A (4:42)

Love it. Okay, you talk to a lot of people and you hear a lot of things. What are some of the misconceptions you seem to hear popping up over and over again?

B (4:50)

Yeah, I think the biggest misconception is that anyone can just purchase generative AI tools, roll it out, and the magic is going to happen on its own. That's not really how it's happening, because when you look at generative AI and the type of technology that you're providing to your people, whether you're a small business, medium business, or A large corporation. It's very different. A regular tech rollout. Let me give you an example. If you are a company that uses, say, Gmail for your email, but you're about to move over to Microsoft and using Outlook, what that process usually looks like is everybody's using Gmail, you start rolling out Outlook, there's a transition period where your people can use both. But then one day you're turning off Gmail and everybody has to use Outlook. Right. So everybody is moving over to this new technology and your people don't really have a choice to work the old way. It's very different with generative AI because a lot of times it doesn't replace old technology. It's just giving your people a new way to work. But because they have worked a certain way without AI their entire career, what you're really asking your people is you're asking them to change. And that change is actually really hard for a lot of people. And I think that's where the misconception of, oh, we can just buy it and roll it out and the magic is going to happen is really holding a lot of companies back from really achieving what's possible with AI.

A (6:20)

Well, and thus the name of your consultancy. Right, because it's a play on transformation, because you have to figure out how to get humans to agree to change or to transform, which I think is fascinating. So when you get people onboarded properly, and we're going to talk about how to do that, but I want to talk about when it's done well, what's the upside? What are the benefits? What are the things that are waiting for those listening who are able to employ? Maybe what we're going to talk about today.

B (6:50)

Yeah, I think there are a lot of benefits at different levels too. If you look at the organizational level, there's actually a lot of research that shows that those companies who are ready to embrace AI and who are doing a good job rolling it out and getting the people to actually use it, they have a competitive advantage. I think it was Accenture. They did a recent study that showed that those organizations who are ready for AI, they see a 2.4 times higher productivity gain than organizations who don't embrace AI. And anyone who participated in a study with, I believe that was McKinsey. The participants said that if they have generative AI at work, their productivity goes up by 80% because they can now focus on more strategic work, they can get things done faster. And so at the organization level, it's really important to start embracing AI to get these Competitive advantages, really. At the individual level, it's more about reimagining how your work gets done. Imagine all of these tasks that are just draining your energy because they're tedious, they just take a long time, but they don't really require you to think a lot. I don't think AI is at the point yet where it can actually do a lot of very critical thinking. But those tasks, like if you have a report that you have to write, say at the end of the quarter, it'll take you maybe a day, two, sometimes three, just to get all the information you need for it, start writing it, because you start with a blank page, right? But imagine if you can use AI to do the first draft. Think of it almost like you have a assistant or an internal doing this for you. It gets you 70, 80% there. It won't be perfect. It won't be ready for you to just ship it off to your leadership, but it gets you 70% there. And then all you have to do is go in, verify the information, and edit it a little bit to make it your own. But that can actually help you not only save time, but it also allows you to focus on the more meaningful tasks that can actually help your team and your organization move forward and get more done. So I think it's a combination of time savings, but then also, like improving the type of work that you do and the quality of work that you deliver as well. I think those are probably the biggest benefits that you can get at the individual level.

A (9:10)

I want to double down on what you're saying here, because I have been working with my staff, and one of the things that I've been telling them, and I've also been speaking this when I'm at my conference, is I think that so many of us do tasks that are meaningless, brainless tasks, and we feel good because we've checked the box in asana, or project management tool. We feel like we've accomplished something, but we're not actually doing critical thinking. And critical thinking requires your brain to be free to think. It requires more cognitive load to actually think deeply about things and not just say yes or no and go to your instincts. And I believe from my own experience, and I hope that this applies with your clients as well, that if AI A allows us to kind of get started a little bit on critical thinking, right, Maybe coming up with a really rough plan and then allow our brain to, like, look at it and say, okay, here's how I would tweak it. Here's how I would Improve it, or if AI allows us to move some of the things off of our plate that are not really things that require critical thinking so that we can allocate actual human time. I feel like these are huge and advantages to leaders and huge advantages to people that work for businesses because they become more valuable. I'm just curious what you think about that.

