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Hello, everyone, and welcome to another episode of the Leadership Growth Podcast. I'm your host, Daniel Stewart, along with my brother Peter Stewart, and we are here today to talk about practical tools and ideas to help you become a stronger leader. And so the topic of the day, we all have talked about AI endlessly and heard so much about it. Let's talk today about how to really adopt, how to implement, how to manage this level of change. As so many organizations, this is where you are at. So we want to talk about roles. We also want to talk about a maturity adoption curve that you can assess to see where you're at, where your team is at, where your organization is at. And you'll probably hear lots of change management ideas.(laughing) And yes, this is a change management thing. It's an effort. It is an initiative And yet, sometimes people can think of it as something unique and different. We'll touch upon that. But let's first, Peter, let's jump into kind of the roles of adopting AI for an organization because this is inevitably one of the main strategies that's showing up everywhere. Give us a sense, Peter. What are you kind of hearing? What are you sensing? And then we'll get specific into all sorts of aspects here.-Yeah, no, let's dive into it. I mean, I think first and foremost, the most important role in all of this is the role of user. And any listener at any level, if we are expecting our organizations to be adopting AI, we personally have to be doing so as well. So we need to educate ourselves. We need to help with that learning curve so that then we can be informed as that's rolling out. So that role is a hat that every single leader and listener needs to have as AI user, AI adopter.

-And to reinforce that point: 2:12

So even you and I, as we lead Stewart Leadership, we invest in and we use Claude. We'll just say it. We'll use Claude as our enterprise go-to AI. And we've built that and connected it to a variety of other systems, and so that we can leverage and have confidence as to the level of privacy for our clients as well. But to your point, Peter, and really kudos to you to helping take the lead in many of these things, you've been the champion. We'll talk about that role as well. But to then, that's what we've done from an enterprise level, as well as creating an AI use policy to be able to be very clear on what that looks like as well. So a few of these basic things, but to your point, Peter, it's if you're talking the need, what are you doing about it personally? How are you continuing to challenge yourself, leveraging AI tools so that you have some experience with it?-Yeah, it is. So it's, I think, so there's the personal piece, but now let's talk about kind of organizationally how you help this flood of change roll out. And maybe, since, you know, this is not new. We've been talking about this for a while. It's a way to help dissect maybe where some of these efforts have stalled or they haven't been moving as quickly. You can do that kind of quick little diagnostic as we're running through these roles of where might you be missing something in your organization. I think first we'll chat about four and then dig into a few others as kind of what might be missing. So the four I'll start off with actually come from Ross Hartman, who's CEO at Kingo AI. I was listening to him give a presentation. I thought, these are really helpful. As he just kind of gave them off the cuff. So these are four roles that are required for a successful AI transformation. And then we can dissect it a little bit. So, the first is an executive sponsor. There has to be that individual who is putting forth the strategy, the vision. They have the faith that this is going to be a good thing for the organization. And they have the authority to make the changes to the operating model to help this be successful So you always need that executive sponsor at the top, leading the way, leading the way for it moving forward.-And to build on that, it's a great question as to who the heck that should be.(laughing)-Yes.-And so often, I know you've sat in lots of executive meetings, and they're talking about AI, and inevitably, they all look at the chief technology officer or the CIO or whatever title they're using for the person over the technology side of things. And it's like defaulted, okay, you are the leader, you do this. And I just don't see that working. It's like it's one slice, it's one angle. I often look at it, at AI initiatives, as it's a three-headed monster in some way. You have the person over technology, you have the person over the people, the HR side of things. And then you have the person over the business. And they need to be able to be aligned. Now, ultimately, they might have one of them be that single, oh, I hate this throat to choke. or single belly button. That's a much better way of putting it.-That is a kinder way.-Yeah, but they need to have alignment between these three leaders inevitably to be able to then get enough of a sponsorship to move forward.-Oh, it's so true. And here's the fascinating part as we've obviously worked with organizations for many years. And prior to AI, and this is still happening even in the rollout of AI, think about like an ERP transition or adoption or into a new system. How much effort, how much time, how much planning, how much... how many resources are put into that so that it can go well? I mean, they are just massive undertakings to put in a new ERP system in an organization. Yet AIs come out and it's kind of just, okay, here we go.