Brian Evergreen on How You Humanize Work in the Age of AI EP 462

AARP
This episode is brought to you by AARP. Ten years from today, Lisa Schneider will trade in her office job to become the leader of a pack of dogs as the owner of her own dog rescue. That is a second act made possible by the reskilling courses Lisa's taking now with AARP to help make sure her income lives as long as she does and she can finally run with the big dogs and the small dogs who just think they're big dogs. That's why the younger you are, the more you need AARP. Learn more@aarp.org skills this podcast is supported by FedEx.

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John R. Miles
Coming up next on passion struck. My hope is that in this era of AI that people would first of all see the value that they have as people, as venerable. It's not going away. The machines give us new means of creating more value, but they don't take away from the value that we have as people. Welcome to passion struck.

Hi, I'm your host, John R. Miles, and on the show we decipher the secrets, tips, and guidance of the world's most inspiring people and turn their wisdom into practical advice for you and those around you. Our mission is to help you unlock the power of intentionality so that you can become the best version of yourself. If you're new to the show, I offer advice and answer listener questions. On Fridays.

We have long form interviews the rest of the week with guests ranging from astronauts to authors, CEO's, creators, innovators, scientists, military leaders, visionaries, and athletes. Now let's go out there and become passion struck. Hello, everyone, and welcome back to episode 461 of Passion Struck. Consistently ranked the number one alternative health podcast. A heartfelt thank you to each and every one of you who return to the show every week, eager to listen, learn, and discover new ways to live better, to be better, and most importantly, to make a meaningful impact in the world.

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It's hard to even believe, and to me, this isn't just a number, it's a testament to the movement we're building. The conversations were sparking and the change were inspiring across the globe. In case you missed it, earlier in the week, I interviewed doctor Terry Walls, who joins us to share her revolutionary approach to health and wellness. Discover how she defied conventional medical wisdom by developing the walls protocol, a diet based treatment that transformed her life with multiple sclerosis, as well as her insights on how dietary choices can influence chronic diseases and overall health. I also wanted to say thank you for your ratings and reviews, and if you love today's episode or Terry's, we would appreciate you giving it a five star review and sharing it with your friends and families.

I know we and our guests love to see comments from our listeners. Today, we're diving deep into the intersection of artificial intelligence and human centric leadership with the visionary Brian Evergreen. As the founder of the profitable good company and a trailblazer in the field of AI, Brian has reshaped the narrative around technology and leadership, advocating for a future where AI enhances rather than diminishes our humanity. In this compelling conversation, Brian takes us on a journey through his latest work, autonomous transformation, creating a more human future in the era of artificial intelligence. He reveals the critical imperative facing today's leaders, the need to pivot from outdated, mechanistic approaches to a new era of human centered social systems empowered by the latest advances in AI.

Drawing on his rich experience as an autonomous AI research leader with tech giants like Microsoft, Amazon, and Accenture, Brian shares unparalleled insights into how leaders can leverage AI to fuel creativity, innovation, and economic growth, all while achieving the elusive goal of profitable good. Listeners will be captivated as Brian discusses how to think like a fortune ten AI leader, uncovering the strategic tools that can ignite a future focused mindset driving your organization's strategic objectives forward with AI. Unleashing AI's potential exploring the transformative possibilities of AI tools like chat, GPT, stable diffusion, two Jasper and autonomous AI, and what they offer for business operations and customer interactions. We'll also discuss the culture innovation nexus, as Brian introduces groundbreaking methodologies for cultivating a disruptive, collaborative environment that can unveil opportunities that were previously unseen. Prepare to be inspired as Brian Evergreen guides us through a blueprint for a more human future in the age of artificial intelligence, underscoring the essential role of visionary leadership in navigating this new frontier.

Thank you for choosing passion struck and choosing me to be your host and guide on your journey to creating an intentional life. Now let that journey begin.

Brian Evergreen
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John R. Miles
I am absolutely thrilled to have Brian Evergreen join us on passion struck. Welcome, Brian. Thank you, John. It's great to be here. I appreciate you having me on.

Brian, I'm going to start out with two things that you and I actually have in common. I was with Arthur Andersen business Consulting, and you were with Accenture, which had formed out of Arthur Andersen. And I wanted to ask you, while I was starting my career there, we went to St. Charles and studied something called method one. And I also wanted to understand if you also studied method one for implementing large scale ERP solutions.

Brian Evergreen
I've heard about it, and I did go to St. Charles when I onboarded, but I was not trained on method one. Method one was so robust, and I think it was one of the best methodologies that was ever created. But overall, it was a waterfall methodology. And many of the clients that I was working with were startups.

John R. Miles
Small and medium sized businesses didn't fit all the different needs that we had. And so I took some of the most fundamental approaches from it and turned it into what you would now say would be an agile methodology. And that methodology proved to be so beneficial throughout my career and now in my personal life. The second intersection point we had actually came during my time at Dell, where I had numerous interactions with Steve Ballmer, who at the time was the CEO of Microsoft. And this occurred especially during a time at Dell where we were looking to implement our first mobile device that was called the streak, which was going to be our entry model going into the mobile phone market.

And fast forward a couple of years later, Steve actually asked me to interview for becoming the CIO of Microsoft. And so I went to Seattle to go and interview. And at this time, it was about 2011, which is, I think, before you ended up getting there. But what I found was a really interesting environment that was very high pressure and fueled by intimidation. And I remember going through a series of different interviews, and then I ended up having one with this gentleman who had actually been at Microsoft for a long time.

But it turned out being like a breath of fresh air. And it was actually Satya, Nadella. And coming out of all those interviews, I ended up not pursuing the role because I thought it was just going to be a fryer cooker if I would have gone there. But what I wanted to ask you, and what I think was typical of a company like Microsoft at that time is sometimes companies go down this path where they are the golden childs and they're highly regarded, and then they go down this path where that luster kind of leads them. It's very interesting to me that Satya has ended up transforming the entire company.

So it's back to being one of the most desired companies in the world for software engineers coming out of Silicon Valley. So it's so interesting for me to hear that with this transformation, what is the secret sauce that he brought to bear? I love this question. And I think that it's fascinating because you hear all the time this idea of, like this question people raise about is, does top down leadership matter that much? Is it just about, should we just focus on bottoms up?

Brian Evergreen
What's that balance of how important the role of leaders is? Are they just supposed to sort of govern the p and l or can they really shape the culture? And I think it's a really, really interesting case study because at the time that I first started consulting with Microsoft, when was just before Satya came in. So to your point, I was exposed to, and I obviously saw at that time the day he came in, it's not like the culture immediately shifted. Right.