B (10:29)

Yeah, absolutely. But I think in addition to that, you can also look at generative AI like a thought partner. Like, yes, it can get you started and give you, you know, a rough framework, for example, that you then react to. You flesh it out, you build it out a little bit more. But if you already have an idea that is just in your mind, for example, and you haven't really had the time to, you know, put it to paper or to really, you know, go through all the different details that are, you know, part of that idea, you can actually use AI to think it through with you. You can say, hey, here's a rough idea that I have. Here's what I'm trying to do with it. What am I missing? What's missing from this plan that I haven't thought of before? And so AI can help you get better, and that kind of goes back to improving the quality of the work that you do. I mean, we all have biases one way or another, right? Some are smaller, some are larger, but we all look at things through our own lens. And with AI by your side, you can actually start getting a different perspective in a way and say, hey, I assume the role of, say, a cfo. What would a CFO think when I provide them this business plan, for example? So I think there's a lot more to AI than just, hey, help me, you know, flash this out or write this out. I think of it as a thought partner, and I use it in that way a lot for my business as well.

A (11:44)

Love it. Okay, so we've got a variety of different people listening to this podcast. We've got CEOs like myself. We've got internal thought leaders that work inside of various size businesses who are maybe the ones on the front line doing the research. Maybe they've been tasked with bringing AI to the entire company. So when it comes to getting everyone in the business to adopt AI, where do we begin?

B (12:06)

Yeah, I think you really have to start with just a foundation and knowledge that it's not so much about the technology, it's really about helping your people get ready to use AI. And if you start by knowing this, hey, I have to focus on, on the humans. I cannot look at this as a pure technology rollout. I think that is probably the best thing that you can do for yourself and for your organization as well, because that will allow you to understand that it's a change management challenge. Because, like I mentioned before, you're really giving your people a different way of working. But because we're humans, it's actually human nature for us to avoid change. It's just how we're wired. Like, there's fear of the unknown. There's when we don't really know what AI means for us in our work, for our organization, for us as a human being, we tend to be anxious about it and even scared because we just don't know what it means. There's also status quo bias. That means that the way we have done things, they just feel better. There's no logical reason for it necessarily. It's just how we're wired. Like, our gut just tells us, no, the old way is a lot better. And at the same time, because change means something is potentially going away and something new is coming in, there's also loss aversion. And that pretty much means that anything that is new or that we're potentially losing, like the old way, our habits, our routines, we perceive that as more negative than potential gains, like the productivity gains, the higher quality of work for us, it just doesn't feel as strong as the things that we may lose with it. And I think you have to be able to bring that into your rollout strategy when you start rolling AI out to your people, just understanding it's human nature to avoid change. So how can I help my people to overcome these challenges and really embrace the new way of working and the change that we're asking them to go through?

A (14:04)

Okay, so what I heard you say is, first of all, it's a change management challenge. Secondly, people have a couple of biases. Status quo bias, which means that they're going to work within their comfort zone because they know how to do it. And loss aversion means I don't want to lose something that I perceive as valuable because I don't perceive the other thing to be more valuable, which I love. So what are the kinds of people that we need to be thinking about? Because this is something that we spoke about when we were prepping, that there's different kinds of quote, unquote people inside the organization that we need to think about. But before we go there, how do we take these three things? Well, actually, maybe you can sew the whole thing together, knowing we're working with humans. And knowing these people, like, we'll come back to how we can sew in these preconceived biases or notions that we know people have, and we'll come back to that. So what are the different kinds of people we're going to be dealing with? Because you've come up with some unique categories?

B (14:56)

