Innovating Leadership:
Co-Creating Our Future

Resources:

Learn more about James on his website at https://www.jamestaylor.me/. His book, Supercreativity, is available at local booksellers and on Amazon at https://amzn.to/4fhIioW.

Our host Maureen Metcalf posts a newsletter every week on LinkedIn. You can subscribe here.

Maureen’s latest book is Innovative Leadership & Followership in the Age of AI. You’ll find details about it at https://bit.ly/LeaderInAI, or check out the Kindle version at https://amzn.to/44buVz8. The audiobook version is now available at  https://amzn.to/4dTCleZ.

Her other 10 books are available on Amazon here.

Other episodes you’ll enjoy:

– The Creative Mindset: Mastering Skills that Empower Innovation with Jeff DeGraff

– Cultivating WONDER: Unleashing Innovation in Your Business with Theo Edmonds

– Greater than Fact: The Power of Leading with Stories with Paul Smith

Guest(s):

Guest(s) Bio:

James Taylor is an award-winning keynote speaker and internationally recognized authority on creativity, innovation, and artificial intelligence. He started his career managing high-profile rock stars and has since become a global thought leader in business creativity and AI-driven innovation. James is on a mission to help individuals and organizations unlock their creative potential, accelerate innovation, and build a sustainable future. Believing that the greatest competitive advantage comes from creative collaboration between humans and technology, he champions strategies to future-proof businesses in this age of disruption. He is a Fellow of the Royal Society of Arts.

Transcript
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[00:00:00]  

Maureen: Welcome to Innovating Leadership Co-Creating Our Future. I’m your host, Maureen Metcalf, the founder and CEO of the Innovative Leadership Institute. This podcast explores how leaders build the capacity required to navigate complexity and deliver results. Today I’m joined by James Taylor, a leading global authority on creativity, innovation, and what he calls super creativity: the intersection of human intelligence, collaboration and intelligent machines. James, I’m delighted that you’ve joined us. 

James: Well, thank you so much. I’m looking forward to this conversation today. 

Maureen: What is super creativity and what problems does it help solve? 

James: So super creativity at its most simple is the augmentation of our human creativity that I believe everyone was born with by collaborating more deeply with other people and machines. So in machines it could be artificial intelligence, it could be robotics, it can really depends on, on the area we’re looking at. 

Really that [00:01:00] fundamentally the book is about creative collaboration, both with other people and AI. The problem it kind of looks to solve really is as we’re going into this age of artificial intelligence that we’re in at the moment, we are seeing kinda one skill that is gonna become much, much more important. 

And this is based upon work by the World Economic Forum, interviews with a thousand global business leaders reports by companies like LinkedIn. And that skill is our creativity, which is our ability to generate, develop, and, and then execute on new ideas. So really the book is based upon the keynotes that I give to very similar kinda audiences to this podcast of senior leaders and organizations, boards, C-suite. 

And it’s really about how they unlock the creative potential in themselves, their teams and their organizations. And obviously the cool part is around artificial intelligence. 

Maureen: So why is it so relevant now? 

James: Well, fundamentally, as we’re seeing especially now we’re moving into things like agen AI, and I have to preface this by something I share on stage a lot is that AI is not new as we know. It’s been around since 1956, the same year my father was [00:02:00] born, and we had machine learning and deep learning, and then a few years ago we had large language models and then ChatGPT, we’re now moving into this era of AI agents and agentic AI. So the interesting thing about where we’re at just now is that essentially AI will replace many of the non creative tasks that we do. The analytical tasks, the routine, the mundane. And if you listen to speeches by people like the founder of OpenAI of Chat GPT, he talks about really these core skills that are gonna be most important. And creativity sits at the top of that because these are tools to a large extent. They’re very, useful tools, but it really come back down to the human and the human teams. What do we want to create? How do we want to innovate? What kind of future do we want to see? 

