What the #1 Global Futurist Says About AI and the Future of Work | Diana Wu David

We are live, ladies and gentlemen, you once again welcome to the Kingdoms Podcast and Diary of a CFO. And today I've got with me a very special guest, fighting out of New York, United States of America. Make welcome, Diana Wu David. Thank you. Thank you for that stadium opening. I feel like I'm not going to let you go. whoa definitely uh you have to give the world's number one ragged futurist of flowers so uh today we are joined by a very special guest and of course today's episode is not just a conversation it is a reality check because the future is not coming it is already here and most people are not ready. I am joined by Diana Wu David, ranked the number one global futurist for 2026, according to Global Gurus. She is the director of futures at ServiceNow, board advisor and author of Future Proof, reinventing work in an age of acceleration. She has spent decades advising executives, boards, and global organizations on one defining challenge. How do we design a future where humans and AI don't compete, but collaborate to create something far more powerful? Because here's the truth. The weaners in the next decade will not be the most intelligent. They will be the most adaptable. Diana, you're once again, welcome to the podcast. Wow. Thanks. I'm excited for the conversation. I am excited as well. So you all currently ranked in the number one futures globally. So take us back. What moment shifted you from operating in BeezDust to designing the future of BeezDust? My background is really as a boring P&L executive trying to think about what's next for my team, what's next for my company. And I wouldn't say it's a single moment. I've always been interested in sort of what's next and fascinated with how humans deal with it. But the real accumulation of friction is why I ended up here. So I think that when I think about financial times and, you know, working across Asia and working with some of the most brilliant executives who are making decisions. But based on the world that was five years ago, so I did, you know, restructuring digital transformation during that time, and people were still in this mindset of we have a physical product that is where information lives that needs to get to, you know, a house before a certain time of day. And I worked with a lot of people years, decades ago, where it was just really difficult. And it wasn't because they were lazy thinkers, but because the systems all around them were designed to optimize for the present and not to navigate what was coming down the pike. And so I started asking, like, what if we could build the capacity to see around corners? And, you know, what if the organization could start thinking about that? And that became a bit of an obsession for me. And then as I worked with other clients throughout my career, I found that it increased the quality of conversations that we could have. It allowed people sometimes to go beyond the turf wars in many organizations to talk about what they really, their broader ambitions. It widened the lens. So, yeah, it's been really become a career for me and a passion. Wow, interesting. So you've actually worked across various organizations. Of course, one of them, dear to my heart, PwC, that's a common point. So, and of course, you've worked, you know, across functional teams, right? And of course, you know, across global markets. What were the early signals that you saw that other people were ignoring? Well, I do have to share with you that we were working, and I, you know, not even know if I'm allowed to say this, but it's quite anonymized, and it's been 30 years, so it's probably fine. But I remember at PwC working with a company around distributed work, which was way before, you know, remote work became a conversation. And, you know, I think that noticing those signals and noticing how things change over time, you know, that would be, for instance, an early signal that I thought was really interesting, which has over time, you know, become a huge force within the workforce. And really, I think the speed at which talent is becoming the central strategic variable has been an anchor early signal that I still believe we don't spend enough time thinking about. So it's not just capital, not technology on its own, but the human capacity to learn and relearn. And then the others, because my background is strategic, I think was that the organizations that are winning are not the ones with the best five-year plan, but it's really the ones that are reorganizing to have a learning infrastructure, to think about how they can build adaptability into their models, into their strategic planning, but also their operating models. and be incredibly adaptable. Wow, I love that term adaptability. And of course, it feels like you were sort of describing PwC without putting the label. Because I remember before remote work became, would I say, popular, many thanks to COVID-19, right, PwC were already testing the future of work. And I was part of that better testing, right? testing working from remote locations and when COVID-19 happened it was just a plug and play situation so what would you say regarding would I say seeing the future anticipating the future and performing research in order to ensure that organizations that entities remain agile you know, despite unforeseen contingences, you know, in terms of ensuring that work continues and that we build organizations that are stable relatively to the contingences that the environment might bring up. Where can organizations become more adaptable? it's a funny story so I have to tell you this story before I answer that question because you were talking about PWC being adaptable and kind of human beings being adaptable and we don't it should go