Yeah, that's a really good question. Because we're all humans, right? We all deal with change differently. And so I tend to see three different types of users when I work with organizations. The first one, I call it the champion user. They're the ones who are really excited about AI. They couldn't wait to get access to the tool, and they're in it every day. They're actively trying to find ways to use it. They're playing around with it. They discover new use cases, and they're the ones who are really reimagining how their work gets done. When you start rolling out generative AI tools like Google Gemini or Microsoft Copilot, and you look at your usage data in the beginning, those champion users are the ones who will drive the most usage for you right from the beginning because they're just so excited about it. On the complete opposite side, you have what I consider the reluctant user. They're the ones who are either not interested in AI at all, they just couldn't care less about it, or they are skeptical because they may have tried it before but it didn't work for them. A lot of times that may have been very likely because their prompt wasn't good, or they tried to use it in a way that is not really intended to, and it didn't give them the response that they expected. They didn't know that it was really the prompt that wasn't good. But for them, the thought just manifests that, oh, this is not worth my time. It doesn't work, it's not worth it. And so those are the ones that you will have to almost convince to actually give it a shot and to start using it. They're the ones who will need the most handholding from you as an organization or as a leader to show them, hey, here's what you can do. You have to really walk them through every single step of the way. In the middle, you have what I call the curious user. They're open to AI. They are not as excited as the champion user, but they're also not as reluctant as a reluctant user. So they're the ones who are playing around with it a little bit. They may find one or two things that work for them, and they will start using AI for those one or two tasks. But they're not actively out there experimenting with that like the champion user is. But if you provide them with a prompt, a use case, and say, hey, we tried this. This works, you, here you go. They will be happy to start using it and, you know, going through that sometimes painful change, but they're open to it. They just need a little bit more handholding. So these are kind of the three different types of users that I tend to see. And the challenge, you know, I mentioned, it's a human readiness challenge, is for your organization. You have to find a way to speak to every single user, no matter if they're the champion user, the reluctant user, or the curious user. So you have to be able to find a way to present AI to them and the benefits that they can get out of it in a way that speaks to them. And I think that's one of the challenges that a lot of organizations struggle with, because when you look at enablement teams, for example, they're usually the ones that see the value because they're, you know, more in technology, they will start using it more. So for them, it just seems natural to start using the new technology. And sometimes it's hard for them to understand that there are some people who have a hard time with change, and we have to speak to them a little differently.

A (18:06)

Okay, so I want to ask some clarifying questions. Let's imagine this is a pie chart with all three of these users we've got. The champions are the ones that are the most excited. The reluctance are the ones that are the most skeptical. And then you've got the curious, which are the ones that are open. How would you put this in a pie chart just based on your experience working across different organizations?

B (18:25)

Yeah, I think most of the users are on the curious side. Like, it's a spectrum. Right. It's not like you're right here if you're a curious user. There are some users that are very curious and some that are just open enough to fit into that bucket. So I would say that most of them are going to be in that curious one. Like, you have to just show them what's possible because they will not actively go out and explore on their own. But if you're an enablement team or a leader, and you can say, hey, here are three use cases that apply to your specific role. Here are some prompts that you can start using. They're probably open to that. They will play around with it and they will adopt you know, maybe not everything, but a good portion of what you're showing them. The smaller version. The smaller portion, I think, are the champion users that are just super excited and there's always going to be a bucket. I think the bucket of reluctant user really depends on, honestly, your industry. I think, because there are some industries that are a little bit more tech forward and that are more on the front line of innovation, and then there are others that are just traditionally, you know, a little bit further behind the times when it comes to. To technology. So I think it depends on, you know, how big your reluctant bucket is just based on, you know, your own industry, but as well as the culture that you have created within your organization. If you're more, hey, let's experiment together and it's okay if you fail, meaning, hey, it's okay if you tried something with AI and it didn't work. We'll learn from it and move forward. I think that will probably reduce the number of reluctant users you have versus if failure is seen as something that you absolutely want to avoid in your organization. So I think there are a lot of different parts that play a role.

A (20:09)

Oh, I like that. I like that. So if you're an organization that prides yourself on high quality, we never fail, you're going to have a big reluctant bucket here because they're going to see this as a path to mistakes. So it seems to me like if I was to guess the champions is like 1 to 2% is probably what I'm guessing a super tiny fragment. And then the curious is 50 to 70% if you're lucky. And then the remaining is reluctant. But the reluctant might be really, really huge if you're an organization that's extremely traditional and you just don't have any room for experimentation. Is that kind of what I'm hearing? You say something along those lines? Am I close?

B (20:48)

Yeah, I think so. I'm not sure if it's 1 or 2%. I think it's probably more like 5 or 7%, at least conversations that I have had. But, yeah, I think, you know, that's pretty much accurate.

A (20:57)

I love it. I was going to go with 5% the champions, but, you know, that's a pretty big chunk depending on how big your company is.

B (21:04)

So.