I was just doing an event this week for L’Oreal and the other speaker there was a woman called Shonda Rhimes who is behind great shows like “Grey’s Anatomy” and “Scandal” and “Bridgerton”, and we were having this really interesting conversation about creativity in the age of artificial intelligence, and we both kind of agreed that [00:03:00] creativity, this most human of skills is actually gonna increase in importance, not decrease. But here’s the bad bit, and I ask audiences to do this on stage. I ask them, “How many of you in the room consider yourself to be creative or good creative thinkers?” Depending on where I’m speaking in the world, that number will be as low as 15%. So if I’m speaking in East Asia, Korea, Japan, it’s gonna be about 10, 15%. If I’m speaking in the US it’s gonna be 40%, so it’s gonna slightly higher. But if we think about that, that means the vast majority of people in organizations do not consider themselves to have the one skill that’s gonna be most needed to survive and thrive in this new age. 

So Time Magazine causes this the creativity crisis. So this book is a kind of call to arms about how we really first embrace the creativity that we’re born with, but then go one step further to this idea of super creativity, which is about really developing this skill in organizations and teams and leaders through working with other people and with technologies like AI. 

Maureen: Let’s step back and define creativity. 

 Often people when they [00:04:00] hear that term think “I’m not an artist, or I don’t write scripts, I just, you know, work in a business.” And yet your call is leaders must be creative. What even is it and how does it apply in a business setting? 

James: Yeah, so one of the challenges with this word ” creativity” is it’s often thought of(as) music, art, those areas. Generally my audience are not from those worlds. Most of my audiences are from global Fortune 500 companies in leadership. And the other challenge that you sometimes find is people use creativity and innovation interchangeably. My generation, Gen X and the Boomer generation… we tend to be much more comfortable using the word innovation, whereas the younger generation, they often use the word creativity when actually really what they’re starting to talk about is innovation. Creativity and innovation are not the same things. 

Creativity is about bringing new ideas to the mind. Innovation is about bringing new ideas to the world, but without creativity, there is no [00:05:00] innovation. So creativity is really the engine of innovation. That’s why we often talk about this engine that we have to kind of develop. And if we take one step, even just before creativity, if we say, “Well, what is the fuel for creativity?” 

It’s really curiosity. Which is our ability to ask questions. And if you look at great leaders like Julie Sweet, the CEO of Accenture, she was asked the other day, “What are the most important skills today in organizations?” And she said two things: leadership skills, so your ability to lead and inspire others; but the second one was curiosity. Your ability to ask better questions. And you have to really develop this sense of curiosity if you’re gonna get creativity. And that’s gonna then lead to innovation. So these things are kind of linked. 

Maureen: Our work with AI is all about asking questions. If I don’t ask good questions, what I get back is not gonna be very useful. 

James: a year ago a lot of people were talking about prompt engineering. Actually you can use prompting in a slightly different way with AI, for example, is you can use prompting to ask it to prompt you to think about [00:06:00] the questions that you should be asking. 

So really using question definition. It’s a little bit like we have problem solving and problem finding. You know, a lot of companies think about problem solving, but actually the more interesting one sometimes is problem finding. 

And using AI to help develop your curiosity and your ability to ask better questions is very useful because one of the things, and I talk about this in the book, is this idea of imaginary masterminds where our brain is amazing, but it, it’s always looking for ways to save energy. And one of the ways it does this is through cognitive biases. 

So we say, “I’ve seen a problem like this before, therefore the answer must be this.” And sometimes it’s right, sometimes it’s wrong. And so as humans, we have to figure out how to deal with the cognitive biases, authority bias, confirmation bias, all these 50 different biases that we tend to have, and usually what leaders do is they have people around them who think differently from them who challenge their thinking. In the book I talk about creative peers like Warren Buffett and Charlie Munger, for example. They think [00:07:00] differently and they challenge each other’s thinking. So one of the ways that we can actually use AI is if we don’t have people around us who think very differently to us. We can use it almost as ways to help us dig into our cognitive biases and find our weak spots and almost stress test our ideas. So that’s using AI in a slightly different way than just using it like Google to come up with answers. 

