Mervyn Dinnen 0:09 The HR Happy Hour Network is proudly sponsored by Workhuman. Nearly 9 in 10 HR leaders say they don't have a strong leadership bench. Workhuman's future leaders gives organizations a smarter way to build one. Future Leaders is the first talent intelligence solution to identify high potential VP plus talent already within your workforce up to four years before promotion. Using proprietary AI and real time recognition data, it uncovers the leadership signals hidden in everyday work, long before traditional succession planning can. It's a smarter, data-driven approach to building tomorrow's leaders. Learn more at workhuman.com. That's workhuman.com. Welcome to the HR Means Business podcast, which is part of the HR Happy Hour Network. I'm your host Mervyn Dinnen, and today I'm joined by someone who's thinking I find genuinely fascinating. He's been on the podcast a couple of times already. His name is Nick Holmes. He's currently a year into a PhD researching organizational culture, and he brings a rare combination of academic rigor and real-world practicality to some of the most important questions that face organizations right now. We're going to be talking about culture, AI, and the relationship between the two, which is not the conversation that most people actually think it is. Most of the debate asks, you know, what is AI doing to our organizational culture? Whereas Nick's research suggests that actually it's the wrong question. The question is, what kind of culture do we need for AI to work? That reframe changes almost everything that we think about AI. And so, Nick, welcome to the HR Means Business Podcast. Would you like to introduce yourself? Nick Holmes 2:02 Thank you so much, Mervyn. Lovely to be back. Thank you for having me. Must have had some pretty good conversations previously to come back through the door. So it's lovely to be here. Yeah, like you said, I'm a PhD researcher in organizational behavior. My thesis is all about organizational culture. The working title is "Defining the Undefinable" towards a new definition of this big hairy word of culture and a new measurement to help us make more sense of it. I'm a VP of Learning and Culture. I'm also the founder of a firm called Culture Nova, which is a cultural research and diagnostic firm, and I work with organizations around the world to help change the way they think and feel about work. So yeah, it's lovely to be here, and I'm really excited to get stuck into this meaty, juicy AI culture pie. Mervyn Dinnen 2:48 Okay, okay. We the I think when we did our our kind of you know catch up before we we started the recording, you you said you've got like kind of 150 years of cultural context in your head. There's 164 different definitions and 70 different measurement tools. Yeah, that nobody really agrees on a consensus. So I suppose first question is, what does that tell us about how well organizations actually understand the things that they keep saying they need to build? Nick Holmes 3:20 So I mean, this is this is the crux of the problem. I I think there is fundamentally a big difference between familiarity and understanding. So I think a lot of organizations are familiar with organizational culture, but actually, very very very few understand it truly. The analogy I use this of a zip? Like you're familiar with a zip, but if I ask you to tell me how a zip works, how it goes from the teeth into the lock, like all of our confidence like falls through the floor dramatically at that point. Culture is very very similar. I think I've I've had I've been speaking to leaders and also through the research, and the consensus is, I think it's a set of how values or behaviors. It's a vibe or a feeling of how work really gets done around here. The most most common definitions like this treat culture quite atmospherically, like the weather, ever changeable, moving, can't really put our finger on it, and yet this word is at the forefront of of every single industry across every country in the world, from boardrooms to football stadiums, everywhere we talk about culture. So, what's frustrating me and the point of the research is: can we actually step back, look at what's been done, build on the great work of people like Hofstede and Shine and and all these people, and actually get to a fundamental core agreement on how do we treat culture and can we make it relevant for 2026? Not relevant for where most of the literature sits, to be honest with you, which is in the 80s and the 90s. So, yeah, it's exciting. I think I want to get all. From familiar from familiarity into a really clear understanding, and when you understand something, how it really works, we can move it. And the AI conversation is is fascinating in this because the the ability and the way that we're using AI currently to sort of quote unquote educate ourselves actually doesn't increase our understanding at all. It just gets us to familiar quicker, so there's a lot in this. So yeah, excited to unpick a bit of it. Mervyn Dinnen 5:26 Yeah, I mean, I think yeah, I've already said in the introduction, your your you know the the the what's the impact of AI on culture is the wrong question, but it should be you know is your culture ready for AI? And I think that will challenge a lot of the way organizations think about this. So, can you, I suppose, unpack that a bit and kind of explain what you mean by that? Nick Holmes 5:49 Yeah, absolutely. There's some really interesting studies coming out quite a lot at the moment. Deloitte have just done a good one called the cultural debt