A (21:04)

Okay, so how do we. I'm just going to stay on this a little bit. How do we. Knowing that the biggest bucket is the curious, and then the reluctant is even a bigger bucket, how do we move people from reluctant to curious? Do you have any tips on that?

B (21:17)

Yeah, I think Kind of going back to the human nature to avoid change. The curious user, we already said, like, they're open to it, right? They're open to change, but they need a little bit more handholding. Same like the reluctant user, they need a lot of handholding and they need to be convinced that, yes, this painful process of going through the change is actually worth it. Because there's something in it for me. And I think the best way to show them that, hey, it's worth going through this painful process is by showing them what's in it for them, Showing them use cases. For example, when you start talking to your curious user, that's more on the spectrum, you know, closer to the reluctant user. If you have a conversation with them and say, hey, what are the one or two tasks that you wish you wouldn't have to do every day, every week? A lot of times these are the tasks like what we talked about earlier, that don't really use a lot of brain power. They're just time suckers, you know, they just take a really long time to do. But you're not really doing meaningful work. If that's the type of answer that you get from those users. And you can say, okay, let's work together and figure out how you can use generative AI to do 70 or 80% of that work and then all you do is finish it and you can move on to the next. I think it's these types of examples where you can make the use cases real for those users where they can start to see, oh, okay, yeah, it helps me sometimes. The question that I get when I'm in a room with people is, well, but it's cheating when I start using AI. And I think there's even studies that show, especially for women.

A (22:48)

I was going to say that, yeah, that's true.

B (22:50)

Yeah, that's a big misconception that, you know, women just feel like if I start using AI, I'm cheating because it's not my work. Because I challenge that, because it is your work. You're, for one, you're using the prompt, right? You came up with a prompt to use it. Yes, AI wrote 70 or 80% of it, but you didn't just take it and hand it off to your leaders. You still went through it, you verified all the information, you made edits to it, you made sure that it speaks perfectly to your audience and then you hand it off. So it's still your work. You just did different types of works. And I think that's really what it comes to, down to is a new way of working and reimagining what we do. But it also means some of the work that you do may actually shift. So you don't start with a blank page and write it. You're just becoming almost like an editor and a finisher because you're finishing the work that AI did for you.

A (23:42)

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B (25:01)

Yeah, it's kind of going back to, you know, you have to show people what's possible. Like there's so many use cases for generative AI that sometimes it's hard to see, see what it is that you can do. It's a lot easier when you have a small focus and you're like, oh, okay, I can do this with AI versus oh my God, the sky is the limit. What am I going to do? Right? Like it's too many choices, too many options that kind of block you from actually using it effectively. And so to combat that, I came up with a framework that uses four mindsets or four lenses that I teach people in my workshops as a means for them when they have a new task for them to pause for a moment and ask themselves, can this mindset help me with that? Can I do it with AI? And the four mindsets that I developed are really meant for that. You don't have to sit there and say, oh, I'm using this mindset to do it is more a framework of helping you identify that, yes, I can help you with the task. There are four of them that I developed and the first one is what I call the assisted mindset. And that's really when you start using AI to help you get things done faster. It's your system that you're basically handing the work off and they come back saying like, hey, here it is, go and you know, finish it up like we talked about. The other one is the explorer mindset and that is really helping you use AI to think in different directions, they get different perspectives, weigh the pros and cons, etc. There's the editor mindset, which is helping you use AI to make something that you already have better. That can be something that you created on your own, or it can be something that you started with AI, say through the assistant mindset. But it's really helping you increase the quality of the work. Be that rewriting something to make it sound more professional, more concise, more persuasive, or analyzing some data and actually, you know, extracting the key findings from it. Like it's really helping you make things better. And the last one is the coaching mindset and I think that is for me the most powerful, but I think it's the most underutilized way to use AI. What the coaching mindset does is it's really showing you that you can use AI to help you grow and learn new things in a way that speaks to you. Like, for example, if I want to learn about, say blockchain technology, I'm not really interested in that. But you know, there might be a case where I need to understand, you know, what it is. If I go to AI or go to articles online and try to understand how blockchain technology works, it might be really complicated for me because I don't really have background in that topic. But I, for example, I have been playing tennis my entire life. If I'm not doing something work related, I'm pretty much doing something tennis related to. So if I can use AI to say, hey, explain blockchain technology to me using tennis analogies, I will get something back that helps me learn because I know tennis in and out. And if you explain a topic to me and put it through the terms or use terms from tennis to explain it to me, it will resonate and I will understand it. So it's using AI to learn something in a way that makes it really easy for me and that's speaks to me at a more personal level. So these are the four mindsets that I Developed that just, you know, help people pause for a moment and say, can the assistant help me? Can the editor help me? Et cetera.