Maureen: Realizing in the moment, “Oh yeah, I can, I can now solve this,” where I didn’t have the capacity, or my team may not have had the capacity previously. 

James: Yeah. So one of the things I like to do, I talk about this in the book, is this idea of building a virtual or an imaginary mastermind. Choose those five or six individuals living or dead, real or imaginary, and say, “Okay, these are the five or six individuals. And they may be come from different perspectives, different industries. They may be business people, they may not be business people. And then here’s the proposal, here’s the idea, here’s the concept. What are the questions I should be thinking about here?” So. If one of my five or six was Satya [00:08:00] Nadella. Satya would some come and say, “Hey, you haven’t really thought about this thing.” 

Or maybe if it was Maya Angelou or Warren Buffet, name the person. the important point that it’s doing here is it’s not coming up with the answers. What it’s doing is it’s helping you triangulate around that and start to think. And if you wanna go one level, even deeper than this, one of the issues is that , if you’re only using one particular tool, let’s say, uh, you use Claude all the time from Anthropic, and you don’t use Chat GPT and you don’t use Gemini. Each of those tools speak in a slightly different way. So the first thing I often say is in the settings of any of them go in, because most of them have been trained by people that look like me and from California and it has a certain kind of tone. 

It could be quite sycophantic. It can come back, James. That’s amazing. What an incredible idea.” I was saying to the audience this week in New York, I said, “You know, you can change it. Have it speak to you like a New York cab driver, you know, challenge you, like, be direct to the point. No fluff.” But if you wanna go one step [00:09:00] further than this, there are now a number of tools coming along. And what they’re allowing you to do is like, here is my idea, here’s my concept. And essentially it will put it out to 20 different AI agents and then what they’ll do is each of ’em will come up with their own thoughts and then they will get together, have a little conversation between the AIs and then come back to you with their best judgment or their best questions, or their chance of their probabilities of certain things going in one direction. So that’s just another way you can just kinda push things even a little bit further. 

Maureen: Does that exist now? 

James: Yeah, there’s a tool just now: if you go onto GitHub, and I’ve forgotten the name of it. It’s something Fish. It’s like one of the number one things that people are downloading just now. There’ll be lots of these kind of coming along now . It is just a useful thing. It’s like what we do all the time. If you take soundings from something, you’re probably gonna ask three or four different people with different backgrounds. Like, “Hey, what, what do you think of this? How would you approach this idea? What am I not seeing?” And all this is just doing it at a much bigger scale with [00:10:00] much more data. 

I have a super creativity podcast as well. I was interviewing the former director of GCHQ, which is one of the British Intelligence Services, so our equivalent to the NSA that you have in America. 

And we were talking about this, about data, and he said that one of the problems about even these amazing large language models is: The information that they’re trained on is only 0.03% of all available information out there. The vast majority of information is held on private servers and private information behind paywalls, behind firewalls, behind different things that a company owns. 

So I was just doing an event the other day; I was doing a panel with someone from Volkswagen in Germany, and you know, I think about the amount of knowledge that organization has: industrial knowledge, intellectual property, just like incredible data, and that isn’t necessarily being sourced by any of these large language models. 

So it’s how you can combine those things and then also bring in the [00:11:00] people side as well. 

Maureen: To the extent that companies train their models, I only then get access to my company’s trained model, not Volkswagen or L’Oreal, or Competent Boards. And yet being able to pull from my own is also very helpful. 

James: A lot of companies would invite me to come and speak at their conferences, and they would say, talk about the bright shiny thing: whatever the latest thing was. But as soon as you really get into any depth, you suddenly have to talk about data and you have to talk about governance. 