analysis. Essentially, what's happening there is 65% of organizations believe that their culture needs a significant change because of what's coming with AI, and 35% say culture actively inhibits their AI goals. Currently, there's even a study that shows that 25% of employees are trying to actively sabotage the efforts of AI because they're terrified of what it might mean for their role moving forward. So, so what I mean about that is a lot of people are saying, well, AI's impact on on how people work and the culture is going to be profound. But actually, when we think about AI, it's a tool. It's a tool. It's it's another powerful, very powerful tool that can and will and is rapidly changing our approach to the work that we do and how we do our work, both things-the technical craft and and the behaviors towards it. But ultimately, when you put a new tool into an environment, that environment is going to spit it back out, use it messily, or use it and actually drive value. So that going back to the original statement we said, the question isn't the impact of AI on our culture. The question is how our environments designed to make use of this tool in the most efficient and effective way, and so what what you have in organizations is we have people adopting tools with very little cohesive strategy. So people in roles will be like, "I've done this really cool thing, and then depending on the type of organization that you have, the design, the culture set up in the organization, that person will say, "No, you can't do that. What are you doing? Because that runs risks, or there's no join up, or it just happens in a silo, and leaders aren't using the same thing, so there's disconnect and mistrust. Or what we have and what we see quite a lot is a lot of work slot taking place, where AI is taking over some of the traditional culture building aspects of work, whether it's communications or connection with other people, so it's all about how we can redefine and redesign the environment to be more successful, and then AI can either come into that environment and enhance the ability of the workforce, you know, come into that environment and fail dramatically depending on what's there, but ultimately we've got to try and rethink how our work is being designed before we can start to talk about the value adoption of AI. Mervyn Dinnen 8:11 You say about adoption because there's something in your research that that I've been thinking about before we had this conversation, and that's that at the moment it looks like globally, employee engagement has been declining over the same period that AI adoption has been accelerating. Now, I know that that in the research you're doing so far, you you're not claiming direct causation there, but you're not dismissing it either. So, what do you make of it? Nick Holmes 8:40 Galup have been, I mean, there's two things for me on this. Nick Holmes 8:44 Engagement. Engagement in itself is is. I approach it with caution, and the reason why I do that is Galup have been running the state of the workplace for 26 nearly years, and the first time they did it was 23%, and 26 years later we're stuck at 23%. So, my point is, it's a useful point to know how people feel, but it might not be helping you drive true growth and performance through organizations. I think there needs to be a different look. Having said that, the second part of this is, whilst there is no direct correlation, I think the coincidence is high, and the reason why I say this is, over the last five years, we've seen that AI adoption flow through the organizations. It is well known that organizations are looking to make efficiencies by using technology, which has a which does has an does have an impact on people's welfare at work. And what I mean by that is their anxiety around their role security will always play through into how people feel. So when they're completing a sentiment survey about how do you feel about your workplace, if this big cloud is looming over you that I'm uncertain what my future is, I'm always going to answer that sentiment survey in a negative manner. So I do think there is a correlation. Glassdoor released like their mid-year review. They talk about like the I don't know the exact terminology, but there's like a fluttering of layovers, and so what a layoff. Sorry. So what's happening is previously workforces used to do like layoffs in chunks. So you go to you know there would be a redundancy exercise, a big round of layoffs. The organization moves on and carries on. What's happening now is it's constant cut. So because the technology and because AI is moving at such a pace, the cutting is constant and it's little. So it's like a few here, a few here, a few here, and then yes, in large enterprise orgs like Amazon, you hear about 3000 people losing their roles, but those cuts continue. The problem with that is the psychological deficit post redundancy and layoff, because for the impacted teams, maybe you're an individual who survived a layoff round, or you've got colleagues that have left. It takes about six months for you to psychologically get over the impact of that. So if you're continuously laying people off through the view of actually, I think this might be, you know, the organization wants to get faster, so I'm going to take people out continuously. You're always in a psychological deficit from a trust perspective, so I'm not surprised to see sentiment and feeling and engagement drop at the same time as AI adoption climbs. I, I think you know there hasn't been any direct empirical, as far as I'm aware. I could be