A (28:19)

Yeah, I think you had. When we were prepping for this, you had a nonprofit example that you wanted to share.

B (28:23)

Yeah, for example, you know, I was working with a nonprofit organization that I volunteer with, and we have a lot of surveys that we send out, and a lot of times we get a lot of open comments back as well. And it used to take the 10 of us, you know, a month going through 16,000 open comments, going through them, tagging them, categorizing them, and then we would all get together to discuss, hey, in the 500 that you reviewed, what did you see? What did you see? And then we would try to find the top 10 trends and then further the discussion trying to figure out how can we action on them. So I started using the explorer mindset, and I said, hey, let's get a different perspective on this data. And actually went into the data and I said, look at these open comments. Give me the top 10 trends. And for each trend, give me two action items of things that we can do in the short term to address the issues that came up. And I was done with that in, like, 15 minutes. So I took that back to my group and I said, hey, here are the top 10 trends. Let's go in action on it. And that was just a way for me to ask myself, well, is there a way for AI to help me with this? You know, it's a fairly basic example, but I think just getting people to say, stop and ask themselves, can AI help me with that? That's one of the most important things that you can do for yourself and for the people that work in your organization as well.

A (29:43)

Love it. Okay, so what I'm hearing you say is there's four different ways you can think about using AI. One is to use it to assist you with the things you already do. One is to use it in an exploratory capacity to kind of enable you to think differently by coming to it with a problem that you don't have a resolution for. Another one is the editor, which is, here's something I made. Make it better. And then the last one is the coach. Right. The coaching methodology is where you say, hey, I want to learn this thing, or, I don't understand this thing. Help me figure out a way to use it in a way that I can understand. I love all four of those different lenses as you refer to them. I think it's really cool. So now that we've spent a fair amount of time talking about the different kinds of users we've got. Right. The champions, the curious and the reluctant, and then some lenses upon which we can teach people how to use AI. How do we actually implement change inside the organization or with our clients?

B (30:43)

Yeah, I think talking about the human nature to avoid change, everybody reacts to change differently. But what you cannot do or what you shouldn't do is look at it as just a technology rollout. Because as we talked about earlier, if you just make it available to people, they don't know where to start because they're just so many things that you can do with it. So that's overwhelm right there. And you're asking people to change and they're not going to do that unless they see the benefits out of it and get the motivation behind it as well. So you kind of have to look at generative AI and the rollout through the lens of, okay, I want to have aspiration, I have to have inspiration, and I have to have motivation for my people to actually start using it. And the way to do that is by activating all three layers of your organization. What I mean by that is the framework that that I developed is really helping you activate your leaders to help lead that change from the top down, activate your enablement teams and your champions. So those who are actively using AI and you who are probably the most expert in generative AI, help them to inspire the change from within and then building it from the bottom up. And that's where your people are starting to reimagine how their work gets done. So you really have to look at all three layers to lead from the top down, inspire from within, and build from the bottom up. And if you that you're really building a foundation that speaks to everybody in your organization at all levels.

A (32:12)

Okay, I want to dig in a little deeper on all of this. You said start with your leaders and your champions, but you said there were three layers, and I'm not sure I caught all three of them. So can you go through those again? I got the champions and I got the leaders. What's the other layer that you were talking about?

B (32:27)

Yeah, of course. So is leading from the top down. That's where your leaders will come in and lead the change. Inspiring from within. That's where your enablement and your champions come in, because they're the ones who will discover the use cases and actually start showing what's possible and then building from the bottom up. That's where your users are coming in when they start to reimagine how they work gets done and actually start using AI every day and building those AI habits as well. So these are the three layers that I use in my framework.

A (32:55)

Okay, so are these three different paths or are these simultaneous paths? Help me understand that a little bit.