It takes time for change to take place. And now it's at a point a decade later where when you're referring to somebody, if you brush up against somebody and they try a certain kind of, I guess, tactic, to your point, about intimidation or even something where you can tell this isn't really the way that the sort of leadership doesn't follow the leadership model that Satya has put in place. There's a phrase now where they say, oh, well, they're Obama era, they're Obama era leader. That's why. And there's still a few of them left.

Right. But a majority are not at Microsoft anymore. And so I think that the biggest difference I see, frankly, is that ballmer, I think in his leadership style, perfectly encapsulated 20th century management principles that view the world and an organization as a mechanical system that you can control. Right. The way that you would, any kind of mechanical system, you can control it.

And the fact that there's people in there, well, there are kind of cogs in that system, and they're getting paid, so they should do what they're being told to do. Right? And I would say that Satya's approach is probably the best example. I know. I know of viewing the organization as a social system and saying, because when he first called Joe Whiting Hill, who at the time had been in charge, charge of mergers and acquisitions, and he brought him in and said, I need you to be a core part of this new people strategy that we're going to be developing.

And we need a new business strategy, a new technology and a new people strategy. I need your help with the people part. And so he elevated people strategy and designing for their culture at the same altitude as technology and business strategy, which I think most organizations unfortunately don't do. And so they think of culture as fluff or extracurricular in too many cases. And I think that's really one of the biggest differences, is that decisions being made along the way, even, for instance, at a point where, okay, we have this opportunity to do something with facial recognition that would be extremely profitable, that kind of violates the trust that we're trying to build in the market, and we don't really believe that's a good application of technology, so we're going to say no.

And so the way that he transformed sort of starting at the leadership altitude and then came up with psychology and neuroscience based principles that Joe Whiting Hill and Kathleen Hogan and the HR organization developed are, I would say, the fuel that made the great technology talent. Because it's interesting to me, because when you think of 2014 and you look at Microsoft market cap at the time, you look at IBM, you look at Oracle, there's many organizations that probably, you could say, had a similar amount of talented technology people all at the same time. And yet one raced ahead. And the big. I can't speak as much to Oracle, IBM and other tech companies in terms of their culture, but what I can say is Microsoft, there is that sort of secret sauce that I think was really the balance of those three pieces of strategy development.

John R. Miles
Thank you so much for that. And it makes me think, why don't these large companies put more emphasis on their people? For instance, before I went to Dell, a company at the time when I was with them had 150,000 employees. I worked for Lowe's home improvement, which had nearly 400,000 employees. And if you think about that and who makes the biggest impact on making happy customers?

It's absolutely the employees who are on the front line. In fact, our CEO at Lowe's would always say, at headquarters, we don't have a cash register. And therefore, we spent a whole lot of time, money and effort trying to train those on the front lines to understand the processes, the technologies that were rolling out, and how we wanted consistent customer service to be across the company. And at first, when I got there, even though it was a Fortune 50 company, it still felt like you were in a medium sized, family owned company. You would literally walk down the halls, and I'm not kidding you, about half the employees who would pass you were wearing some type of branded Lowe's apparel or something that had to do with the Lowe's racing team.

There was just this magnetism and pride about being a Lowe's employee. And that started to shift as the company switched its headquarters from Wilkesboro, where the company was founded, to Mooresville, which was a town just outside of Charlotte. About that same time, our CEO, Robert Niblock, had a death threat that went against him and his family. And so they ended up bringing in this complete security force to protect the senior executives, including a number of former military people and secret service officers. And all of that ended up up being a huge shift that impacted the entire culture of the company, because what happened was you would typically see all these senior executives walking the halls when we were in Wilkesboro, but when we moved to Mooresville, they tend to just sit there.

And when we moved to Mooresville, instead of walking around, we were more summoned to the area that they were at because of fear of security and other things going on. So it changed the whole dynamics of the company. And then when I went to Dell, it was almost night and day out of all the times I walked the halls. You would be lucky to find one person out of thousands that you would interact with in a day who was wearing a branded piece of Dell's apparel. Wow.

I mean, I really saw it. And just to see the difference in these two companies was so enlightening. Well, enough about all that. What I wanted to talk about is you were very well known for advising Fortune 50 executives on artificial intelligence strategy, and I wanted to come at it this way. There have been some really interesting studies that have come out of MIT and Oxford about how automation and AI is going to cut about half the jobs that are currently in existence over the next 20 or so years, as well as Thomas Frey's prediction coming out of Google that they're going to be about 2 billion jobs.

They're going to be automated by 2030. With all that as a backdrop, I'm sure many of the listeners who are tuning into today's episode are very worried about their future careers, especially if they're midterm into their career or if they're just starting their careers. What strategies would you suggest listeners start adapting to successfully navigate the shifts in the landscape that are only just beginning? It's a great question, and those are dismal sort of figures that are being put out there. And one thing I think that often is that I've been seeing take place a lot that's been troubling for me is that I think that we often merge in our mind, in our mental model.

Brian Evergreen
We merge tasks and jobs. As one thing. Say we look at the number of tasks in a given job and we say, okay, if those are the tasks that make up that current job and we can automate those tasks, therefore that job is going to go away. But if you think about, for instance, right now, a social media marketing manager might be doing these tasks, and these ones can all be automated, but, like, are you going to put a machine in place that just automatically posts regularly based off of a trend, combined with a few different business rules and generating an image and text and then just posting? I don't think so.

I think you would still need the human to be looking at and thinking through, because if you do that, but it's sort of like driving to the bottom line, then all social media content is suddenly going to be exactly the same from every company. And the ones that apply a lens of sort of a human that putting in that human magic that only we have are going to be the ones that stand out as opposed to everything else that drives to sort of the same kind of the new standard. And so I think that tasks and jobs I like, I always suggest that people decouple them is the first thing I say. Second is that if you think about, like, at the time that cars came out, right, there were a lot of people that had jobs driving horse and buggies and training and grooming those horses, but then also making the buggies themselves, engineering the buggies, et cetera. And you could say, well, shoot, now that cars are coming out and we can see this rise from thanks to Henry Ford's sort of factory model, think of all the jobs that are going to be going away.

And it's interesting because if you look at it now, you can kind of see, well, engineers that were working on engineering buggies could switch to cars, and drivers that were driving buggies can now switch to driving cars. And so I think it's going to be similar where if you're someone who's currently doing a highly, there will be a natural kind of shake up of the market. There will be times, I'm not saying there will not be job loss, especially in the short term, but in terms of the overall economic outlook, I think what's going to happen is that we're going to have people that are doing one type of job with one set of tasks today still doing something within that function, but they're able to do more with less that one person or that group of people are creating even more value. And what it really comes down to two things. I want to answer your question, but I first want to say it comes down to your leadership within an organization.