wrong, but I do think there's a correlation. I do think there will be a bit of a dotted line to the two. Mervyn Dinnen 11:26 Yeah, and a lot of people talk about AI readiness. You know, is the organization ready for AI? Is their culture ready for AI? What to you? What does it look like in practice? Because I would guess that most organizations probably think they're closer to it than they actually are. Nick Holmes 11:46 I so when I look at when I look at culture and I look at the definition I'm moving towards in my research, I treat it as an operating system, as an OS, and within the operating system there are distinct domains that determine how healthy or not your operating system is running. We call those maps, wires, patterns, and sparks very quickly. Maps is the integrity between the purpose of the business and how it shapes its priorities for its people. Unwritten rules, values, and behaviors in action. Wires is information flow, incentives, and operational working between teams. Then patterns is psychological safety, candor, and repeated memory. And then the sparks element, all about leadership modeling, managerial practice, and the ability to learn, learning agility. So, how good are you at failing and learning from failure to then rewire your system consistently? For me, when it comes to adoption of AI, there are two things that essentially organizations need to know and get good at. One is communicating change that's worth backing, right? So when we talk about change in AI, is it change for a lot of organizations? Is it worth backing? And so to answer that question as an employee, if I'm sat in a warehouse or if I am out in the field selling something or I am in the finance team, I need to know how this tool is going to enrich my life and make my work better for me and my client or my customer. The second thing is, you need people who want to do things better. So we always need that's what's going to drive an organization forward from adoption. To say, here's something I'm doing today. Do I have the energy, the agency myself to want to say, I want to do this better? And now there might be a tool out there like AI, a claw, ChatGPT, a workflow, or Copilot-that's going to help me do this tool better, do this thing better. If you don't have those two things, adoption will never reach its its endpoint. A fascinating thing around transformation, which is all this is though, is that 70% of transformations fail, and 80% of transformations don't achieve their targeted goals they set out to in the first place. And yet, the tool isn't the issue. It's how ready the organization is for that transformation. And worryingly, that number has not moved since the 70s. So we've got worse. We haven't got better at adoption for transformation because ultimately our behavior and we haven't we've been measuring the wrong things culturally to get our cultures ready for transformation to be successful, so it's a it's a mindset adoption, but then it's also an investment piece in your people. Because really cool thing, I think McKinsey came out with: for every dollar you invest in AI, you should invest five back into your people in terms of their readiness, their skilling, the environment they're working in. So it's not easy fix, but if you want to realize the true benefits of AI and get it scaled, it's worth slowing down to speed up to figure out what your system's doing, understand where the investment needs to take place, and getting people ready for change and then on the bus, motivated to do better. Mervyn Dinnen 14:35 Does that surprise you? The ratio. kind of spending. Nick Holmes 14:38 Yeah, it's higher. Yeah, yeah, yeah, yeah, yeah. I was surprised. I think it's a a combination of investing in people is not is expensive today. It's not what it used to be even 10 years ago where and and the the price of and the the problem is people are investing it in such unjoined up ways. It might be in a learning course or a catalog or a library. It might be in just more people in that team. It's it's not really for me being thought through in a really holistic way where there's going to get genuine value out of every dollar or pound that you spend. So yeah, I think I think and I think people teams are struggling with that. They're struggling with where do we invest the dollar in order to maximize our cultural impact so AI can flourish. It's difficult. It's not an easy answer, but yeah, I see why the investment's needed. Mervyn Dinnen 15:33 Yeah, and you you gave the the zip analogy earlier. Yeah, everyone knows how to use one, but no one can explain how it works. And you said that AI is amplifying this gap massively in organizations. What I think within leadership teams, what does it look like? I mean, it's where do you see or what role are leadership teams playing at the moment? Nick Holmes 16:01 Yeah. So you've got leaders who are non-native to AI, not adopting, and teams who are adopting will see a perceived efficiency, perceived capability gap. Because if you've got teams who are native using these tools and their leaders aren't mentioning them at all, you'll start to see an integrity drop between that relationship to saying, "Well, I'm using it, my bosses, and what's going on. We know manager leaders play a critical role. On the flip side, there is actually some positive stuff coming out of leaders using AI in what's called augmented leadership as a mechanism to improve the way that they manage their teams. So, what that looks like is AI is being used in the team working setting setting for constant feedback being used and practiced