Most don’t wanna talk about that on larger stages. With the amazing, amazing opportunities that come from artificial intelligence also come risks. And unless we think quite deeply about the risks that come with it and how you mitigate risks and how you quantify those different risks, then we could be in a pretty dangerous place. Some of that groundwork often hasn’t been done. And then you get into the dangers of using like shadow AI and people are using different tools and public data, you know, [00:12:00] information becoming publicly available. And that’s definitely where we, we don’t wanna go. 

Maureen: We wrote a book a couple of years ago on leadership in the age of AI and the 10 mindsets required. Creativity is one of them. And also risk management, and then systems thinking. So what systems do I put in place to ensure we mitigate risks?  

James: You need those guardrails. But then kinda coming to the culture piece, the thing I notice most often in organizations that do this idea of super creativity well, what they tend to have in common is a sense of psychological safety: simply this shared belief that you wouldn’t be punished or humiliated for speaking up with ideas, concerns, or mistakes. So going back to the risk piece as well, have you created a culture in the organization where people can not get sucked completely, into the kinda tech bro thing, but they can also raise their hand and say, “I see a risk here. I see a danger here. How do we think about this? How do we mitigate this?” And so that’s just having that openness. 

What is the thing that often links creativity in different places and people? It is actually this [00:13:00] word openness, this value of openness. You see it time and time again, and sometimes it shows up in the sense of curiosity, but sometimes it also shows up in the ability to challenge ideas, challenge ways of working, to critique, to really think deeply as well. So these are all just different forms of openness. 

Maureen: what do you do culturally to build openness? 

James: 80% of AI initiatives and organizations fail to deliver value for the organization. And everyone is kind of thinking about this just now. The huge investments going into AI, it’s only just starting to show up in the productivity numbers, but there’s also a large amount of churn. 

And I think what we’re seeing is we’re seeing a lot of pilot purgatory, as I call it, lots of things getting stuck in pilots, and that’s fine. You know, people are just kinda figuring out, but now we really, really need to start delivering value. 

And when they dig into this, what they find is that only 20% of it is because of the technology itself; 80% is the people, the playbooks, the [00:14:00] processes that are being run. So we have to spend a little bit more time thinking about that. So a perfect example of that, how you think about the 80% piece in why AI is not being deployed well and not delivering value is something like the competency penalty. What the competency penalty is, is basically people are afraid that using artificial intelligence in their work will make them seem less competent in whatever their professions are and it’s quietly derailing AI adoption. 

So, for example, there was a company recently , they gave access to AI agents to 25,000 employees. And yet after six months, only 40% of people were actually using these tools. And so they were like, well, what’s going on here? Why, why is this happening? And so they did a little study with a thousand engineers at this particular company. 

And they had them review code. Some of the code is written by a human on their own. Some of the code is written by a human collaborating with an artificial intelligence. And what they found [00:15:00] is that when someone thought a piece of code was written with the help of an AI, they judge that person’s work to be 9% lower than if it had been written by the human on their own. 

Interestingly though, on the cultural piece, if a woman uses artificial intelligence, she will be judged to be 26% less competent than a man for doing identical work. So  

this is a culture piece here and where you most often see this is where you see often older male non-ad adopters of AI reviewing the work of younger female workers who are using AI. They’re the worst critics, those older, non-ad adopters of AI. So the good news is it’s actually quite simple to solve this problem. So the first is you map the hotspot. So you look in the organization and you can do this if a company uses Copilot or Chat GBT, you kind of look and say, well, in which teams do you have this big range of [00:16:00] senior people not using AI at all? Junior people, you know, using it all the time. There’s a differential there. The second one is, you really wanna highlight people in the organization who are seen as, role models, you know, are great at what they do and highlight how they are using artificial intelligence. 

And this is basically showing that excellence in your job can coexist with the use of artificial intelligence. And the third one, and this is maybe controversial, is don’t put AI used tags on things. You should focus on the output rather than anything else. And so some companies still put, like “This was partially created by AI.” Obviously there are some exceptions here. If you are doing scholarly work or work like on finance, you have to put certain things in. But a lot of things you should just be focusing on, is this good? You’re looking for hallucinations and all those things you would normally do anyway, but they’re, they’re actually becoming a little bit less. 