So if you have a type of leader that is, that you're working for, that is looking for ways to cut costs, and that's their main outlook, is we always have to try to drive down costs for shareholder value. That leader, regardless of how good the technology is going to experiment with letting people go. And yeah, they very well may try to replace your job with some degree of AI plus automation. If you're working for the kind of leader who says, I want to figure out how we can grow top line revenue so we can create more value in the market, more new products with the same number of people. So we're going to augment the people that we have with technology, but honor that and the legacy and the culture that they bring, and how do we empower them with all these new tools, tools to do even more.

If you have that kind of leader, you don't need to be worried. I think in terms of the type of leader you're working for, I think is a bigger question than what the technology is capable of. And then in terms of answering your what should people be doing? What I would say is double down on the things that people do best. We're really good at a linear thinking.

We're really good at envisioning the future and trying to ask questions like what would have to be true for us to be in this future? And we're really good at problem solving and not just doing the same thing repetitively. Right. And also we're good at building connection and meaning and answering the question of why something should happen. Machine might be really good at doing the what, but we're really good at figuring out why and coming up with a plan on why we should do something new that maybe we're not doing yet.

So I'd say that if I were a young person entering the workforce today, I would be thinking through, what is it? The unique where the across any field that I'm interested in, if I'm interested in marketing, if I'm interested in finance, if I'm interested in any given engineering, let's say I would think through, okay, based on these tools, if I'm looking at these sets of tasks that these tools could likely automate, I'm going to double down on the deeply understanding the discipline that I'm in and trying to find ways to maybe leverage those tools to be able to bring a new type of value for me. It was creating a sharepoint workflow. When I first joined Accenture, the first project they had me on was a data entry project, and I realized, oh, theres this sharepoint workflow thing. I automated 60% of what that team was working on or so, and then that opened up doors for me to go work on the next thing.

Id say that if youre entering the workforce now and youre wondering, okay, what do I do? Whatever team you're put on, even if it's a really transactional job that you're initially put into, if you can have even the most low fidelity, simple vision for even just the next step of the future, that is going to be leveraging some of these new technologies, that's more than the average person seems to be bringing when they're entering the workforce, and that you can already start to gain traction and start to move in a direction where you're adding a unique value that no one else is bringing. This episode is brought to you by AARP. Ten years from today, Lisa Schneider will trade in her office job to become the leader of a pack of dogs as the owner of her own dog rescue. That is a second act made possible by the reskilling courses Lisa's taking now with AARP to help make sure her income lives as long as she does and she can finally run with the big dogs and the small dogs who just think they're big dogs.

AARP
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John R. Miles
Brian, I'm going to ask you a follow on question to that. So going back to your experience at Accenture and now fast forwarding. Until today, Accenture has been really someone who's been highlighted as turning to AI and seeing it as an advantage to how they can propel themselves forward. In fact, they're doing it without displacing employees, meaning they've looked at areas such as data entry, other areas like manual computation, and they basically allowed AI to start taking a bigger role in doing these tasks. But the people who were previously doing the tasks, they've now sent them back for furthering education, to have them sitting on top of all the results that AI is spitting out and analyzing them and providing value added services to them.

However, to your point, Brian, there are going to be some leaders and some employees who aren't going to want to go or support that direction. So my question would be, are there certain job categories that you view as low hanging fruit for AI, automation or replacement? And how should employees, if they're in one of these sectors, start preparing for these pending shifts? Yeah, thats a great question. I think less about job category and more about how repetitive is the work that youre doing and extremely repetitive.

Brian Evergreen
And then thats usually the first thing that when consulting firm comes in and says how can we try to cut costs, they look at whats repetitive and can we have some kind of automation do that instead? And so ID say its less about like a specific category, like or business function, like HR versus marketing versus finances or engineering. I wouldnt say its that, ID say its more about the actual job that you're doing, how repetitive are the tasks in that job. And what I would say is that if you're worried about that, what I would be thinking through is because if you think about any given organization, maybe the job you're doing right now is very repetitive. So let's say you're in a customer service organization.

Like there's been recent news about some layoffs in that space. And so if you're a customer care agent and there are experimentations taking place with using chatbots to handle those types of things, then I would say maybe one you could think about ways to upskill to try to move into a new career path if you're really concerned or depending on the type of signals you're getting from your leadership. The second thing I'd say though is if you think about the goal, like if you, instead of thinking about the set of tasks that you do and how could you do those even better so that you're replaceable, I would think more about like what's the goal of from a customer service perspective, what's the goal that our organization is trying to drive toward. I mean, we want to delight our customers. We want to resolve their issues quickly.

We want to ideally not keep them on the phone for too long. If you think through those kinds of things, who better than the people that are on those phone calls to know where the roadblocks are to being able to do that, right? And so you could literally put together, it doesn't have to be fancy. You could put together an email where you're like, hey, here's something we could do. For example, when I was working with Microsoft on customer care, we realized that, oh, where people are googling, these care agents are actually googling the answers or binging the answers to try to find things that have been put out there by the Microsoft developer community on how to solve these office 365 problems.

Then they're reading them, hoping that it works, and if not, they go find another one. And we thought, well, that's not the most efficient way. So then we had an idea. We said, what if we had a Pinterest, like where once you find one of those answers that then the customer says, that works. Thank you so much.

Great, I'm going to pin that. This worked for this customer call. And then other people can come find that when they're searching, they're coming there first instead of to Bing or Google. And then they can upvote if it works for them too. And now you're starting to create your own internal better knowledge repository than you had before.

Well, you could wait and hope that leadership comes up with something like that, but the customer care agent could very easily, even though it's not technically in their job description, they could say, we could really use something like this. And I'd love to try to help create the plan for that and maybe project manage the finding of the right, either product that's already in the market or consulting firm that's going to help us to do that. And that could be, that's just one very small example that could be anywhere, across anything. The people that are in the work doing the transactional things that are the most ripe for some kind of automation, also know where all the biggest pain points are, which are usually very big opportunities for creating more value for customers. Yeah, Brian, thank you so much for sharing that.

John R. Miles
And the reason I asked these different questions was to set up the rest of our discussion and also because I know they're top of mind to my listeners. Today we're going to be discussing your new book, which came out last year called autonomous transformation. And there's a copy of it sitting right behind your shoulder if you're someone who's viewing this. For the listener who might not be familiar with it, Brian has won some incredible recognition, the first being a must read for the next big Idea club, which is curated by Adam Grant, Malcolm Gladwell, Susan Cain and Dan Pink. And it went on to becoming one of their top 50 business books to be featured for the year.

And then Brian was also a finalist for the Thinkers 50 award, which is a really big deal. And you were actually there with a couple of friends of mine, Wendy Smith and Marianne Lewis. It's a profound recognition that comes only every other year. So as I was exploring your book and reading the introduction, I noticed that you start off by asking a whole bunch of questions and then you start unraveling them. One of those being why only 13% of AI implementations turn out to be successful.