B (33:00)

They're parallel, but also simultaneous. So it really depends on where your organization is. Usually what I do is I start with the leadership. And the reason for that is during times of change, people tend to look to their leaders to see what is going on. Why is this a priority? Why should I go through this painful process of changing? And if your leaders, for example, aren't actively using AI or they're not really talking about it, that sends a message to your people. And that message is, it's not important. I don't have to go through this change because my leaders don't care. But let's imagine that your leaders are actively using AI and making that usage visible. It doesn't mean that they're constantly saying, hey, look what I did with AI. But let's imagine that, say you have a monthly meeting where the entire team comes together. If your leader sends out a email before that meeting and there's a little note that says agenda was generated with the help of AI, that makes it visible. It's not intrusive, but it makes it visible that, oh, my leader used AI for this. If they then kick that meeting off for the first five minutes and say, okay, I want to hear how AI helped you this week. What is a win that you had with AI that shows that they actually care about their people using AI? It's not huge, right? It's just five minutes. And they're just asking for people to share their success stories. But it does a few things. It shows that one, my leader cares about AI being used in our day to day work. And it helps me actually reimagine how I do work and get in front of my leaders to show that. And the third piece is whether that's a champion or a user sharing that win, it actually helps inspire others. Because let's imagine Bob just reinvented how he does his say, monthly expense report. If he started doing that with AI, but nobody knows about it, is it really happening? Nobody knows about it. So who knows if AI is really helping Bob, right? But if he comes to that meeting and says, hey, I just saved 30 minutes every week because I'm now using AI to do my expense report, that makes it visible. And that means that win that Bob had at his Desk is now spreading across the organization because everybody's aware of it. And so that's where the leadership comes in. They play a really important role in making AI visible and providing people a North Star that they can align to and understand why they're being asked to change. I think that is really important, but something that most organizations don't even think about when they start rolling out AI.

A (35:37)

I love this as the CEO of my business and someone who is very motivated to employ AI Change.

B (35:44)

Yeah. And you do as well. You motivate your people as well. We were talking.

A (35:47)

Yeah, I do. But at the same time, it's very easy to just send an email saying we're to going to go do AI and then move on to my job as a CEO and that's not enough. And I like what you're doing here, which is to recommend that it's continuous message that's getting implemented and integrated into the regular comms from the leader. Now, some people listening work for the leader. Do you recommend that they go on a special mission and meet with the leader and say, hey, let's agree that you're going to take on this extra role. And I know that I might be getting into one of the other categories here, but like, sometimes you're dealing with a leader who would happily be part of this, and other times that leader might actually be reluctant. Right. What's your feedback on that?

B (36:27)

Yeah, absolutely. I have conversations with some leaders that are all about it and they're like, yes, what can I do? I want to help. And then others, it's almost like a chicken and egg situation where they're like, okay, yeah, I want to do it, but I do want to see the impact first before I commit to doing it. But it's like, well, you can't drive as much impact unless you're doing it. But if you're not doing it, the impact isn't going to be there. So how do you have these types of convers? Right. And a lot of times I come in and I actually do workshops with leaders that for one, help them understand the whole idea of this is a change management challenge. A lot of times, you know, they just look at it as a technology and say, I'm trying to retrain them to think about all the changes that people have to go through. And I do walk them through. You know, it's human nature to avoid change. You have all these different types of users and you have to be able to speak to them. And I show them examples like what I just mentioned, like. Like if you're a leader and you make AI visible, it sends a very different message because all of a sudden you're basically putting out there that AI is important for us, we're doing it at the leadership level and we have a expectation or desire for everybody else to also do it. So it's these types of workshops that I think are really powerful and a lot of times it kind of opens the leaders minds a little bit because they may have had a fairly narrow view of the technology, you know, as a technology, but when they start to see, it's like, hey, there's a whole human aspect of AI that we probably didn't think of it of before or we didn't think of it, you know, to have such a big impact. I think that's when the mind change happens and you know, they become more open to say, okay, I will do a few things. Be that, you know, adding that little note, the agenda was generated with the help of AI or asking their direct hey, what are five things that your team did this month with AI that I can then share at the next town hall or something like that? So I think it's just having conversations and really focusing on the human side and how important it is.

A (38:28)

Well, let's talk about the inspiring within with champions a little bit because this may be a route that some people are going to have to take first. Right, so talk to me a little bit about that.