back to education but you know most companies can't do that and my adaptability story was I actually interviewed at Cooper's Library and Pricewaterhouse and then the first day of work had a friend send me a note and say, did you see that they merged? And I was like, look, I know you're just trying to yank my chain. You know, I'm so nervous about my first day at work anyway. And they had, they merged the very first day I started. So that was my adaptability story. TWC, yep. Employee number, you know, one, I guess of the new merged entity. so I you know people have to be adaptable you know on a basic level and the thing that I see more and more right now is is from watching what happens when technology gets deployed without that question being asked so I keep seeing this a company rolls out a powerful system and within 18 months the human judgment that used to live in the team is atrophied people stop developing instincts because the machine is doing it for them, or they've already designed workarounds because they don't like the interface. And then when the machine is wrong, or when the situation is really new, then the human capability to catch that is underdeveloped. Like we're not used to taking responsibility. And in all of these conversations I'm having with businesses who are all doing AI business reinvention, this is the crux. They're like, who is responsible? And so this is a moment where being more adaptable and creating an environment that makes humans more capable is requiring us to redesign work. And I think that back in the day, I was in Korea doing business process mapping for a telco. And so it's not that not all of this is new. We've always been in an environment where we had to redesign work to best figure out how to coordinate humans, how to create, coordinate humans with data, digitization, now AI, agentic, physical AI, then quantum. But now we need to do it. We can't do it and then go, okay, that's the system. Let's let it run for five years. It's a fluid, continuous adaptability that both organizations and human beings need to get their heads around and start thinking about. Okay, so you often talk about AI, and of course you say, how do we ensure AI makes humans more capable? So where did that question come from, and why does it matter now more than ever? well i'm somebody who believes that um the whole point of technology is enabling us to have better lives right my desire is for the best possible future for the most possible people and what i see um as the opportunity is for us to thoughtfully design technology to enable to enable human beings to be to to live up to their highest potential. And I frankly, I think we're really far away from that. So, you know, that our ability to be humans is not that great. We don't have time. You know, there's cognitive surrender with AI coming aboard and people saying, well, if the value is efficiency and speed, then I'll use AI because nobody cares if what I'm producing is high quality. They just want it, want it now, want it yesterday. And so I think that that's what I mean when I say, how do we ensure AI makes humans more capable? I think it's about the intent, like what is the broader intent of the business and frankly societal value that we'd like to create and harness technology to create. And the sort of larger conversation believes this, right? You can see that when people say, oh, AI is going to cure cancer. Like we want to believe that it will make us so capable that we solve some of our largest problems. Like we, as a world, we have huge problems. And if we can focus some of both the human and technological firepower at solving some of those problems, I think it could be extraordinary. But using the old way that we digitized, frankly, our processes, We're just taking the same old things that we always did and trying to apply AI to them. So A, AI does not apply to everything. And B, you know, maybe things should be different. Maybe we should be focused on different things. And I think that that's the human capability, the intent, the judgment, the decision on why and what we're going to work on is important. And I think that we need to really lean into that. Okay, you talk about the many problems, especially the big problems we have as humanity. And speaking of problems, one of them is unemployment. And cutting through the noise, is AI replacing jobs, or is it fundamentally redesigning how value is being created? Option C, all of the above. So both are happening. And it matters which one your organization is pursuing. The companies I worry about are using AI just to compress headcount. And some of them are using AI as an excuse to you know, compress headcount or course correct after a lot of post-pandemic hiring. So they're kind of optimizing a cost structure and calling it transformation. And they're rewarded often in the market with share price increase or, you know, investor, positive investor sentiment. But the companies that I find that are really exciting are asking a completely different question. So they're thinking, given that AI can now handle a large portion of what we used to do, the sort of human cognitive labor and some of the human manual labor, what becomes possible that was never possible? What's that? mundane work, the work people don't want to do, people pushing into AI these days. Yeah, the mundane work and all the pain points, the work we don't want to do. But what I find interesting is the value creation, which you pointed out, that like, what becomes possible that was never possible before? And that's sort of the redesign question. And, you know, that leads to entirely new categories of value and new ways of serving customers and new business models. And, you know, the replacement narrative is real. And I think for early in careers especially, it's