Can you go into some of the other questions? And what piqued your interest so much in this space? So I was working in AI strategy for Microsoft. I was the USAI strategy lead and I was flying out to meet with Fortune 500 C level executives to talk about AI strategy. And it's sort of a loss leading function for Microsoft is saying, okay, if we can help you create a vision to transform your market and then develop a strategy for doing that where we're not talking products, we're just talking strategy, then we get a few different valuable things out of that as Microsoft one is, then we get to propose back the ways that we're going to help you achieve that now with our existing product set.

Brian Evergreen
And the other way is we're getting feedback on where the market's headed and what kinds of things we should be incubating or developing into our product set. When I was having those types of meetings, it was very interesting because coming from the tech centric and consulting centric mindset that I had at the time, I expected the conversations to go differently than they went. For example, one of the first questions that almost inevitably happened every time was something you've already brought up was what about jobs? What are we? How do we, what's the future of work?

And another one was, well, what does it even mean to be human in this a meeting with c level ctos, CIO's, CEO's and them asking what is it going to mean to be human in ten years? It was not something I expected to be asked as a Microsoft strategy lead, as well as how should we be designing this workforce? Transformation is another example, or what is from an ethics and bias. There's all these questions that didn't exist when you were looking at whether or not to move to the cloud. When you're moving to the cloud from an on premise data center, the questions are, capability, cost, change, management is pretty simple.

You don't have to think about ethics or bias. You don't have to think about pr concerns the same way. And so I collected those questions, so to speak, along the way of things that people were asking. And then that sort of grounded the research when I, because I felt like everyone was talking about digital transformation like it was the ends as opposed to the means. I would always joke, they'd say, yeah, we're on a digital transformation journey.

And I'd say, oh, great, what are you transforming into? And to often blank, oh, I hadn't thought about it that way before. Right. But the purpose of transforming is to go from one state to another state, right? That's why we transform.

And furthermore, digital, getting something digital doesn't necessarily, to me, that's just the opening. It's not the end game of, from a chess analogy perspective. Right. I thought, well, what's that next phase beyond digital? You've gone from analog to digital.

Now, what? And the real promise, I think, of AI is that you can go from digital to autonomous to where systems can make decisions without humans in the loop. And so anything that's highly manual and repetitive, that, and I don't mean physically manual necessarily. I just mean that there are certain areas where, okay, we can augment our people by them not having to think about that anymore. Like, a great example is dow chemical used to have to stop production, drain their chemical vats, have people put on hazmat suits, go inside to inspect them, and then once they finish the inspection, come back outside, then start the production process again.

That's expensive. That's dangerous to people. Now they can just drop a drone in, and the drone will just autonomously scan and inspect, and then they're actually saving money, and the people are, it's safer. And no one's jobs went away. There's just one less thing that is on their plate that they used to have to do that they don't have to anymore.

And yes, that's sort of where I started from a research perspective in approaching the book. And I think probably one of my biggest ones was, okay, I have all these people that I've met that are trying to do innovative work, whether it be something to completely change the world, something to change the market, even just something that they think, wow, this would be a real breakthrough. And they keep, there's sort of a systemic condition of their organization is stopping them. There's basically no way around it. So what would have to be different about the way that we do strategy and the way that we plan that would change that?

That would make it so that rather than the really innovative things that take place, being the exception, how do we make that the rule of a given organization? That was a big question. That was kind of one of the grounding of my research. Thank you for sharing that. And during my time in technology, a field that I've been in for about 20 years, I remember people would always come to me and say, why do so many transformations, regardless of what they may be, end up failing?

John R. Miles
And I always tell them it's because everyone thinks that the technology implementation is going to work all these wonders and they end up putting all their eggs in one basket, which is the technology solution. When what I have found out throughout my career is that it's only about ten to 15% of the overall equation, and probably 30% to 45% are process overhauls. And your biggest equation is changing the hearts and minds of the employees and reshaping the culture that we talked about earlier. And a really key point about this transformation is making these employees see how they fit into the solution and how its going to make not only their jobs better, but their life better. And if you cant do that, why would anyone want the solution to begin with?

And from what I have found throughout my career, what ends up happening is that third quadrant, the change management aspect, is where companies end up spending the least amount of their time, to the point that it often becomes almost an afterthought. And I thought that that was one of the key reasons that I see so many implementations fail. And one of the things that I like that we did at Lowe's, when we were rolling out a new solution into the stores, we would always start with just one individual store. We would let them play with it for a while and gather all the feedback that we could from the people who were actually using the solution. We would then introduce it to a second store in a different part of the country, then evaluate if we were getting the same feedback or not.

And then we would take it out to a number of stores, maybe throughout a single district, make changes, then take it out to a region, make changes before we ended up rolling it out into the entire chain. What I liked about this is we were putting out a solution, and the developer who's making this understands some aspects of the job, but they're not the ones who are doing it. So by slowly rolling this out, giving the users input into what was working and what wasn't, it actually made the product so much better because the end user had input and ownership over it. And when it was released, it also had buy into it, because even if they weren't part of the initial launch, other store employees knew that their peers had been significantly involved in its creation. So that's a long way for me to getting back into your book, where you introduce in part one the fundamentals, and one of the sub chapters is titled weaving our way to the moon.

Another one is job protectionism, job fatalism, job pragmatism. And my question for you is this, if we're starting out with the basics, Brian, could you explain the difference between inflammation, transformation and creation in the context of autonomous transformation? And how do these concepts more importantly pave the way to a more human future? Alongside AI, transformation is the process of transforming states. So you're starting in this state and you're transforming into another state.

Brian Evergreen
So a great example would be a caterpillar, right? Transforming into a butterfly. Right? So that's transformation. And when I set out to define autonomous transformation, which is moving, transforming your organization, the value that you bring to clients or to your customers in the journey of moving from analog or digital to autonomous, I knew that was what I wanted to put out there in the world as, okay, that's autonomous transformation.

But what I was worried about was that everybody would think, well, because digital transformation has come to mean anything that gets plugged into a wall. And so I thought, okay, I need to add more clarity to digital transformation so that there's cleaner lines between digital transformation and autonomous transformation. So I looked in and I thought, well, what about all the initiatives that are taking place where we're going from analog to digital? Yes, but nothing's being transformed. It's the same process, it's the same value being created, but it's being created more efficiently.

And so what I actually started with the definition in this case and worked backwards to reformation, which is funny, because I think when most people hear reformation, they think of the Protestant Reformation, which is actually really more of a transformation of society. But by definition, reformation is to improve something without changing the nature of it or structure of it. In other words, not transforming states. And so what I did is I put in this two by two, like a good consultant, digital reformation on the bottom of moving from analog to digital transformation. Above that, and then on the other side, you have autonomous reformation, which is what I would say Amazon is doing with their robotics and their warehousing, it's the same process.