and role model to make them better as leaders, and how can I improve things? That modeling has huge payoff from a trust perspective and played down. Coms is sharpened, but not taken over by by AI because if it's only slop that's going out to teams and there's no thought, critical thinking in the process, teams see through that right away, but one of the important things to know, and it goes back to how the organization learns fundamentally, and the one of the scary impacts of AI currently is if AI is allowed to do all of the work for us, what's happening is familiarity gets better, but understanding will continue to to just disintegrate. So what I mean by that is, you know, someone take an example. You and me are at a bar talking about football, and I'm like, "Oh, do you know anything about Rangers? And you go, "Oh, just ChatGPT Rangers. And then you say, "Then you go, yeah, Rangers. You you might have think that you now know everything about Rangers FC, but the reality is tomorrow if I ask you about ranges, you will never have a clue. So we've got this false presence, this false bravado of understanding, when really it's just enhanced familiarity, and that is so dangerous because we're making decisions off stuff that we don't really understand. So what leaders need to do in role model is making sure that AI is enhancing their already hopefully strong skill set and their abilities, not replacing their ability to get to know and understand what their people need and what the business needs and what clients need. Because otherwise, you just have hollow work, and you're missing this really important thing. And your brains, as we use this more, will become weaker, not stronger. And it's it's a real danger with the onset and the adoption of AI. Mervyn Dinnen 18:23 Yeah, I mean, I suppose the whole thing about leaders kind of agreeing to AI strategies that they might not actually understand. Do you think this is something that is is understood or is underexplored within organizations? Nick Holmes 18:41 I don't. I I don't see enough evidence to say that we truly understand what we what we need from AI, anyway, and organizations to to believe that everyone's got it locked in. I, from a leadership perspective, I don't see enough. There's some good terminology around around how leaders can get better learners, and and that idea that actually learning is this most most important most critical skill that leaders can do. Doing something, I think what we need to understand is like just by using a tool like Claude or ChatGPT to do a piece of work doesn't necessarily give us the understanding of how it's going to shape our work. We do need to spend time in these tools. We need to do self-discovery. We need to understand the rights, the wrongs, the playing with it. We need to have what's very important is leaders create an environment for people to fail safely using their tools. So whatever it is, as long as the organization has an agreement, what tools can and can't be used, because that's part of the problem that we see is AI is in every system and platform, but what can we can't we use from our own lives, which we use probably on a daily basis, and to work we have restrictions around that. So I think from a leadership perspective, it's about understanding A: what the environment that work the organization is allowing tools to take place. Are you allowed to use Claude AI? Are you allowed to use ChatGPT? But and beyond that, setting the environment within the teams that it's safe to fail with these tools, because otherwise they're not going to understand why things go wrong to fix them for next time. It's just going to be the false familiarity that we go back to. So needs more is my answer to that one. Mervyn Dinnen 20:16 Now, when we were having a chat before we started recording about what we're going to be talking about. One of the things that you shared rather surprised me, so I'm going to ask it here. You said something like 29% of employees admit to actively undermining their employers' AI strategy, and amongst Gen Z, that figure is is rising up to something like 44% I mean, that's not resist. That's not resistance. That's sabotage. What? What? What? What's what's driving it? And I suppose what's the the the broader story about how organizations are handling the human side of AI adoption? Nick Holmes 20:56 I know. I was. I. I actually really enjoyed this. Not from I want to see workplaces be sabotaged. My work is the opposite of that. But Workplace Intelligence Report 2026. Yeah, it's fascinating. We think nearly a third of employees are trying to you know sabotage it. It goes back to the point earlier that says, well, it's it makes sense, right? Because if your overall engagement is dropping and hindering at the same rate as AI adoption is, and you're seeing the psychological deficit come along with trust in the workplace because people are leaving their roles from a hierarchy of needs. Like you want to protect what's yours and yours. So if you see a threat like previously in 300,000 years ago, this was a lion stepping on a stick, and we were like, "What? Now it's potentially AI taking away our livelihood, which isn't the case, by the way. As well, like there is a lot of contradictory data out there to say AI isn't actually reducing all the works; it's also adding work in. So there's this huge, messy gray cloud of understanding. But the Gen Z phenomena in this, seeing them almost twice as more likely than any other sort of generation to sabotage, I think it speaks to the fact that they are the generation that have grown