But something as simple as a competency bias. That gets you quite a bit of the way there. There’s all these other things you can start to do, but a lot of them [00:17:00] still track their way back to people, playbooks, processes, leadership. 

Maureen: This sounds like bigger. More accelerated. But it sounds like we treat it like we would treat any other large change initiative. 

James: Correct. Exactly. And there’s different models obviously you can use on the change management side. And I just spoke earlier last week in Amsterdam for an organization called Scaled Agile. What they’re interested is like, okay, how do you take all those AI tools and all the things that are kinda going on there, and really bring this into the organization and do this at scale and do it with some of the classic change management. And this is my hope here, this is where we get to maybe in two years time, is we almost don’t really use the word AI so much in a conversation in the same way that we don’t use e-commerce so much as a phrase or the internet and a phrase, it just is, we just assume it’s baked in. Arthur C. Clark, the writer, once said technology at its best should appear like magic. It should kinda disappear [00:18:00] and I think that’s when it’s done well. People like Rita McGrath talk about this as well. 

Uh, a professor at, I think she’s at MIT, so she talks about how this innovation has gone a little bit quiet, less people talk about this word innovation as a term. I think that can end up coming back. Because AI has sucked so much of the energy out of change management, innovation. ‘Cause everyone just talks about AI, AI, AI. 

And my hope is that we are gonna get through this little phase just now and we actually get back to some of the core things that we know. We have to think about how to manage change, how to lead people through periods of change. How to ensure that innovation and resources are being deployed in the best way that provides value to the shareholders, stakeholders, and in the organization.  

Maureen: How do I continue to deliver value as a human leader; what are the mindsets I should be focusing on? 

James: The mindsets we spoke about earlier, the sense of curiosity. This is, I believe, a new roaring twenties we are on the start of just [00:19:00] now, and it’s gonna get messy and there’s gonna be creative destruction in this process. So it is also, we need to focus on not just innovation, but also exnovation: killing off things, killing off projects, things that are no longer delivering value to make space for the things that we want to do as well. And then the other thing I would take in terms of a mindset, and I put this as a challenge to a company last week, is about a year ago, Sam Altman from OpenAI said in his lifetime, he thought we’d be starting to see the first one person billion dollar business. 

It didn’t take his lifetime, it took a few months. And so in February this year, we saw the first one person, $10 billion company. So one person had created an AI agent, a tool, in October of last year. They sold it, I think in February for an estimated $10 billion, $1 billion in cash, $9 billion in equity. 

Now think about that for a minute. That’s a one person, billion dollar, multi-billion dollar company. The very least you should be looking about, okay, how can we start to [00:20:00] deploy these, this technology, these tools to drive greater value from what we’re doing. 

You know a good example here, I have a client, Micron in the US. They make memory for the silicon chips and things, the farms, data centers we’re looking at today. And 95% of their entire procurement process now is being handled by AG agentic AI, by AI agents; 95%. 

At this point, then you start to think, “Well, what are we gonna do with all those people?” Definitely it’s showing up in the US in the job numbers. You’re seeing a lot of people losing jobs in big companies. 

AI is actually not the main reason behind that. I think a lot of the reason is ’cause people over hire during the pandemic and then interest rates are also going up. And so people are really having to focus on that bottom line. 

But with the AI really starting to come in, you do have to start making decisions as a leader now, okay, we have 10,000 people or a thousand people, that we are gonna have to think about what their job is. They’re working customer service, they’re working in administrative roles. There’s other types of [00:21:00] roles, certain types of middle management roles. 

So if you look at a company like Ikea, they decided, rather than let all those people go– I think they had about, I think it was like 3000 people in this particular function– they said, rather let those 3000 people go, gonna, we’re gonna rescale them and turn them into interior designers. So now IKEA offers an interior design business. 