It's just more efficient now that we have robotics doing it right, and then autonomous transformation being, okay, we're moving from the digital or analog paradigm to autonomous, and we're going to transform the market, we're going to transform the value that we're creating. Unfortunately, I don't have a great example of that from an enterprise perspective. The best example that I've seen so far is from the consumer side, which is the rabbit r1, that's saying, okay, we want to transform the way that people experience. I mean, the Internet, for lack of a better phrase, we want to make that so that you can just talk to this little device and instead of pulling up your phone or computer and going to Uber Eats and clicking the 15 buttons to get the same takeout that you've been getting off and on for years now, instead just being able to speak to a device saying, yeah, get me my favorite thai food. Yes, I'm at home, and maybe it already knows you're at home, and that's it.

And I'm not looking at any screens anymore. Or, hey, I need to catch an Uber from home to the airport tomorrow at 06:00 a.m. being able to just do those kinds of things without needing to look at any screens sort of transforms the way that we as people are experiencing things that we've come to rely on for our day to day life and then creations. To transform something means you have something, you're transforming, right from one thing to another. Reforming means it's the same thing, but you're going to make it better and more efficient.

And then creation is when you look at what you want to do in the market, let's say you're in the energy sector and you want to do self generation, that the deregulation is happening. And you say instead of clinging to lobbying for more regulation so that we can continue to operate the way we've been operating, what if we became first to offer a truly incredible self generation option for the existing states that have been deregulated? We could test it in developing countries, et cetera, et cetera, right? That would be an act of creation. So you're not just taking the existing grid and trying to reform the grid, or you're not even trying to transform the grid into a new kind of grid.

You're saying, I'm going to create something new that doesn't really exist yet and give people a viable path for self generation that could. Theoretically, maybe there's a future where we don't even need a grid anymore, and we're going to create that. Right? So that'd be the third piece of it. So when I think of transformation, I think of something that's fundamentally changing the nature or composition of something, but reformation really means something different.

John R. Miles
It's where this composition isn't necessarily changed. It just becomes different, maybe even more efficient. Is that what you're describing here? Yep. So transformation would be like what we've seen with Uber and creating the gig economy is like transforming, and Netflix is transforming entertainment, right.

Brian Evergreen
So we're having these kind of transformations of the market and of the way that we just experience life as people and as consumers, and the ways that enterprises are even coming up with new business models based on these things. And then, whereas Expedia, I think, is a great example of reformation, where you were having to go in person to a travel agent or call them, now you can just do it on your phone. It's way faster. It's so much more efficient. But it's essentially the same process of selecting a flight and looking at what times you're going to go and how much it's going to cost and which class you're going to be in, and then booking it, and then going in person and checking your bag.

The checking the bag process is more efficient because of digital tools, but it's still essentially the same process. It's just faster now. So that whole. That's a. I think the travel industry is a good example of.

Of digital reformation, and I'm grateful for it. And reformation. I think sometimes people take digital transformation as a badge of honor. And then I think by adding reformation on to make sure people don't think that I'm saying that one is better than the other, they're all means to an end. From where you're starting, you have something you're trying to do, some kind of value or new value you're trying to create.

You might be in a spot where you just need to focus on reformation because your profitability is off and you're facing a recession like reform. You might be in another spot where you say, you know what? We have enough margin right now, and we see the climate of where things are headed, and we think it's worth it to go try to create and perform an act of creation, do something that doesn't exist yet. Or we might want to try to look at digital transformation, autonomous transformation. They really.

Instead of starting with saying even how you want to transform, though it usually has to do with that. The process should start with, what's your goal? What's the future that you want to be in? And then working backwards, those all become a stitching together of means to that end. So it might be that you have a data set over here.

You're just going to reform because you need it as the foundation for this thing of digital transformation that you want to do. So it's also not just one overarching transformation. In reality, it looks more like many different little steps along the way that could theoretically be sort of tagged with each of those different labels. Brian, I appreciate that explanation, because I really do think it sets the foundation for everything else that we're going to be talking about today. Something that we both also have in common is we both have a coveted endorsement from Seth Godin.

I didn't know you got Seth Godin's endorsement. That's awesome. Not only that, but when I wrote my book, besides my agent and my publisher, Seth was one of the first handful of people who had actually read it. And I remember sending it to him. And I have to tell you, Brian, I was absolutely scared to death, man.

John R. Miles
I thought I had such a fear of rejection because, man, everyone knows Seth knows how to write books. And I also know he doesn't do many endorsements, but he came back about a week later and said he absolutely loved the book. Can I please be your lead endorsement? And I'm just telling you, man, it, like, hit me in the heart. And I think a reason why he agreed to do the endorsement is because my book is really about how do you create a significant life?

And it ties into his latest book that he wrote called the song of significance. And Seth is one of only four people that I've had on this podcast, twice, the others being Gretchen Rubin, Robin Sharma, and Arthur Brooks. So he's in some very good company. And the last episode that we did was about that book I just mentioned, the song of significance. And he's really advocating that approach to the workforce.

And so he and I are advocating for something in a similar way, but with different audiences and in different ways. But we're both trying to help people create lives of significance. So when you think about that and embracing uncertainty and what it means to be human in the realm of AI, how do you define what it means to be human in this context and why this pain of uncertainty, capability, and consciousness are vital? So the first thing that I'll say is that, counterintuitively, the way that you get more value out of your machine starts with your. How you treat and work with the humans around you.

Brian Evergreen
And so I think a lot of times people think, well, we're going through this digital transformation. We have these deadlines. I need you to just do the work right? And they don't bring people along. They focus on tactics.

Experts, they think. Or we have this thing I call data science, Taylorism, where they say, okay, I don't need to talk to your experts. We're the experts. We're the data scientists. I just need the data.

We're going to redesign your process for you, which sounds a lot like taylorism, just in a new form. Casey, Brian, hold on just for a second. If I can just break in here for a second. If a listener doesn't understand what Taylorism is, it basically means that you break things down into tiny steps, and then you focus on how each, each person can do his or her job against those steps. And the best way possible is my 101 of it.

And Frederick Taylor was kind of the first management consultant. And the process was that they would come from the outside, they would document. There'd be like 20 people working to build this widget, let's say, on a line, and they would document how each of those 20 people was doing it. They'd be using stopwatches from the outside. They themselves were not making anything, they're just consulting.

And they would then document that they would come up with the best way that it should be done. And then they would work with the management to then teach everyone else how to do that perfect way that they've designed. And so that there's this paradigm of management working with this outside expert who knows everything, but they actually don't know anything because they've never done it before. They're just observing to come up with a better way. And now, if you cast that forward to today, the outside expert coming in that has never even walked to factory floor, for example, but is saying, you just give me all your data.