up with this very natively, and they themselves, you know, actually want less of it. I think there was an amazing survey done. I think I don't know if this categorized in Gen Z, but of 17 and 18 year olds last year who gave you the choice: if you were to grow up without AI, if social media and AI didn't exist, would you prefer that than you were today? And I think 70% said yes. So these are tools that also I think what's what we need to remember is these tools, social media, AI, have not been built by Gen Z. They're built by millennials who are the who are the most users of AI in the workplace, which isn't a surprise. So I think it just comes from this place that they use it so much, they see it all, and they also want to know like that they have security and safety as they look up and sideways in their careers. And if they think that actually their opportunities are going to be swamped or taken away by this, they're going to think that. So that I think the human impact in AI goes back again to how your organizational environment designer setup. If culturally you have a good history and a record of treating people well and fairly, and workload management anxiety in the workplace is low, and you layer AI into that, you will see. Hopefully, when I go back to what moves an organizational forward, people who are ready for the change and excited by the opportunities and willing to ask, how can this make things better? But if you're an organization who traditionally, and maybe over a run of period of time, has laid off cuts without this in in in tow, doing this because you feel you have to do this, otherwise you're going to fall behind, have not set a clear change agenda for how this is going to set, have a really poor purpose related to priorities, values are performative at best, and you're asking sentiment surveys once a year. Then you'll probably see a lot of hesitation about tools coming in. What they're going to do? What does that mean for my role in the first place? And the worst thing I find majority of the time is managers are so ill-equipped to deal with it, and managers are a linchpin in all of this. Right. So if you're directing workflow upwards and you're reporting status, sorry, directing workflow downwards and reporting status upwards, you're a linchpin in your organization. If you're not equipped, don't have the answers, have no experience using these tools, but your people are or supposed to be, you're going to get two sets of pressures. It's just going to compound in this already fractured and broken role, so the human impact on this again boils down to how well already your organizational culture is to adopt a new tool in the first place. I think if you combine that with we've never been more access, you know, we've never had more access to news and information as we had in our lives. We've never been more dispersed and connected at the same time. That your external anxieties that you see and read every time you read the news are just are just inflated at work. So we have to be quite careful with how we're approaching and mandating tool use and how we're treating people internally because they're dealing with so much right now. Mervyn Dinnen 25:02 Yes, and the cognitive load is is is increasing. I think there's an assumption that the the a lot of people think AI that reduces workload, but but what we're really seeing is is the the yeah some parts of workload obviously are decreasing, but this cognitive load is actually increasing, and I mean, are you seeing from the research organizations doing anything differently about this? Nick Holmes 25:30 So the promise of so again, this is like an integrity trust break because the promise of AI is that it was going to free you up to be more creative. Like I don't know if you remember, like two, three years ago, right? Everything was like we can AI will take over, so you can do more human stuff. I don't know if you see this, like you know, look back on all the slide dates and presentation from that time, right? And we were like, well, what is a human thing? Like, what is? I mean, yeah, Deloitte again, 2025 came back with a 77% of employees say AI has actually increased their workload. Frequent AI users report 45% high levels of burnout, and so the answer to this is is challenging because yes, there are moments of promise where it's like AI will reduce these things, but the reality is, if again the work that we're doing the environment we're set up isn't to say we're going to stop doing. It's actually what can we do more of? Then of course you're going to end up just doing more. You're just doing it quicker and faster, but more stuff will always come in. I think what's fascinating about humans and society in general is whenever we're told to innovate or create something or make something better, we always add to that system. We always add to that project or add to that initiative. Whereas the best organizations, frontier organizations, who are doing and working with AI really well, there's a really interesting one about Warner Brothers and their merger with Discovery. There's a quite cool MIT slogan research that goes with this: is they say, "What can we stop doing fundamentally that gets replaced with AI, like so. From so a really miscon a big misconception of this is like, oh, AI can do my decks for me, right? So it's like, yeah, AI makes a deck, but if you're just trusting that there will be mistakes on it, so you have to check the deck anyway. So that's fine. But then, just because you've done that deck with AI, you continue to make more decks with