That business generated $1.3 billion in revenue last year, a brand new business. The smart leaders, I would suggest is they think forward. They think, “Let’s assume in two years time, everyone pretty much has a very similar tech stack. Maybe a couple of exceptions. What are we gonna do with the people? How do we want to redeploy these people? How do we wanna work much smarter?” 

And so you’re not necessarily about building one person billion dollar businesses, but it’s a mindset like that, makes you much leaner and much more competitive. 

Maureen: I just had an article published in Forbes that looked at kind of how do I implement AI? And then the last item, and I wonder if it [00:22:00] should be first, but it’s what business are we in? What do my customers value and what will they value six months from now? 

James: Leaders need to think very, very hard about what the future is gonna look like. What is that? What is your industry? What is that world gonna look like in two, three years time, four years time, five years time? 

I think very carefully about do we have the right products, services, offerings for where that world is going? It gives you a good roadmap where to go. 

Really also using your imagination. That is kinda what that is doing. You’re using your imagination, creativity, like how is our industry gonna change? What is gonna no longer be required? I remember when the pandemic happened and I did a, a session with a well-known luxury clothing company. 

It was a virtual session we did, and we kind of mapped this out using the creativity of the people and they, they very quickly realized, well, people aren’t gonna be buying as many suits. They’re gonna have more leisure wear.  

Sales of our shoes are high-end shoe [00:23:00] products. That’s gonna change. 

We did the same activity though as we were coming out the pandemic. And we thought, “Oh, okay, everyone’s buying Manjaro, they’re buying Wegovy, those kinda products. Everyone’s gonna need new wardrobes now. Their wardrobe that worked for them three years ago doesn’t work for them today. 

Let’s think about that: creativity, curiosity, asking questions. 

Maureen: How do we help leaders stretch their own creativity and their vision to really get a sense of what is this gonna look like? 

James: I mean, I, I think one thing you can do, depending on the industry that you’re in, is you can travel. If I wanna step into the future, uh, I go to cities in China for certain things. I can basically get a picture of two years down the road, like where, where we’re going, electric vehicles or, or, or certain other things as well. 

I think travel is a pretty amazing thing to do. You can read things, but nothing has the impact about going somewhere, going into businesses. Often in other countries seeing what they’re doing, how they’re applying this technology. Obviously you’re [00:24:00] seeing it just now in, we’ve got wars going on around the world. 

You’re seeing that you’re seeing in different parts of the world that, you know, those things taking you a bit into the future about where we’re going there. So I think it kinda stems from that. I think then it comes back for that leader to say, “Okay, that’s interesting about doing that as individuals. How we, how do we create a system for doing this?” 

you mentioned Forbes. I was quote in a piece in Forbes recently with the team from Hewlett Packard Enterprise that created a thing called Idea Matchmaker. And it’s a very simple tool. They had a similar problem. 

They wanted to figure out how could they go from idea to execution much more quickly and speed up the process of innovation. So Idea Matchmaker is just a very simple tool that all 65,000 employees have access to. So anytime an individual spots a problem or an opportunity and have an idea for something, they can put that idea into the app and then the AI that sits and runs behind it recognizes what is the ideal combination of team members required to make a project like that successful. And it works like a modern dating app, like [00:25:00] Tinder for example. You know, swipe left, swipe right. So let’s say if I’m a data scientist, I’m gonna be seeing the ideas from other people in the organization that the AI recognize that someone with a data science background is required. 

And like I say, “Oh, I’m interested in this project.” But the other thing that’s quite nice is the AI also has the HR information in there, so it recognizes the psychometrics of the different team members. So it says, ” We’re gonna put you together in a team to work on this project, not just based upon your skill sets, but also your psychometrics. Because we want a mix of those big thinkers, those people that are researching, like looking into the future. But we also want completers finishers, people who will kind of get into the nitty gritty, love that side.” And so that’s an example of a very simple tool. It’s called Idea Matchmaker from Hewlett Packet Enterprise… internal tool they’ve built up. 