The data is going to tell me everything I need to know to automate this thing or to do something better. And it's often a failed premise. I mean, that's why I think 87%, or I think the most recent Gartner one that I saw is 85% of AI initiatives are failing. And I think a big part of it has to do with this breakdown between people, between if you have the technology people and the industry people or domain experts, and then you have business leaders, and they all have different training, they're all extremely bright, and often a lot of the energy that's being, that could be spent creating value for customers ends up getting spent strategically, vying for purchasing power and trying to get their way bought in, get buy in for their way so that the people will follow their plan. And I think that the way that we as humans are working together is getting in the way of getting value out of our machines, so to speak.

And so I think that to me, if we start with saying, okay, not only is this going to be transforming the thing that we're trying to do, it's like a little bit like a band, I guess, is another way to put it. People focus a lot on the outcomes that they want, and they focus on bringing the right experts together in a business. They'll say, okay, we have this many data scientists, we have this many process experts, we have this many right. And they think we've got all the right experts. And I've seen this firsthand because of my work at Microsoft and working with many of the world's leading companies.

You've got no shortage of experts. You've got no shortage of resources. But it just keeps not working. I describe it like, if you had a band that you're going to put together, you're trying to put together a concept, and you say, okay, this new band that I'm constructing is going to have all the top experts. So it's got John Mayer on guitar, and it's going to have Beyonce as the lead singer, and it's going to have will champion the drummer from Coldplay, and we're just going to throw him on stage at to a sold out stadium.

Let's say knowing those experts, I'm guessing, would be a heck of a lot better than amateurs in trying to improvise and create something meaningful. But it would be a lot better if we first had those people and figured out first if they can even work together and then let them jam and find their sound. And then once they found their sound, then they can start writing albums and they can do that kind of stuff outside of the context of being on tour. And I liken it today, a lot of us as leaders, every day that you show up and you've got a solid block of meetings is like you're on tour, all of your creative energy is being spent. And so you don't have a lot of creative energy left for envisioning the future or for even solving anything and speaking in time, to be able to break away from that and be able to even focus on the emotional culture of your organization, on the relationships.

Because an organization is fundamentally a social system. It's not a mechanical system that we can tweak little a dial here or there. It's a social system. And so the relationships, even that these different experts have between each other and with their leadership and also with why they're doing what they're doing, make a huge difference. You could have.

And that's one reason that you can have the same experts within one organization not producing much value. They leave, they go somewhere else, and they absolutely crush it and do these incredible things. And a lot of it has to do with the systemic conditions and the culture of the organization that have either been designed or not designed, and therefore sort of just naturally falling where it may by leadership. And so the core, when we think about strategy work, we often think of it as this cold, numbers driven. But to me, it's the, in truth, it's much more creative of like art, where we have to think through the why of what we're doing, and that why being conveyed at all levels of the organization, I think, makes a critical difference for each person.

Contributing and feeling value in what they're doing and meaning, is going to make a significant difference in whether or not the initiative is successful. Brian, thank you so much for explaining that. And one of the things that I think is so important is that the day to day practices in business really need to be reevaluated, not only to rehumanize them, but also, if you think of what Wendy Smith and Marianne Lewis were talking about, to start using both and thinking to extract greater value from the machines that were all now operating. And one of the things in my leadership roles that was always such a huge burden was taking on the maintenance of outdated systems. And often we would talk about this in terms of repairing spaghetti architecture, or you could call it the accidental architecture that ends up compiling over time, as you make more and more incremental changes into these systems, and then they end up becoming almost an unmanageable mess.

John R. Miles
So, Brian, how can we embrace these advanced technologies to break free from these old systems that so many companies, like the ones I was with, are using? I love that question. And I'd say, the first thing that I would say is that if I asked you how do I make an ATM system better, the first thing that might come to mind for you. I don't know. You can tell me if I'm wrong, John.

Brian Evergreen
But for the most people, I think the first thing that comes to mind is, well, I would need to talk to someone who builds or designs ATM systems, whichever engineer does that. How do you make that system better? If I said, what should the ATM experience be? Well, now anybody can answer that question, right? Because it doesn't require knowledge of the existing system.

You're thinking more about the experience, right? And so I think a lot of times organizations get stuck because they start with the question of, here's our existing system. My goodness, how are we going to make it better? And there's like maybe two people that understand the whole thing, if that. And then there's lots of people understand they're one part, and then that's their whole job is tied to maintaining that one part.

And they're defensive of it and they want to spend all day trying to explain all of it at the very technical, domain specific altitude to other people. And then you end up up sort of just in the quagmire, so to speak. You're stuck. And so there's this great exercise that a leader at Bell Labs did in the fifties, and John, you'll recognize this because it's in the book where he said, the telephone system, the us telephone system went down overnight and it's irreparable, we can't fix it. And his leaders were looking kind of confused.

They looked between each other because they thought, well, wait a minute, we just used the phone this morning and all that, right? And so he said, hey, anyone who doesn't believe me by noon is going to get fired. And then even more confusion and intrigue from them. And he said, pause. Put that on pause for a minute.

I want you to think about the greatest were bell labs. We were just awarded with the top industrial laboratory, research laboratory award. So what are our best inventions? And they, what are our top three inventions I can give them now? So one of them is the coaxial cable.

The ability to thread multiple calls through a single line was one. And he said, great. When was that invented? When they first come up with that and, well, in the late 18 hundreds. Great.

And then when did we implement it? And I think it was the thirties or something. They said, okay, and now what is another one? Well, the transatlantic cable. Okay, well, that was invented and implemented in the late 18 hundreds.

And then he said, okay, and what's the last one? And it was the dial on the telephone, which was invented in the late 18 hundreds and implemented in like the twenties or thirties as well. And so then he joked and he looked around and he said, what in the world have you all been doing? Right? Most of those inventions happened before these people were even born.

He said, I'll tell you, it's not your fault. You've been maintaining the system. Any change that's been even brought up as an idea is first look through the lens of, is that possible within the system we have, or looking at scaffolded systems saying, well, if you think about like an electrical grid, for example, if you start thinking about any changes to a grid, you think about all the mission critical operations that are taking place in hospitals, data centers, all these things that rely on the current way that we're being supplied with electricity. So the idea of making any changes is terrifying. Right?

And so, of course, you're not going to make significant changes. And so he said, well, the reason that I first brought up, going back to his original point, that the telephone system was destroyed is that I want you in the next, I think it was a year or nine month period, we're going to be going through a series of exercises to imagine the future of making phone calls, so to speak, outside of the system of the existing. We're not going to talk about what's existing. We're just going to talk about what, what should you be able to do when you're trying to make a phone call? What would be amazing.

And one of the things that came with it was, well, it'd be amazing to know who's trying to call me because right now it's just I pick up for everybody because I never know. So it'd be great to know. And so they came up with the ability to see that on a phone, and it'd be amazing to be able to, because when you're spinning the dial, right, you're not able to, not always able to be precise. And so they came up with the touch tone phone. Right.