AI. You're not stopping the reporting process in the first place, and automating that somewhere with AI, you're using it to make a thing faster, and then just doing more things quicker. Whereas that thing might have taken you longer. It's just you're not reducing your workload, so it's important to note that. That's important. On the flip side, organizations that you use AI well, very well for sort of going back to the burnout point, can see gains in mental health and stress days related to mental health decrease because you can use smart AI as a in-house, in-moment therapist, which can share views, talk back to you, and say how are you working, what's going on. So I think like all of this, there's no good, bad, like there's good, there's bad, there's ugly with all of it. So we've just got to make sure that we're cutting through noise where it needs to cut through, speaking to data and facts, and using your own workplace and using your own people as, as the research students, basically. Mervyn Dinnen 28:14 I know one of the things that you've been looking at as well is AI's specific impact on psychological safety, and I think it's kind of like it can either enhance it or it can can cripple it quickly. What what what do you find, or what are you finding determines which direction it goes in? Nick Holmes 28:35 Yeah. So if we think about defining that quickly, psychological safety-that feeling of being able to speak freely, you know the risk of failure is is normalized for you. You can share your point of view. You're included, and you can feel like you can bring your whole self to every argument, every conversation, every debate. Right, that is the thing that drives innovation. Organization is being able to have that moment and those mindsets. AI's role in this is quite interesting because again, if you have a group or a team where there's lacking psychological safety in the first place, I think AI will only enhance those those issues. The reason why I say that is, if a leader is using AI and they always only ever choose two or three people for a project, that's just going to enhance the bias that exists in that leader's head. A leader's head. From a comms perspective, AI just drives comms throughout, you know, and it's just slop and it's generic. There's no trust building. It becomes very difficult to come up, raise up, and challenge. On the flip side of that, if you're using AI as a leader or as a manager to give you feedback on how you managed a team meeting using a transcript or a video and asking copilot, say, "Was I inclusive in that call? and getting feedback and telling your team you're doing that, you're going to dial up psychological safety. If your organization has actively cited AI as a reason for roles being removed. You're going to kill psychological safety. So there's again, it goes back to the principles and the simplicity of: Are you being fair, inclusive? Do people have the boundaries, the safety to be curious and raise their hand and share their voice? Again, like I say, if you have a cultural set which is encouraging that already, AI will amplify the good and amplify the bad in it. So you need to be wise on that, and be very, very conscious of how you're already entering the the conversation. Mervyn Dinnen 30:30 Okay. Now, as we're we're coming to the end of the conversation, and one of the things that I know we've talked about in the past, it's very easy, you know, the conference stage podcast like this in boardrooms to talk about AI as very much a what I would call a white collar conversation, but you know we've we've got certainly in the UK and I think Europe something like 60% of the workforce is location specific. They're not sitting around in offices all day long planning. Yeah, I can do this quicker with Claude. It's it. Yeah. What are we missing by talking about AI as if it applies to everyone? Because this is you know. I know there's an example which you you you may give about the NHS. You're still being paper based at the front front line. It's how how do you see this not so much playing out, but but how do you see AI? I suppose coming into the I don't I don't like to say blue collar, but I mean those kind of front line industries? Nick Holmes 31:31 Front line roles, humans humans connections, and we're such a long way away from AI or technology or robotics replacing humans in this way, and those service roles, which are so critical to the functioning of society, I think it's really important that we're very clear, and organizations themselves are very clear about what is protected, how AI, you know, look, and so say you're someone who's a cashier at Morrison's, for example, there may AI might come into the way that you scan through food, and yeah, technology might you know remove some aspects of your role, but it's being really clear and doubling down that why one of the I think backing tracking slightly on this, one of the most powerful things about those jobs is it gives people human connection, ah, the the ability to converse and talk to another human, right? Whether it is transactional, like I'm being checked in at a hospital, or whether I'm talking to a cab driver who's driving me from A to B, and we're talking about my day, or I'm getting my car washed and and we're talking about why, or there's an interaction there. We run the risk of a overcomplicating work for some, which doesn't need to be overcomplicated, and we also run the risk of like saying, "Oh, we because we think we can do things better. Those who have never done that job in the first place, removing something really