a concern. But it's the least interesting thing about what AI makes possible. You know, it's interesting that a lot of organizations are caught in the efficiency trap. So most organizations are using AI you know for efficiency or especially from a cost perspective why is this a dangerously narrow approach Well, we talk a lot about bimodal leadership, and it is a dangerous approach because efficiency is ultimately a race to zero. If every competitor has the same tools, and everybody eventually will have the same AI tools, more or less, then efficiency gains are competed away pretty quickly. And you have a faster, cheaper version of the model that may already be obsolete. So I think the organizations that really lead into the next decade are using AI to do things that were previously impossible, not just to do existing things faster. And so there's a difference between optimization and reinvention. Bimodal leadership is where you do optimize in order to free up either the capital or human resources to apply to this reinvention. And the way that I talked about it a couple of years ago is when they projected years ago that you had 14 percent gain in productivity is what if you had an extra day instead of seven days you had eight days and I remember speaking to this huge thousand person HR conference and saying what are you going to do with the extra day like how are you going to structure work if you have an extra day If you have eight days in the week and you just got a free day and that is for reinvention. Wow, interesting. So speaking of reinvention, what would you say are the non-negotiables for leaders in this age and time when it comes to making decisions regarding humans and AI within organizations? So I understand how tough it is to be a leader right now. And, you know, the people I speak to are saying that they're getting five hours of sleep because they're trying to keep up with the information. They're trying to redesign work. They're trying to make sure that work can happen at the same time that they're redesigning work and make sure everybody feels okay so that they don't feel like they're being redesigned out of work. Like it's, it's so hard for a leader. And so first let me just take a pause for compassion. I think that some of the things that they need to think about is where will judgment live? So not every decision should be delegated to an algorithm, although just today somebody sent me a paper about AI's influence on leadership. But even when the algorithm is more accurate, sometimes there's decisions that carry ethical weight or political stakes or human consequences where accountability should remain human. And you need to have some explicit clarity on that boundary. Second, I would say decide what you're building human capability towards. So if you're using AI to automate without investing in what humans do with that cognitive capability that's freed up, then you have a workforce that is actually less capable because they're doing the same thing they always did, only a little bit more of it is automated. or they're doing the same thing and they're relying on AI to write all of or summarize all the emails and you haven't replaced with some kind of level up. So for example, some of the early in career trends I see, the pace setting companies, they are not asking their early in career hires to just do the same thing they always did but with AI. They're setting them impossible tasks, tasks they know they cannot complete, but they're asking them to do as much as possible with AI. And then they pair them with a senior mentor leader to say, here's how to go the last mile. And also to review what their assumptions were. And like, that's a growth mindset. It's a growth mindset for the early in career and probably for the senior leader. And then the third is always governance. I think that governance as compliance and even technological architecture is important, but also governance as a living system. So AI is changing all the time and the frameworks for oversight need to be built for continuous revision and often principles based because the human beings end up being the guardrails in a fast moving organization. Wow. So what would you say is the biggest strategic mistake that companies are making right now when it comes to AI adoption? um they have a tech first approach that people don't trust and they're really interested it's what i call that let's take the robot to the fridge problem which is you have this shiny new object that could you know change the world cure cancer whatever else like you know a robot that can lift heavy objects and save people from rescued car wrecks. And instead, you're like, this is so cool. Instead of going to the fridge to get your soda, you ride the robot to the fridge because it's just fun. It's a shiny object. Let's play with it. It creates absolutely no value. And you could do that on your own much better. And that is a tech-led approach to AI business reinvention that disrespects, that sort of disregards the human experience of being within this organization. And it's very point solution, like let's try this one thing. And McKinsey has shown that actually across 25 different categories, having an end-to-end solution where you really are thinking about what is the value that we want to create in three years, let's say. What is the world look like then and what is the best way to serve that value creation or that customer with the combination of the technology we have now the technology we think is coming the human attributes we have now the human attributes we think we can develop and people a lot of people are not taking the time to do that they're just going okay let me buy this thing you know a lot of people are obsessed with the tools and this is something we emphasize a lot on this podcast