And then they also came up with, it'd be great to make a phone call from everywhere. What would have to be true to be able to do that? And they came up with the foundation for what is cellular technology. And there's so many things that came out of that one little exercise that I think is such a great case study for. If you're starting with a system where you have a Frankenstein or a spaghetti architecture of all these different systems.

Yeah. If you're starting with that lens and saying, how can we make this better? How can we rehaul it? It's impossible. But if you start instead with saying, okay, what would the, based on the value that we're bringing to the market and all the operations and all the functions that we have right now, what would the ideal supporting technology stack look like then?

What would it take to get from here? To there? And are there certain workloads? We can just build the new, fresh tech, debt free architect piece of it here and put that into production and give that functional group this tool to help them, and then go one by one and sunset. The older things that weren't working before that would never have been able to be transformed because they carry so much tech debt and they're so interstitched with everything else.

That would be the way that I would think about that. And I think that because true transformation sort of does require starting with that question of what is it that I actually want? And if you start with what you have and you try to solve problems within what you have, you'll forever be caught in a cycle of maintenance mode. Brian, I love that answer, and thank you so much for it. And my next question, I'm going to throw a curveball at you.

John R. Miles
The curveball is, I'm going to combine questions on you. I love chapter six where you discuss the problem of solving problems and you introduce this concept of future solving on this program. I love to talk about the concept of crafting your future self and how so many of us live in this gap where we're measuring ourselves against some unrealistic idea when we're trying to problem solve our own way out of being stuck instead of looking at the gains that we're incrementally making. And so I love this concept of future solving. Then, as I went further into the book, you also go into the concept of being data driven, which I experienced very much in the different roles that I was in throughout my career, because we were trying to compete on data, or as you say, the need to be data driven.

And to me, future solving and being data driven connect with each other. And I would ask, Brian, do you see the same thing? Oh, 100%, yeah. So future solving, to me, is the problem with solving problems is problem solving is the craft of getting rid of what you don't want want. And you naturally look at the lens of, okay, what don't I like about what's working and how am I going to solve that problem?

Brian Evergreen
And it's another thing that keeps you in maintenance mode, right, where you're not going to have breakthroughs if you're just solving problems. Even though I think the pervasive thing that is being recommended in conferences today, if they say, where do we start? They say, well, start with picking what problem you want to solve. I disagree. I think you should use a construction example, because my dad was a general contractor, so I grew up with a tool belt around my waist.

And I love that's such a visceral, I think topic. So if you think about being in a home, if a pipe bursts in your wall and there's water flowing, that's a problem that needs to be solved immediately. You need problem solvers that know exactly how to get in and fix that problem. If you're instead trying to think through a home remodel, the way that I call it tool worship, the way that people that are in kind of this realm of tool worship would think about, that would be, okay, well, let's pick a tool, how about a sock? And let's walk through the home and figure out how we're going to make the home better.

Let's pick some low hanging fruit use cases that we're going to use with a saw to make the home better. And I think that's also naturally a problem solving, ineffective way to try to be inventive or innovative. And so if instead you start with future solving, which is saying, what future is it that you want and how do you solve for it? And so in the home remodel example would be, well, I want more counter space. That's not because I'm trying to solve a, a counter space problem.

There's no burning platform. But my experience would be better if I had more counter space. What would have to be true for me to have more counter space? We have to architect it. We have to come up with a plan.

We have to come up with a budget. We have to check with safety standards and codes and submit something maybe to the city potentially during none of that process. Are you talking about which tools you're going to use to do the work that comes after you first, just focus on the future you're trying to create, whether it's a more counter space or a bigger shower or whatever else. And so that's the first thing, is the future solving to first half your question, and then the second is being reason driven. So being data driven has become unscientific in practice.

In theory, it's scientific because there's data involved, and so there's a sort of correlation and feeling that it's scientific. But in most organizations today, what we've done is we've said the scientific method being asked questions, form hypotheses, conduct experiments, analyze results of those experiments, and then draw a conclusion. Right. And instead, what we do is we ask questions, form hypotheses, analyze results of investments we've made in the past, things we got from Gartner and IDC, draw a conclusion, which is our investment decision. And then we begin the experiment.

But instead of calling it experiment, we say we've proven how long this should take, what the ROI should be, and we're going to tie your performance to it, which by the way, is not a very human way of working and it's a recipe for failure. And so being in a systemic condition where you have to prove in advance the return on investment with data for something that's innovative is an absolutely failed premise. Because the only way I would have data that something would work is if someone else already did it and I was able to get data from them on how it worked and what it did for them. So therefore it's not innovative. With each new organization today getting a WordPress site, I know exactly how long that's going to take and how much it's going to cost because it's been done so many times.

But if I'm trying to do something that no one, if I'm trying to create a self generating, like that example I gave earlier, and create some kind of option for self generation at the home, I cant really, I can of course come up with addressable market. I can guess, I can come up with a sort of logical why this is worth investing in, but I cant prove it in advance because no ones done it yet. I can prove it once were already behind if you want to wait till then. But if you want to be innovative, we have to start with the discipline of reason paired with data of an example would be nfts. The data said data driven decision about NFTs is invest in 2021, buy as many as you can.

They're all going to appreciate in value because that's what it looked like. The reason driven decision was I don't really see how it's so valuable, even though everybody's buying them and the data is there, that they're worth millions. I'm not sure I'm going to buy them. Let me wait and see a little bit. And so in my case, I didn't buy any.

And I don't know if you did, John, but I always say if you didn't buy nfts in 2021, that was a reason driven decision that you made. And Steve Jobs, when he decided to do the iPhone less than a decade after general magic, had all the right pieces in place, that it should have worked for their smartphone but didn't. And the target addressable market that was generally accepted for the smartphone market was really low. But Steve Jobs thought no, his reason went beyond the data. He saw something and he said, I think there's a way, I think theres something there and its worth investing in.

And to me, the reason driven framework starts with that. The way they merge to your question is that it starts with the future youre trying to solve for. Ask the questions of what would have to be true in order to get to that future and that first level become your theories. And then each theory bubbles down into different kinds of hypotheses of things that would have to be true. And so then the discipline becomes going and proving and disproving different hypotheses along the way to try to create that future.

And to me, it re embraces science in the work that we do, but it also rehumanizes our work, because then, instead of joining an organization and the welcome message being welcome to organization, these are the three initiatives with this much time that we have that we're trying to get this done and this much budget, and this is the next milestone, instead being welcome to our organization. This is the future that we're trying to create, and these are the things we believe would have to be true in order for us to reach that future. And this is the part that we need your help to efficiently prove or disprove this hypothesis. And so then the measure of even of how well you're performing is you're now disproving that hypothesis of something we were hoping would work, as opposed to this should have worked because it worked for that other guy, and now you failed at making it work, and so now we're going to ding your performance, right. So it just sort of changes.