The other thing I really like about something like that is it allows them to spot the hidden figures in the organization. People that don’t take the limelight, but [00:26:00] they have unique skills, unique talents. 

They’re amazing, but they’ve been quietly kind of hidden out of sight and they bring them to the fore now. 

Maureen: I love the idea that there is a way to identify and amplify people who are maybe just introverted, aren’t forward, but are delivering highly competent high impact work and are undervalued just because they’re not visible. 

James: It’s the very first part of the book. I talk about the story from my background. Before I do what I do today, which is being a keynote speaker , i used to manage the careers of high profile rock stars, so I worked with members of the Rolling Stones, multiple Grammy Award winners. And I start the book not talking about AI or innovation; I started the book talking about this experience I had standing at the side of the stage at London’s Royal Albert Hall. And this 5,000 capacity venue, and I’m standing there and I’m watching my artist as they perform with the spotlight on them. And I, I’m noticing that the audience is seeing that person, that singer with the spotlight [00:27:00] on them and they think this is the lone creative genius, but what the audience isn’t seeing ’cause I look to my right, I can see the 100 or 200 people backstage who are just  

who are just as creative are, are just as much a part of making a creative and successful and innovative show. As the person with the spotlight on them. This is one of the reasons I embarked on this journey that I do today, wrote this book– was for all those backstage heroes, to really kinda celebrate them as creative, not just the person, the CEO in the front cover of the magazine or that person on the stage with the spotlight on them. This book is my call to arms for those people, and maybe this is the reason that, you know, the industries often book me most like the finance or accounting or legal industry or technology. Often these aren’t the so-called sexy industries. And they’re often not the places where you think about that word, creative. 

But I see huge creativity in these places. They just need to recognize like, what does that term actually mean? How does it apply to the work that they do? 

Maureen: how do you use super creativity [00:28:00] combining with AI to amplify the impact of those 200 people supporting the one. 

James: Yeah. So I talk about the two ways we often use it like centaurs or cyborgs is, is one way. So cyborg is simply an individual who is intertwining everything that they do with AI, constantly refining and molding its responses. It’s like a guitarist that has a guitar. The guitar becomes part of them. 

So in this case, AI just, it’s just part of like who they are. So that’s the kinda cyborg way of doing things. A centaur, usually a more senior manager is someone that looks at a project or a piece of work and has the understanding, the skill to be able to say, “These are the things, these are the tasks that the AIs are gonna do, the agents are gonna do, and these are the tasks that myself and my human team will do.” 

Whether you decide to be a cyborg or centaur in your work doesn’t really matter. But that’s just first, it was kinda going in with that approach, to going in with this idea of augmenting the work you do with AI. And that’s gonna take different forms in different industries. I talk to some of the managing partners at law [00:29:00] firms. 

It’s completely changing the way that they work. And actually for them, their role as that trusted advisor actually becomes more important because AI is doing a lot of the grunt work. Gets rid of a lot of that work for them as well. Now, here’s the thing, and I don’t know the answer to this. I’d be fascinated to know your audience and your listeners thoughts on this: how do we think the shape of an organization will change because of this? So at the moment most organizations are like triangle shapes with like small top, small number of people at the top, a lot of people at the bottom. 

Many people think that what’s gonna happen is this will shift and it can be an inverted triangle. Maybe a lot of people at the top now, less people needed for more junior positions. AI is gonna do that. There’s another thought which say actually it’s gonna be more like a diamond shape. 

Fewer people at the top, few people at the bottom, but we need lots of, almost like middle managements. And that kind of goes against what we’ve, we’ve been doing probably for the last 30 years in management and, and leadership where we’ve been getting rid of those middle levels, that connective [00:30:00] tissue may actually become more important. 