we we have a framework called mindset skill set tool set and uh it's really amazing you you touched on the growth mindset the growth mindset is what we promote on on the podcast and you know looking at your work you actually need you know futures research at ServiceNow. And we are at an age in time wherein the future is very, very uncertain. And I think in the words of your friend, who is also a futurist, that is Roy Stour, he talks about leading in uncertain times, that is navigating without a map. And I very much would I say relate with your empathy for leaders right now. It's a difficult point in time in history for leaders. So how should leaders approach thinking about the future when prediction is unreliable? I don't know if prediction was ever that reliable, because strategic foresight started in war, basically. It came out of the military. But some of the times that it's been most famously used is in Shell during the oil price shocks, when there was a really conclusion or an assumption across a wide body of executives that things would not change. Because we are just wired to think that things are not exponential, that they're linear. And so if you would ask 10 executives at Shell to predict what would happen, they would all come with the same answer, which was business as usual. and what I like to think of is preparation so not prediction but preparation what will happen and what are the many different things that may happen if we start to track certain trends we start to think about the pressure points and and then kind of relay those out like what are the you know in foresight what are the different future possibilities what kind of conversation can we have about which one is our preferable future for our organization? And how do we optimize around that while still maybe rehearsing for the possibilities that we may need to face in the future? And you think about, you know, going into a room, if I go and speak on a stage in front of 2,000 people, I'm totally fine because I've done it so many times before. I've rehearsed. The first time I did it, it was terrifying. And the same is true when you start to have these conversations. A, you build up exceptional situational awareness. You know, you've all had these conversations about what may happen. And you've started to track and synthesize and make sense of, you know, what they call kind of time zero events. Like when we see certain signals in the market, let's have that conversation about what could happen next. And we've all kind of, it's like a fire drill. We have either rehearsed or we've talked about what we're going to do. And, you know, that's why in Asia, for instance, in Hong Kong, where I lived, they had lived through SARS. and the minute COVID hit, they said, okay, we know what this is. We've done this before. And they acted really quickly. Whereas you saw other places where they had never experienced that kind of pandemic, where there was no process to deal with it. And there was high emotion and a lack of coordination. A lot of places had no process in place, no infrastructure in place. and it was devastating. And you've actually said this before in the past. You said that the best organizations do not predict, they adapt. So what systems make adaptation, would I say, a smooth process for organizations? Well, I think it's useful to have some kind of genuine intelligence function within an organization. And I say that now as part of a big organization. but even startups within their frame of reference should decide and maybe even, you know, if you have a five-person organization, meet for half an hour once a month to say, what are we noticing in the market and where the market is tending towards? So it's not just market research, but a living process for sensing weak signals from really the edges. You know, the snow melts from the edges, and oftentimes the change that you see is not from the ivory tower or the C-suite. It's really from people who are speaking to customers constantly, who are maybe customers who are early adopters or from adjacent fields. And then the second would be like the organizational permission to act on those signals before they're proven at scale. So different organizations do this differently. Usually people will see things coming in the organization. And I remember being a PwC consultant saying to my father, yes, I interview all the people who have the knowledge within their own organization and then tell the boss what's going on, right? That's the whole idea of surfacing that intelligence. So often people don't have a mechanism for the observations to influence the decisions in time. And then third, a culture that treats small failures as information rather than as, you know, verdicts that affect careers. So the organizations who are adapting fast are ones that are running experiments and updating based on what they learn. And they're real learning organizations. Oh, wow. Interesting. So you talk about deciding how you decide. So what does that mean in high stakes environments? I feel it means being deliberate about your decision architecture. So I mean that from an individual leadership perspective and also from a corporate perspective. and being deliberate about that before you go under pressure. Because when people are in a crisis or facing really novel challenge, you don't have a cognitive bandwidth to design your decision process. And the leaders who are deciding in advance know who needs to be in the room, what information is sufficient to move, where the decision authority sits, what review cadence looks like. And even if that's a baseline that needs to change, I've worked with a ton of boards and boards of directors, and they will have a plan. It's better to have a plan and a decision architecture and change it than to have none at all