powerful which we need in society, which is human connection, in order to function like the the world's longest happiness study found two things that drive sustained happiness over time: health and human relationships. AI cannot replace that. In many pockets, that it's trying to replace that, and after initial bump of of hit of connection serotonin, depression sets in very quickly because we're not getting this moment, not looking at other people, driving the human chemicals that exist when we talk to people face to face. So, for those more service-driven roles, there will inevitably be some form of scene and visualization. These people are inevitably using and interacting with it on a daily basis, but take the pressure off them to say, just focus on what it is that you're doing in your role. Add as much value as you possibly can into that, and we'll hopefully use AI to enhance your ability to do more of that, not less. So, yeah, if AI in the NHS can help a nurse complete paperwork three times quicker, so she can get or he can get to see someone new, let's do that, right? Mervyn Dinnen 34:03 Okay. Finally, because it's been fascinating, it's been a lot to think about here. We, we, we, we've, I suppose, covered quite a bit of you know what's going wrong or where there are pitfalls. So I suppose finally, you know, to look on the more optimistic side. When you see an organization that's genuinely getting it all right, you know the culture, the culture stroke AI relationship right, not just chasing gains, doing things quicker, productivity gains, and actually you know, but actually you know giving value to customers and their people. What what what do you see them doing differently. Nick Holmes 34:43 Instead of communicating that AI is going to help us work better, and this is the big difference maker for organizations, instead of coming and saying, "Oh, we're going to use AI and it's going to make us work more efficiently, no one gets out of bed for efficiency. No one goes, "I can't wait for more efficiency." There, there's the the the organizations that are frontiering this, that are driving real value for customers, are saying, "How can we change the world by using this and enhancing our craft and not replacing it? So I go back to this Warner Brothers Discovery integration that took place. The message to their creative team was: How do we give you the tools to enhance your superpowers? So when we talk about AI replacing creatives, you know who the number one role that you use is AI for creativity is creatives. So it's it's about the organizations that set that tone. We call these the maps domain in the OS framework who set purpose, who set priorities, values, behaviors are so lived they drive every decision. So the the the you know the contrast, the integrity smash in this. Say you've got a a corporate value on your wall that says integrity, and then you tell people we're not gonna be like everyone else. We're gonna use AI, and then all of a sudden, you don't you stop you stop replacing roles, and you think that AI is going to get it, even though you haven't implemented it correctly. So all that happens is other people just do more work. Of course, you're going to see attrition fall through the rule, and you're going to see confidence flat, and you're never going to realize the value because people don't buy your change, and they don't they stop asking how they can do things better. The organizations that are delivering genuine value through AI for their clients, their customers, and their product are ones who say we're going to use these tools to enhance your ability, and then you're going to play a role in us making the world a different place through what we do. Yes, they might use them to work more efficiently, but they don't lead with efficiency. They lead with purpose, and there's a distinct lack at the minute of very good, powerful connections from organizations who are genuinely leading AI purposefully versus AI for like I feel like I need to do this because for so many organizations, if AI didn't exist, they would still be doing the same thing. They get disrupted versus doing the disrupting. So it's organizations who are using it are to enhance their purpose, not to just drive an extra couple of hours on the clock. Mervyn Dinnen 37:11 Okay, Nick, it's been an absolute pleasure to to have you on the podcast again. There's been a lot to think about in everything that you said there, I mean, what I for for for you, you're you're you're doing the research and stuff. I mean, will this be published at some stage? Do you think? Or? Nick Holmes 37:32 Yeah, I so there's a couple of things. I'm launching through Culture Nova at the end of this year something called Nova Labs, which is research that everyone can get involved in that asks three questions a month that you'll be able to see back straight away as well. No hidden agenda there, just wanting to get research into the world that makes the world a better place. So just interact with that. My my thesis will be live in 2028 at some point, but I will every week I share what I'm learning, what I'm hearing, tools and my expertise, things to get involved in on my LinkedIn. So yeah, and it should be quite exciting for everyone to get involved in as we move forward. Mervyn Dinnen 38:09 It should be great. And listen, lots of luck with it. And I look forward to getting you back on when the PhD is out there. Nick Holmes 38:16 Absolutely, PhD books, all sorts. Cheers, man. Okay, Mervyn Dinnen 38:20 All the best. Nick Holmes 38:22 Thanks. Transcribed by https://otter.ai