But then when I look at a lot of companies, they really think about how do we redeploy some of these people? Yes. Some organizations will just go straight for the, the lever that says, you know, mass redundancies. 

But a lot of them are saying, “Well, how do we upskill and re-skill these people? How do we take people with us on this journey? How do we ensure that the people aren’t fearful of this?” 

They’re excited about this. And if you look at countries like Singapore, they’re leaning in to this. It’s no surprise that Singapore has probably one of the best AI governance frameworks that’s getting adopted by lots of other countries now. ‘Cause they’ve really asked the deep questions about recognizing our most important asset are our people. 

How do we use AI to augment them, not necessarily just to replace them? 

Maureen: What one question should leaders ask their teams about innovation this quarter? 

James: Sometimes I’ll pose this in workshops with audience and it’s very just quick. It’s just to essentially say, if we were to create our own competitor, how would that competitor do [00:31:00] it? 

Most companies you don’t have the luxury of doing, ’cause you’ve got existing tech stacks and existing systems and everything. 

But just going through that process makes you often realize, actually this is the gold that we have in this company we’re not making the best use of, or maybe we have these layers that we can strip out or do things much better. So if, if you were to create your competitor tomorrow, you actually build up a second business, it’s gonna be your competitor, it’s actually gonna replace your entire business and gonna take your business from you: how would that work? 

Maureen: So next question, one capability to strengthen before scaling AI. 

James: Values. 

Values. What are your values as an organization? If I was to go around everyone on that team and say, “What is the values that this organization’s based around? What do we care about?” It shocks me how few that they actually know their organization’s values or their company’s values. I think if you get those really strong, then it removes a lot of things ’cause you can go back, if we think about launching this new AI product or using AI in this kind of way, you go back to your values and you say, ” How does this [00:32:00] align with our values?” 

Maureen: Clarify values, and then I’m gonna extend that to say: and ensure that your systems reflect those values. 

James: Correct. And your people know those values right across the organization. There’s some companies I go into and they, they are living their values. Other organizations I go, I could be anywhere. 

There’s nothing that makes this distinct as an organization, I don’t feel anything in this organization. And, um, so yeah, values. 

Maureen: Is there any closing thought that you want leaders to have top of mind about super creativity? 

James: Go into it a little bit from a sense of play. Uh, and I know say, play and business don’t often don’t go together, but a very simple thing you can do is to create three lists. Three columns. And in that first list, simply say, “What are the things I do which I don’t enjoy doing. I’m not very good at doing. Not the best use of my time?” Next 30 days, [00:33:00] there’s tools I guarantee you that already exist to get rid of those things on that list. Do that first for the first 30 days. The next 30 days, focus on things which you maybe you can do, but it’s not the highest and best use of your time. 

Work on that list next and then the 30 days after that, those things you enjoy doing, you’re probably quite good at doing, but it’s not the highest and best use of your talents or where you’re sitting in the organization now. And focus on which AI tools do you have to do. Certainly in that first list, you probably already have the AI tools to do that in the next 30 days. 

You don’t need to have to learn anything particularly new. As you get a bit further, you might have to learn some new skills, maybe use different tools. 

Maureen: Beautiful. Thank you. Hold up your book; title? 

James: The title is “Super Creativity, Accelerating Innovation in the Age of Artificial Intelligence.” 

Maureen: Beautiful. James, thank you so much. I assume we find your book on all the normal outlets. Do you also have a book website? 

James: Yes, if you go to JamesTaylor.me/SuperCreativity, uh, you can go and find [00:34:00] that. But actually I would ask if people wanna get a copy of the book, go to your local independent bookstore, wherever you are in the world, and go and buy it from your local independent bookstore and support them. ‘Cause leaders are readers and we want, we want more readers and we want more writers in the future as well. 

Maureen: Thank you so much for joining us and to our listeners, please like us, share us, share James’s conversation and focus on what are your values as you’re implementing AI, and how do you ensure that they are firmly embedded in the organization.