and spend the first couple of hours trying to figure out what you should be doing. Likewise, that gives you the time when it's not a crisis to think through bias, to develop checks against that. And the people who are failing in the high-stakes situations are not failing because they're not intelligent people. They're failing because their decision processes just collapse under the pressure because they were not designed in better times. And this is what actually results in wrestling and organizations. You know, you said it before that organizations that do not evolve will break under pressure. So what is it that founders should look out for in the process of building these organizations that are resilient, that can adapt, that can evolve under pressure? I think founders of startups probably have that built in because they don have the layers of hierarchy and the organization that make things a little more brittle But I would say build for learning in addition to performance Because organizations that break are usually ones where they don't want to admit uncertainty or changing direction is treated as a weakness. and the ones that evolved just have made psychological safety like a genuine operating principle not just a poster on the wall and that's true if it's a three-person organization or if it is a 30,000 person organization it's about having like short feedback loops smaller experience before making larger commitments leaders who are intellectually humble and when a person at the top says, I was wrong and here's what I learned, that sets a tone that really reverberates across the organization. The tone at the top is very, very important. And of course, it's something that PWC always emphasizes. So as AI becomes more capable, what skill sets will become more valuable for humans? so it's a question we keep asking ourselves and i think it's a defensive posture to a certain extent over the last couple of years that i've had that conversation i'm starting to think that it is a mindset it's not like i don't think that skills Certain skills are durable, right? Sense-making and ambiguity is something that I think is important as a human being, partly because when all your technology goes down, you need to actually be able to still perform. The ability to ask the right questions before you know the answer that you need. cross domain synthesis although I think that AI is starting to do that at least better than me but I seem to be able to connect dots in a weird way that doesn't make logical sense but maybe makes intuitive sense ethical reasoning I think is an important one I think you know, for us to really hone and be thinking about relationship building to create trust for real collaboration. That's something that, you know, people are designing technology and even LLMs for emotional logic, but you still have to be face-to-face with a human and have a conversation and build that relationship. And then adaptive learning. I mean, I really feel like the thing that we need, their fundamental human capabilities, AI can amplify them, but can't replace them. So, you know, always learning, thinking about the willingness to learn, the ability to unlearn, relearn and then find find a place to take your unique capacity and attributes to create value for your surrounding i think i very much appreciate that of course he you are reminding me of the episode i had yeah this is well over a year ago now with our mutual friend Brett King. Shout out to Brett King. And, you know, he said, all I need to tell people is I am a person with a curiosity to ask the right questions. And I can see this is evergreen. The ability to ask the right questions never goes out of fashion. And speaking of fashion, like AI has become what is in fashion right now. that there's a lot of buzzwords out there right now. But beyond the buzzwords, what does it mean for an organization to be future-proof? And what does it look like? That's such a great question. I think that it's an organization where a strategic planning cycle is not just annual, but is continuous, where there's a dedicated function for scanning and synthesizing signals from outside the organization, where a leadership team has genuine cognitive diversity and people who think differently from each other, but build the trust required to use that diversity productively rather than kind of defaulting to consensus ideas. a place where the workforce is genuinely developing, not just being re-skilled for current roles, but being equipped for roles that don't exist yet, and where governance of AI and emerging technology is embedded into operations, not just in the compliance team. Okay, so when it comes to the teams that work in these organizations, there's a lot going on, what I say, regarding redesigning the way teams function. So how should leaders now redesign their teams in order to enable them to become AI native organizations? There has been so much written about tiny teams, and there is a shift in perspective that I don't know is helpful around average revenue per employee, because we're seeing smaller teams of humans with more AI capabilities create more monetary value. So in that context, I'll focus on the human beings. And if you are a leader of a team, I think you need to be honest about what is your team doing today? What value are they producing? Like, what is really the job to be done? And when you map it out, you might find that a significant portion of work is information gathering, formatting, summarizing, scheduling, routing, that kind of thing. AI handles that better than most humans. So then what is the human contribution that you want to be left with? And designing towards that and building smaller high-trust teams where each person is genuinely operating at the top of their capability. I'll give you an example