(laughing) Like, let's see how it runs. And are we really putting the effort behind the adoption? So we need that clarity of the executive sponsor. Often... You got to have the CEO on board. But yeah, it doesn't have to be just that technology-specific person who is that sponsor. Figure out who makes the most sense and who has that authority to make the changes to the operating model for the adjustment. That's a real key part. Because the second part is the AI champion. And this is the individual or individuals who may be designated. They are responsible for helping to diffuse AI throughout the organization. You know, they really are the change management experts. They're the ones who are helping to squelch the AI fears. You know, this is going to take over my job. I don't know what to do with this. This is too complicated. This is just a wave, it's going to come and go like the latest fad. You know, whatever the human reaction is, because they're all very real. And they're important, especially to anybody who's feeling those things. But this individual is helping to be that kind of warm, fuzzy contact in many ways. You know, they might organize the hackathons to help get things going, to just give these events for people to start to use and try and utilize some of these things. And it's helpful to ID those champions basically in each domain across an organization. So we're not just talking about one. It's these are the individuals who are excited about this transformation and have the knowledge and/or people skills for change efforts to help it happen. So they're not just the technical experts. We'll get to them in a minute. They are really the people experts.-And I love what you're saying because you're helping distinguish this idea of it's not just one person. This is also where the notion of a champion network can be built in. So that there are super users or champions throughout the organization, local go-to people, who have a sense of and are educated. They also have a sense of confidence about the future. These are also folks that can be leveraged in an advisory capacity.-Mm hmm.-Because what I'm hearing is kind of somewhere in between this executive sponsor and the champion, there's often this need for a steering committee. And this steering committee needs to —it should not be massive, but it can be informed by then hearing what the champion network says and getting feedback to be able to then enable the overall steering committee to be able to decide where do we want to invest in the one, two or three specific enterprise wide areas. And that's what the executive sponsor can then lead in the process.-You got it. It's helping to diffuse much of that energy across various areas to provide direction. And then, as they are out into the organization, more and more of these champions, they are really looking for who are the early adopters, those who have the skills, who are already incorporating it into their work, and these are the prototypers. So the champions help to identify those prototypers who are already excited about it. This is going to be roughly, what, 10%, 15% of your staff, your workforce who are already digging into it. They're building skills. They already have sub-agents galore. They're excited about it and they've seen how it can impact not only their personal productivity, but also the efficiency of their team or division or whatever they may be a part of. So these prototypers are going to be building the skills, the agents, the subagents, the processes, the automations, that the rest of the organization can leverage. Why? Because this is what they do for fun.(laughing) Like, they love this. So leverage that superpower.-And so let me ask you a question, Peter. The prototyper as kind of the next role.-Yeah.-How much of it have you seen clients just allow prototypers to self select? And how much of it is an assignment? And how many prototypers do you need? Because these are the squishier kinds of questions that it can be overwhelming, especially when there's a sense of optimism this is unique and it's going to manage itself in miraculous ways when we know it won't. You need to pay attention. You need to treat it like a regular project. Thus, prototypers. How many prototypes do you want happening? How do you organize that role?-Yeah. I mean, I think to give a classic consultant answer, it depends.(laughing) But you don't want so many that you can't keep track of them. So I think really that number of about 10 to 15 percent, if you're exceeding that number of prototypers compared to your overall number of employees, probably have too many to track. And as they're going about doing it, it's this is where you have the champions who are helping to organize and coordinate what are the efforts. What are the areas that the prototypers are building out skills for? What are they leveraging? What are the steps by which then things get rolled out to a broader audience? So it's not just, hey, I built something last night, we're rolling it out to the whole organization tomorrow. You know, what are those standards by which we're testing, we're assessing, and we're utilizing it for that improvement loop that gets done? Every organization is going to be a little different. So, but there has to be some, yeah, guardrails as you're putting some guidance there on that. But it's harnessing the natural energy that the prototypers are bringing. And that's what you're wanting to leverage. Because, again, this is a change management adoption flow. And so there's human side, and you want to take advantage of that energy, and it's the intangible part that they're bringing to the table. Because then you get the quick wins, and people are able to see, oh, wow, look what just happened because of this. Sign me up for that. That just saved me an extra two and a half hours of something I used to hate doing. And now... LLM of choice is doing it automated.