work has been done in the past if you're a native so you're just building and making it and i think how decisions get made to me is held by kind of instinct and trust in the wisdom of the tool that continues to get better and better which i find really fascinating i think legacy organizations are trying to figure out where to weave in the tool to existing workflow and that's why that's what's holding them back versus rewiring it all together or untangling the wires and just stripping it together which aligns to by the way outcomes which is also really hard because many organizations are process oriented and they're not thinking really thoughtfully about okay like you know i want 100 like successful onboarding rate from my people team right like let's start there like and then work back about how those workflows will get to us versus many orgs are like okay like this process is broken this process is broken let's see how ai can help us that way and to me that's it's just a fundamental reorienting of how you think about business that's
Speaker 2really interesting i think one of the challenges in that regard is that to do that slows you down you have to really stop and think and be very thoughtful and then you've got this fear of your competitor over your shoulder being more pragmatic and in at least in the short term potentially winning i think there's there's a real tension with that let's redesign sort of from first principles versus let's just get incremental efficiency and productivity and lower
Speaker 4cost one of the crazier examples we've seen is there's a financial institution that's creating an ai native version of itself very transparently i think what's what's interesting about it is i mean first of all just making it transparent which is great so like you're reducing a little bit of fear and you're making it more of a collaborative effort but you need to understand what's broken right in the overall systems and what can be quickly more reimagined is to kind of build this thing from the ground up and that's one method we've seen which i think is really important and i think it's i think it's quite vampire and very
Speaker 2interesting yeah and laura do you have any lessons of how much time ai native companies because ai's capabilities are evolving so fast is there a certain amount of time they're all spending experimenting like what can legacy and traditional companies learn from how to work with ai when the ground keeps moving from underneath you
Speaker 5yeah i mean i think what we've noticed is that if you're in a technical role at one of these you're just constantly plugged into all of the different tools that are at your disposal and there's a very strong sort of engineer culture of let's find the next update let's figure out what's working better for people at you know peer organizations and there's i think a lot more community that's driving sort of that sense of daily reinvention of workflows i think what we've definitely found with even some of the most cutting-edge ai first companies and this has been echoed by several different leaders is that the only thing that's holding them back from adopting these tools is not fear it's actually just time and because many of these ai first organizations they're also in hyper growth they're moving so quickly that they don't believe they actually have the time to take the steps needed to upskill themselves reskill themselves redesign their workflows and so that's a big detractor and i think with these ai natives they also don't necessarily have the time because they're just moving at the speed of light but i think they're able to have the advantage because they're just building that new
Speaker 3yeah yeah they're just on the tools all the time literally
Speaker 5building exactly and that's one ai native ceo we spoke with said and this is sort of another paradigm shift he likes to hire for polymaths and he encourages the marketers to work in the same code base as the engineers to have awesome marketing ideas and that there's really a lot more role overlap than there might be at other organizations but that's something he actually encourages the other thing maybe this is relevant to share is that i think the daily rhythms of how people are working are totally different so they have a stand-up in the morning as a company again they're quite small and at the end of the day everyone kind of sets their workflows going and lets them run overnight until the next morning and someone you know when he was asked essentially like well what happens if someone is working late nights and he was like well if they want to be doing that they can but you know the agents are working
Speaker 2overnight classic just love to hear from each of you start with maybe mark you know if you look three or five years ahead just very briefly what concerns you most about where we're going and what's going on and what's going on and what's going with ai i i
Speaker 4think what i'm most concerned about is i'll give you this line i think modern capitalism has taught people to think like machines they are getting like more productive more efficient like that's just kind of how executives have been trained right the opportunity i think with ai is to help us think more like humans again i worry that people have been oriented so much to think one way that when ai automates their job automates their way of working etc they won't know what to do and the the dopamine deficit that war alluded to when you learn don't learn anything at work etc becomes a mass endemic that's what i see i really
Speaker 2like how you've expressed that it's sort of i haven't heard that before but you're right you know from the industrial revolution on we've been sort of trained to do and think you know much more like machines on the flip side what excites you most about ai we
Speaker 4could get a creative renaissance i think what i think people building like like everyone becoming an engineer and a maker is a really interesting idea and also maybe like what excites me is maybe we're all gonna spend a little more time with our families our kids reading like west of the pace wouldn't that
Speaker 2be nice yes laura how about you what concerns you most first in terms of ai
Speaker 5yeah i think it's not a coincidence that the biggest and most urgent question that we've heard from leaders industry agnostic is what happens to the next generation of talent so i really worry about what it must be like to be graduating from higher education in today's context and wondering what my first job might look like and i really worry that we're leaving a generation behind so you know i would love to believe that they're gonna find new creative endeavors and that new jobs will be created out of this need but i do worry about that yeah
Speaker 2yeah i think it it's it's not solved is it and it is sort of uh an ongoing concern what about on the flip side what excites you most about what lies ahead yeah i
Speaker 5mean the techno optimist side of me would love to believe that there are going to be just exponential developments in you know health care and in curing disease and in basically reaping all the benefits of this technology for societal good and that we could be entering into an era where we're all a lot healthier and
Speaker 2happier yes let's hope it goes that way we get those agent values truly aligned and those goals not too skewed it's been such a fascinating conversation laura and mark thank you so much if people want to learn more about you your work or libra collective where should they go to our
Speaker 4website we're a great place to start libra-collective.co or you can find us on linkedin
Speaker 2fantastic well we shall put that in our show notes for the episode as well so thank you guys so much it's been a really interesting
Speaker 3conversation yeah it really has and we could we could talk for hours this was just you know a small conversation but so fascinating so thanks guys
Speaker 4thanks for having us
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