because I think that people feel this pressure, leaders feel a pressure to design this and serve it up. But we have so many instances within our own company where a leader has said, let's pick five topics that we feel are going to change the game in this new AI business reinvention. And let's spend some time coming together in a squad or a guild or whatever you want to call it and really work on disrupting ourselves and work on the future of what this team might be. So I think that that's what I see happening right now in a way that gives people a sense of empowerment, gives people a reason to be creating the future of human AI collaboration, and also being exposed at a smaller level to like what are the risks that might come. So they're in a more experimental, almost mini startups within even larger teams. Okay, interesting. So you have had the privilege to serve on boards, you know, to serve organizations that have impact on a global scale. So what would you say separates the leaders who scale globally from those who stay stock locally? My thinking on this has changed a bit because I am by almost definition a globalist. And in my first book, Future Proof, Reinventing Work in an Age of Acceleration, it talked about technology demographics and globalization. And while I think that globalization has been the story of my era, both the hope that people had for it and the retreat from it right now, I don't necessarily think that you have to be global in order to create value. So let me just say that as a beginning. That said, I appreciate working for global businesses. And I find... What's that? That is a disclaimer. A disclaimer. I work for global businesses and always have. And I see that it's the ability to hold complexity without collapsing it into false simplicity. So leaders who have scaled globally develop contextual intelligence. They don't assume their market's home logic applies everywhere else. They're genuinely curious about why a different market operates differently and what they can learn from it. And they build teams that span worldviews and geographies and invest in creating bonds between people that have that different worldview. So there is a tension of managing very different contexts simultaneously without forcing them all into one framework. But leaders who can do that globally are those that can be quite comfortable with managing all those different contexts simultaneously. Oh, wow. Interesting. You remind me of a phrase that was quite popular at PwC during my time. They say, get comfortable being uncomfortable. table, right? And you've actually spoken a lot about learning today, and it is clear that a mindset shift is required in order to lead successfully in this constantly on certain times. And what would you say is the key to balancing that short-term survival with long-term transformation? The key to balancing long-term survival and short-term transformation is from moving from certainty as a goal to clarity as a practice. You cannot achieve certainty in this moment. The leaders who try to project it and say what they believe is going to be true for all time often end up either lying to themselves or their teams, or they have to freeze when reality doesn't cooperate. So the leaders who kind of thrive in uncertainty have stopped needing to know the answer before they begin. They're clear about their values. Values are very grounding. They're clear about their directions, even when the path is not visible, and they communicate their assumptions and their intent. And that is a huge shift for many leaders that I speak to, especially those that were trained in an era when five-year plans worked and it requires genuine personal development to shift from this more rigid, linear mindset to the more adaptable, exponential mindset. I think that that is amazing. And I just remembered something from PwC. I think the mission statement is building trust in society by solving important problems. So how do the leaders in this age and time build trust when basically the machines are making more decisions for humans? How do we build trust? Leaders build trust by being transparent about what their intent is. So when machines are involved and what limits of involvement those machine has is a sublayer of that. The trust crisis around AI is almost entirely, to me, a transparency crisis. So when people discover the decision affecting them was made by an algorithm and they weren't told, the trust damage is enormous. when they receive a letter that is written to say how sorry we were about the death of children in a school shooting. And at the bottom, it says, written by ChatGPT, the trust is damaged. And so the leaders who build durable trust in an AI era are the ones who explain it clearly. Here's what the AI is doing. here's how we are overseeing it here's where human judgment is applied and here's how you can raise a concern about that so that transparency is the foundation of what i think of as trust architecture and it's not just an ethical imperative it's a competitive advantage and will allow leaders and companies that they lead to move faster with more integrity So what would you say is the human advantage in an AI-driven world? What is the human advantage in an AI-driven world? It's our lived experience. It is the capacity for contextual wisdom. AI is great at optimizing within a very defined problem space. But we're really good at redefining the problem space entirely. We are really good, but a lot of people have fears around AI, especially with losing jobs and losing relevance, losing even their identities. So what is it that people are misunderstanding about AI on a general scale right now What are people misunderstanding about AI In what sense On a general scale, because right now there are a lot of doomsayers out there, and