-Mm hmm.-Yeah.-What's also helpful about looking at the prototypers is you can be very clear with each prototyper what the scope is that they need to be emphasizing. So I often think of you have three different levels of scope that a prototyper can then be involved with. One is that personal productivity level. And prototypers can then be leveraging various different AI tools to then improve and build personal productivity for themselves, and then they can share that with others Then that second level is seeing how many prototypers you want to then having working at the team level to then look at team processes, team outcomes, team efforts and say, okay, prototyper, focus at the team level, whatever team they're in or what their team they're assigned to, seeing what are the processes, how is value added in that team, and what can be routinized, what can be addressed, what can be analyzed. So that's a second level of analysis that could be assigned or scope. And then, of course, the third is at the organization or enterprise level, identifying who are the prototypers, working on the one or two, maybe three big macro process, big large efforts, whether that's a whole recruiting effort, applicant tracking and recruiting, or it's some sort of ERP system that you want to... or it's some sort of customer process, or it's a customer checkout process. Whatever it is that the organization decides on, you can then assign a prototyper or more than one to that. So what I like about the prototyper role is you can then get specific and be clear and connect the scope with what the prototyper is going to be focusing in on. So then the prototyper knows how to best communicate and share the results as well.-It is, because that term prototype is intentional. Prototypes are the first round. It's the beta. It's the pilot. They're supposed to fail because they're trying to design things quickly. So it's this iterative process of let's see what works, let's test it out and come back and improve it. Improve it. And it's helping to break the natural scope expansion as you have something that works for a small team or a small project, and we think, oh, great, we're going to adopt this for the entire organization. And that may not be the answer. And so it's being open to the idea that, well, this might actually work really well here, or let's test it out here before we then roll it out everywhere. Because what we don't want to do is have those solutions which are half baked and partially functional, and which then we have users frustrated throughout the organization, because then adoption is decreased, and that goes against the whole purpose of what we're trying to do. So we're trying to just build in those design thinking mentality of we're going to iterate, fail fast, and keep moving forward. So that's the prototypers.

That's their role: 17:01

to start putting ideas into tangible outputs so that then it can be iterated from. And built and improved.-And building on that one more time, what I find is organizations, this is one of the roles that the organization might assume they have.(laughing) Or they're not quite clear what skills are needed to make a good prototyper. And this is where I think we can get caught ourselves in thinking that AI is going to make it so easy that anybody can walk off the street and become a prototyper, because they should be able to have access to all of the tools, instantly understand stuff, and yet, it isn't that easy.-Correct.-The prototypers need a certain amount of skills. They need some technology skills. They need to be able to perhaps project manage. They need to be able to communicate and involve others. They need to have some business expertise. And maybe it's a small group of two or three, and that's the prototyping team that is then able to work, or the project team, in other words. I just find organizations can flat flat, and really get frustrated, when they assume that the role of prototyping doesn't require much set of qualifications, when it does.-Yeah, it does. It not only requires those qualifications you just identified, but it requires the intentional identification and giving that permission to people to fulfill this function, so that then they are also feeling they're unfettered. They're able to actually go forward and do this. And they have access to the information that they need, you know, to whatever systems so that that can happen. And so that access point actually gets us to this fourth role of an architect. An architect whose function is helping to look at information. And is information accessible at the level it's needed for each and every role and system. So it's helping to make that company data, the conversations, the skills, the resources, all of that, centralized and digitized so it's accessible to both AI and human workers, which is a large-scale effort. Because AI is only as good as the information it has access to. And same with humans. So the efforts to try and help, you know, share and spread and disseminate the appropriate information so people have access to it helps everybody all around. But it takes that intentional step to, okay, we just had this hallway conversation and we made this decision. Wonderful. Where is that captured? How is this communicated not only to the workforce, but also so the AI agents have access to it? Those are questions to be thinking about.