And at the strategy level, the discussion then and now, it's a blind shot of can I get this initiative approved or not? Right. On a given initiative, if you're bringing out this reason driven framework where you come up with all the theories and hypotheses, if somebody raises something that they're not sure will work or not, they raise a new question or hypothesis that adds to the strategy of what you're doing, you add another hypothesis that they just gave you, and now you're gaining momentum in those conversations as opposed to stuff. Brian, thank you so much for that great explanation. You really nailed that one.

John R. Miles
And that's exactly how I also saw connecting the two. So I'm so glad that you and I were aligned on that thought pattern. Me too. Brian, the last thing that I wanted to ask you came out of your next big idea interview. There's a quote from Frederick Taylor, who we discussed earlier around that concept of Taylorism who famously wrote in 1911, in the past, the man has been first.

In the future, the system must be first. He was able to realize his vision, and it's still pervasive today, 112 years later. We can now say that in the past, the system has been first, and in the future, the human must be first. Using that as the last kind of quote. What do you hope readers take away from your book?

Brian Evergreen
My hope is that in this era of AI, that people would first of all see the value that they have as people as venerable. Its not going away. The machines give us new means of creating more value, but they dont take away from the value that we have as people is probably the very first thing I would say, because I think theres a lot of noise in the market saying something else that I just fundamentally disagree with. The second thing I would say is that when you go about creating value in organizations or even just in your own personal life, you want to go do something. First of all, if youre doing it alone, doing strategy thats based on reason is going to be more effective than purely data.

But if youre doing it with other people, the first step is to envision the actual future that you want to create. And the second is to come up with a strategy that is, I would argue, reason driven would be the most effective method ive seen so far to be able to the next step, which is carrying that through and getting other people on board with what it is that youre trying to do. The joke people make is it only takes one person to stop an AI project or any project, right? Just one naysayer and you're done. And so I think a lot of times people keep trying the same way of going about teeing up an initiative and getting funding and then going and executing on the work.

And it just keeps not working. But we keep just thinking, but if I try harder, then it will work. And I would say that there's one takeaway. It's you don't have to necessarily try harder. You might need to try a different way.

And if you try that different way, and if you're thinking from a social, of your organization as a social system, a network of people, as opposed to a mechanical system, which is a bunch of functions that happen to have people doing stuff, then you can design your plan and your strategy in a very different way and come up with win wins across the organization and ground the work that you're trying to do, even if you're a senior executive coming out and saying, everybody has to do this. Because I said so is never going to have the same effect as painting a vision for the future and showing them themselves in that future and why that will be meaningful for them to be there with you. The Antoine Saint expiry quotation if you want to get people to build a ship, you don't buy lumber and start ordering them around. Instead, instill in them a restless longing for the sea. And so I think that the 20th century Frederick Taylor management system of treating people like their cogs in a machine worked really well before we had the distributed workforce.

And the fact that people can work remotely, they can learn any skill online, now they can apply and find new networks online and they can go work other places. The management style that we've inherited from the industrial revolution just doesn't work anymore. And AI plus the social context that we're in today brings all of that to a head. And it's a precipice upon which those who want to be leaders in the future need to make a decision, that they need to change the way that we've been doing management up until now and start doing something that's different and start focusing on grounding in the future. The human must be first.

Me saying that is saying that you start with how am I going to get this group of people to be passionate about passion? Structure your book. How are we going to get them to feel significance in what we're doing and why we're doing it and be able to bring their best selves to doing this. I would rather have people that are connected to what we're doing and have psychological safety and that are one tier of expertise lower than the top experts in the world, stressed out and frustrated by what it is or confused about what it is we're even trying to do. Brian, if a listener wanted to learn more about you and your book, where's the best place for them to go?

Best place is brianevergreen.com or find me on LinkedIn. That's the only social media platform that I really spend any time on. If you want to connect with me, I'm always excited to hear from folks, especially folks that are putting this stuff into practice is so exciting and fun for me to hear about that and always happy to answer any questions. Brian, thank you so much for joining us here today on passion struck. It was such a joy and an honor to have you.

Thank you very much for having me. It's been a great conversation. I thoroughly enjoyed that interview with Brian Evergreen and I wanted to thank Brian Wiley, Hannah Clark for the honor and privilege of having him appear on today's show. Links to all things Brian will be in the show. Notes@passionstruck.com dot videos are on YouTube at both our main channel at John R.

John R. Miles
Miles and our clips channel at Passion Struck clips. Please go subscribe and join. Over a quarter million other subscribers, advertiser deals and discount codes are in one convenient place@passionstruck.com. deals please consider supporting those who support the show. If you want a daily dose of inspiration, then follow me on all the social platforms at Johnr Miles.

And lastly, if you want to join our current movement, then consider signing up for our weekly newsletter titled Live intentionally. And you can do that@passionstruck.com. where each week we post a different courage challenge. Are you curious to find out where you stand on the path to becoming passion struck? Then dive into our engaging passion struck quiz.

Crafted to share the core principles reflected in my latest book, passion struck, it's a dynamic way to gauge your progress on the continuum of becoming passion struck. Just head over to passionstruck.com dot. The quiz will take you about ten minutes to complete and consist of 20 questions. You're about to hear a preview of the Passion Struck podcast interview that I did with best selling author Ryan Holiday. Ryan, who's known for his thought provoking works on stoicism and personal growth, will discuss his latest groundbreaking book, right thing right now.

Good values, good character, good deeds. In this not to be missed conversation, we'll discuss the virtues that make a fulfilled life, how stoicism can address the challenges we face in modern society, and why doing the right thing matters more than ever in today's world. David Attenborough comes always close to the top of the greatest revered Britons of all time. So maybe Winston Churchill is number one, but he is not close behind because all of his work using evidence to show the importance of climate change and its impact on the environment. So why is it, when you see such strong evidence, might people not respond to it in the way that they should?

E
It is because of these biases. And these biases are reinforced by the fact that sometimes climate change is a matter of identity and politics rather than science. So one great documentary on climate change was an inconvenient truth, and that was laden with facts and figures and evidence. But because it was about Al Gore, this made it seem like a Democrat versus republican issue. So even if you're a Republican who's able to understand data and science, and you're generally rational now, your identity feels threatened because you think, well, climate change is something that people like them believe and people like us, we should resist.

John R. Miles
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Brian Evergreen
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Brian Evergreen on How You Humanize Work in the Age of AI EP 462

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1. Introduction

2. The Role of AI in Leadership

3. Human-Centric AI Applications

4. Visionary Leadership and AI

Actionable Advice

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