there's this general fear when it comes to AI. it's it's interesting how i get funny comments on our videos on the channel saying really obscene things about ai and it's like nobody's putting people in check right now the fear is becoming pervasive but what is it that people are misunderstanding and what is it that people need to start doing now in other not to become what i say victims of their own fear yeah that's a good point because there is a moment when the fear you have over something prevents you from even beginning to be curious about it and i think that that is an issue yesterday i went to lunch with somebody who's just graduated college and he's in theater and he said, nope, no AI. It's going to completely change the way that creatives make a living, and I want to have nothing to do with it, and I never go on it. And while I respect that he has a point of view, and he said, this is my point of view, other people can have other points of view. A, I'm not wired that way. I'm just curious about everything, pathologically curious, probably. But I think that this is partly a leadership issue. I heard something called FOBO, which is fear of being obsolete, which is basically a deep human fear, right? Like people are not just scared of AI. They're scared of their identities and their roles in that. And in my first book, Future Proof, I talked about this before AI was on the scene because it's a longer lifespan where you're going to have to figure out how to work longer, probably. it is not going to be the same job that you've had your whole life because the lifespan of companies is shortening and you have a disconnect between the education and maybe what companies need. So there's not just AI, right? There's so many different things that are coming together to make people feel a sense of precarity all over the world. And AI is just like the fuel on the fire that I believe will fundamentally change work. But I think that if people can be open-minded and curious about what are the things that I care most about, And I think, you know, really being aware of what value you contribute as a human being to your community or within your organization as aligned to the strategy, like that is a red thread. That is something you need to do no matter what happens. Because if AI is coming, you know, and that's all done, then something else will come. So, you know, that is a quality that as a human being you need. What is it that are my unique superpowers? How can I contribute them in this organization? How might that change when the external conditions change? In the same way that for me, I have lived in the US, I've worked in Europe, I've lived for two decades in Asia, and the value that I provide in each one of those environments can be quite different based on the organization I work for, the country I work in, whether or not I'm leading a team or not, what kind of intellectual experiences I bring to bear. I think of it as a mosaic or even a kaleidoscope where you have all these things. You're a human being. You've accumulated all these lived experiences and your ethnography and your schooling and your work experience and your connections. And they all go in. And depending on where it, you know, you turn it or where you put the tiles, the picture changes of what you can contribute. And I think that that is fundamentally something that we need to teach people to do because we spent too many years telling them you just follow ABC and then it goes DEF to the end of the alphabet and you'll be fine. And you can turn your brain off once you're finished with the ABC part. And it's just not true anymore. People want a predictable paradigm. And of course, I'm going to bring this home right now. I just remembered a comment I saw on this podcast's YouTube channel. And it was dropped by a teenager. He said something. He said, I am a teenager and I am scared for my future because of AI. So what are your words of advice, you know, being a highly experienced person for such people watching us today and, you know, to the younger generation, you know, generally, like how do they equip themselves to stay relevant for the future? So while I don't believe in perfect solutions, I do believe and wrote an entire framework about being perpetually reinventing. reinventing. And in Future Proof, which was all about reinventing work in an age of acceleration, it was about experimenting, reinventing. It was collaboration and focus. And so those are the things that we, even in Future Proof course, teach people to do. We teach them to audit their current value, which frankly you can do as a teenager, that you can do strengths finder as an assessment and find out, you know, not your job title, but like, who are you? What do you actually contribute that creates impact? And being brutally honest about which one of those contributions are, you know, durable and which one is vulnerable as we change. I would say another thing is identifying your highest human leverage, right? What is it that you do that AI does not replicate? And I have three children that are in college and on their way to early careers. And I think that if they can build relationships, develop their own point of view, invest in that deliberately, that that is a huge strategic asset. And even though we're saying AI, no AI, I do believe that people need to build their AI fluency. So not to become technologists, but to become people who orchestrate AI effectively, who think about ways that they can work with new technology as it comes on board, because the next leaders will be judged by how they direct, evaluate, and govern human AI collaboration. Amazing, amazing. The Vice President Global Fintech Strategy for Money 2020 was on this podcast in the second half of last year. Zach Hettett and he said something, your