-The data management, what I keep seeing from so many different clients is clients who are doing AI well, it's a simultaneous effort of a clear data management strategy. You need both in tandem, at least when you're wanting to focus AI at the enterprise level.-Mm hmm.-At the personal productivity level, not as needed, but the more advanced, the more functions you leverage, the more teams, it is critical to then look at what is your data strategy? Where are you storing it? How are you keep how are you flowing it? How are you then making this? And do you have a sense of confidence and trust with this? Peter, what are you seeing with this data management with folks you're working with?-It really isn't. And I would say, it's so important at the individual level to have that as well. Yes, at the organizational piece, because it helps at all levels. But as an individual has more access to the information they need, and they're able to have that partner in their agent to be able to find it and leverage it and utilize it, then it brings just a robustness to the type and the quality of work that they're able to carry out. So, when that gets extrapolated to multiple levels, then you're helping to get away from this whole notion that information is power. And individuals hoard information because now they are valuable. And we're trying to go completely against that. And you're trying to spread the information about so everybody has the information they need. Now, does this mean everybody has access to all information? No, because that is information overload. That's not helpful. What we're trying to do is you want to have this architect and the system for data management that you're implementing give everybody access to the information that they require to function at the top of their role that they are to execute in. That is the key. And it helps fight. You've all been to that organization of, well, this person, they have a history of not telling people information because they like to the water cooler conversation. They like to know. They feel valuable because they know something others don't. And that's counter to the culture of true productivity. That's counter to the culture of true progress. And so we're trying to turn that on its ear and say no.(laughing) Like, information needs to be spread to the level that's needed.-So what do we tell leaders who are looking and they're listening to us now and they're thinking of the organization, and they're like, our data is all over the place. I don't trust it. We're missing information. I don't think it's updated as regularly. It's not well connected. How do we respond to that? And because my first reaction is, you're not alone. I don't know what organization has, like, flawless, beautiful data that comes out and every... It's not that way, but yet, Peter, where do people start?-I think you you recognize you're not going to have a perfect system. You're never going to get to 100% data fully accessible and digitized. And if we are, then maybe we're losing a human piece. So it's how do you say next month we want to have incremental improvement to what we have today? Okay, so maybe we're leveraging AI meeting trackers for decisions, and that gets filed in client folders or in project folders or whatever it is, so that it's able to be disseminated better for those who attended or need that update on the project. Maybe that's just one step. But it's looking at how do we improve so that next month we're better than today.-Yeah.-And that's, I think, the... It's the Lego principle.(laughing) Going back to how do you build a Statue of Liberty out of Legos? It's one brick at a time. It's just one little step. So, how do you make that incremental progress?-The other aspect is this deep-seated assumption that I find, that AI should make things cheaper.(laughing) Or it shouldn't cost anything. It should be easy and quick. And cheap. And I just don't agree with this inexpensiveness that we believe. Yes, we want to be cost conscious, but AI is not done to save money. It's done for productivity. It's done for value add for the customer. It's done for competitive advantage. It's done to keep up with the marketplace. It is not necessarily done to save money. And I find when the attitude comes in, looking at AI as we need use this as a cost saving or cost cutting effort, that's one part, but that is not the main part. And when it is, it just increases frustration incredibly. Because that's not the part. And you think back on any large system implementation, no matter what people say it's going to save money, it doesn't.