job is not going to be taken by AI, your job is going to be taken by your colleague who knows how to use AI better than yourself. So I think this very much applies in a lot of situations. It's very important that we make ourselves, would I say, AI literate in this age and time. I think that's the bare minimum. Well, I think that you need to get good at noticing because you will not be out of a job because of somebody who uses AI better, you will be out of a job because AI has fundamentally changed the system of value creation in your industry. And so that is why I'm a futurist and I believe foresight allows you to scan for what's changing and where you need to go and learn in order to perpetually stay ahead. That's what I would say. Wow, thank you very much for that take. And of course, there's something I always say on the podcast. Anytime a person shares their time with you, they share their life with you. Of course, the SI unit for measuring time. Life is time. So before I hit the big fire round, we have a tradition on the podcast. So you'd give me a name you would love to see on the podcast. Okay, two names, actually. One name you would invite yourself and one name for me to invite on the podcast. So do you want to take the quickfire round before you come up with the names? Are there any names top of your head right now? Yes, because you said strategy is how we spend our time. It would be David Lansfield, who is writing a book called Every Day Strategy, who is himself a master strategist and also a past partner at PwC. Wow. Ah, another PwC alum. There you go. Is that the name you are inviting? We'll both invite him. I don't have to give you two names. Okay. Okay. I'll do the intro. I'll do the invitation. Okay. Okay. We'll go with one name. We'll go with one name then. Okay. So are you ready to rumble? five quick questions and apparently five quick answers. So number one is opportunity or inequality. AI will create more opportunity or more inequality. What side are you on? Both. It depends on the choices we make now about access, education, and governance. And I think that we have the chance for more opportunity, but the responsibility for decision-making and action is on us. Okay, interesting. So what is one skill to master for every leader in the next one year? What's the most important skill to master right now? Asking better questions. Not just of AI, but of themselves and their teams and their assumptions. Okay, amazing. I love that. Okay, so number three is what is one belief about the future of work that is completely wrong? That the goal of work is to find a stable role and stay there as long as you can. Stability is no longer the goal. It's about navigating and learning, and the people who are going to thrive will be people who can move and reorient and contribute in new configurations, not the ones who just found a safe place to stand and defend it. Hey, there's no such thing as stability any longer. It is gone with the weed. Okay, number four is about starting over again. So if you had to start your career over again today, what would you focus on first? I would have built relationships across industries and disciplines much earlier, instead of thinking I had to pick a lane and stay in it. Because the most powerful thinking and work I've done has always happened at the intersections. And I would have sought those intersections out much more aggressively from the beginning. Amazing. I think that also speaks to the PwC, our professional framework, and building relationships is a pillar on that. And of course, the ability to work with cross-functional teams as well. That is your global argument. The very last question is about legacy. So what legacy do you want to leave in shaping the future of work? I want to have contributed to a world where the AI transition actually expanded human potential rather than diminished it. And that's not just for the people at the top of organizations, but for everyone whose work and livelihood is being reshaped right now. So if the frameworks and thinking I put into the world help more organizations make that choice consciously and well, that will be amazing for me. Wow, amazing. And of course, speaking of amazing, your time today on the podcast has been amazing and of course to the viewers guys uh the future is not coming it is already here and most people are not ready the winners in this next decade will not be the most intelligent but they will be the most adaptable and of course uh once again thank you very much uh diana david do you have any last words uh any final uh uh patting words or do you want to leave a shout out to anyone before you leave today? Well, I've been thinking a lot about my early career and the fact that I worked for Dr. Henry Kissinger, who is no longer with us, and his ability to scan the horizon to see what was next and to act on that information. And so, yeah, I guess a shout out to him. wherever he is because I really appreciate the wisdom and and being sort of observing that from afar and the amount of different kind of people that would go through our office that he would talk to and I think that you know that is what I think is really relevant is continuing to have conversations together across many different people is something that we all can do with fairly little effort. And so I appreciate you for bringing us together on this podcast to have those conversations, Adamala. Wow, thank you very, very much, Diana. David, so to the audience once again, you guys know what to do. Comment, like, share with your network. And of course, always go for something in your life. Conceive, believe, strive to thrive and go achieve. Till next time, it's goodbye from me and of course it's goodbye from Diana Wu David. Wow, amazing. Hey, there was a little bit of a lag in something.