(laughing) And it usually costs more. And that's not the point. The point is to be more productive, to be more ready, to be more reliable, to be able to add value to customer. And it is a lifetime journey thing. And so when we see efforts and cost cutting as the major reason, ugghhhh, it's just going to lead to inevitable frustration. Again, it's important, and we need to keep this in mind. However, we are going to be focusing on value add to the customer. And with that comes improved internal decision making and analysis and ease for the customer. Those are the priorities.-And I'd say customer, both internal and external customer process, just to expand that, because you're exactly right. And we are in the thick of adoption, not only of a new technology, but a technology so disruptive that it is turning the entire organizational model on its ear over the next few years as we see this. So this is not an effort to immediately save money. Down the road, will there be or could there be cost cutting measures because of AI adoption? Possibly. That's a part of the promise that's being made. But those are not actually going to be showing up on a balance sheet or a P&L(laughing) for I think a few years. And it is a question, just a quick tangent. Where does your organization categorize from an account perspective expense on AI transformation?-Good point.-Is this under a technology, a dues and subscriptions, under some sort of those accounts? Or is it under labor? And as more and more agents and humans are managing both people and agents, it's an interesting philosophical conversation to have. And maybe it's a paradigm shift as we look at the investments we're making in AI.-I love that mindset shift because it challenges us to look at AI not just as a tool, but it's a labor resource. And if we think of it as like a member of our team, a hybrid member of our team, a quasi, what does that mean? What does that look like? And will that help us actually provide the needed resources and attention, organization, prioritization so that we can leverage it moving forward.-Completely. So we've talked kind of broadly about some of the roles that often are needed for these AI transformations. What's missing, Daniel? Are there areas that we haven't gotten to that would be helpful to talk about?-I think the biggest thing is to be able to then identify where to actually focus these roles. And that's where you want to then look across the organization and say, what are the routines? What are the typical routines? And what's the level of importance or impact for those routines? And that's where you go back to these roles from the executive sponsor on down to then help and have those roles clarify where do we prioritize our efforts. Because it's not just everywhere. It's not just getting a bunch of tools and saying, go forth. That's like at the educational, foundational level. But once you get past that, and this is the maturity curve, you think of the personal productivity as the foundation. The next level is how are we bringing AI and AI thinking and tools and human design thinking to the team, looking at one or two routines or processes, but then ultimately at the enterprise, not putting AI to every process across the organization. What's the one or two biggest value gained areas? And that's where you want to emphasize. So, the thing that's missing is to be able to focus. Focus, focus, focus.

And that's the essence of strategy: 30:32

knowing what to say no to. And AI is very deceptive, or it's so provocative and enticing. We want to say yes to it all and do it all. No. What is the one or two areas that this quarter or this year we are going to be tackling? And inevitably, it's going to be customer focused. How do we add value, external or internal, so that the end customer will be able to then stay with us, will be able to attract and increase the value to them. So, prioritizing, that's then the focus.-Oh, I couldn't have said that better. And so here's the caveat and the caution,

particularly to the executive sponsor and potentially for that AI champion: 31:26

Do not get so caught up in the excitement of the expansion of everything AI can do, that you are now confusing and bogging down your teams with an endless supply of ideas. They won't know what to do with it. They won't know how to prioritize it. And you're going to slow things down because of the flood of shiny objects you're throwing at them. Give them the respect and help them by prioritizing. That's one of the most effective things you can do. Resist, even though you can get so excited about doing 18 million things, but they can only do so many things at a time and to do them well.-Well, listeners, thank you for joining us for another episode of the Leadership Growth Podcast. Tools and ideas to help you develop yourself as a leader. Today, all things AI with the implementation in mind. How do you prioritize? How do you set specific roles so that you can plan accordingly at the personal level, at the team level, at the organizational level to optimize the way you are adding value to your customers and being strategic as you lead others? Thanks for joining us. We look forward to having you at a future episode. All the best. Take care, everyone. Bye. If you like this episode, please share it with a friend or colleague. Or better yet, leave a review to help other listeners find our show. And remember to subscribe so you never miss an episode. For more great content or to learn more about how Stewart Leadership can help you grow your ability to lead effectively, please visit stewartleadership.com.