B (38:36)

Yeah, I think the inspiring from within is probably the easiest path to take and to start with because you will have these champion users, everybody listening, you probably know exactly who that is within your organization because they're probably like me, like they just can't stop talking about the amazing things that they can do with AI. So the first thing that you want to do is activate them, encourage them to actually become the champion for their team, for their function, for their organization, whatever makes sense for how your company is structured. But if you can get them to really take that more visible role, you can do a few things with that. For one, you can give them something that makes their champion status, if you want, visible for the organization. Like what I provide to a lot of the organizations that I work with is email banners that they can put on the signature in their email that says I'm a champion or ask me how I use AI today or a little avatar that they can put around their photo and their profile that says I use AI every day or something like that that just makes it visible and that actually tells others, hey, I can go and ask Bob about It because he uses AI or, you know, he says, hey, ask me how I use AI. So it's activations like that that make AI visible. But then it's also about those wins that they have because they're the ones who are on the ground, right? They're the ones doing the actual work that everybody else is doing as well, but they're reimagining how that work gets done with AI. So if they're the ones who have, say, a going back to that report example that I have or the expense report example, if Bob has a series of prompts that help him with that, it should be fairly easy for him to say, hey, here's a prompt. Go and use it and pass it on to the rest of his team. Because everybody's doing expense reports at the end of the month. And so if he can create those prompts, create a prompt book that everybody has access to, it pretty much opens the door for other users to go into that library of prompts, pick one or two. And knowing that, hey, these prompts work like they work for Bob, so they will work for me. I don't have to do the hard work of coming up with a prompt myself. So I think that's where the inspiring from within comes in, where the champion users are reimagining the work. So let them help others be inspired to do that as well.

A (40:59)

Any tips on the bottom up building?

B (41:01)

Yeah, I think that is really where it comes down to. You have to help users build habits. That is one of the hardest things. Like, we all know how hard it is to unlearn a bad habit and build a new one, right? And so the best way to do that is, yes, you need the inspiration from the Bobs of the world who are actively using AI, but it's also showing them through, like small trainings what they can do with AI. You absolutely need to do a prompting one on one type of training. Because if your users start using AI and it doesn't work because their prompt isn't good, the thought manifests, oh, this isn't worth it. It's not worth my time. It's not working right. So you absolutely want to start out with a really solid prompting, one on one training to give them the foundation of how to structure a prompt. But after that, you have to help them with tips and tricks of how to actually start building these habits around using AI. And like the workshops that I do with both teams and individuals actually finishes with, how can I start building AI habits today? And it's just ways to build New routines. Say every morning you commit to doing one prompt a day. It doesn't have to be anything super complicated, but just commit to say, as you pour your coffee in the morning, start using a prompt, whether that's, hey, what's the weather today? Or if it's a Monday, hey, I have a really tough week coming out with a lot of deadlines. What's a strategy that I can use to make sure that I keep these deadlines that I'm focused throughout the week? It's things like that that will actually help them build habits around using AI. And then what I also tell people is because you're unlearning an old habit and building a new one, it will be hard in the beginning or hard ish in the beginning because nobody is an expert right from the get go. So, yes, you would expect, if you think of, like star ratings, that the first few times you use AI, you may get three stars, maybe some two stars. You will probably not immediately get five star ratings for the output that you get back, but that's okay. So if you start, for example, tracking your progress, and I do that through journaling, which is what I tell people to do as well, imagine that every day or once a week, you can start it weekly as well. You put down what you used AI for, like what's the use case you used and what's a star rating you would give it. You will see that in the beginning you will have a lot of fairly easy use cases and, you know, maybe some two or three star ratings. But if you do this every week, you will see that fairly quickly. Not only will your use cases become more complex because you get more comfortable with it, you get more familiar with what's possible. You will also see the star ratings go up. You will see four stars, maybe some five stars as well. And if you see that, like visually see that, hey, I started off, say a month ago with a lot of very easy prompts. I tried, but I only got two star ratings. I stuck with it and now I get more complex projects and I get four, sometimes five star ratings. That makes me feel good as a human being, right? Because I see, wow, look at this progress that I'm making. And I think that can be a really powerful tool as well. Just something for people to reflect on the work that they do and realize, wow, I'm getting better at this. I'm actually having fun with it too. I think that's going to be really important as well.

A (44:26)

Kristen, there's so much gold in that mind of yours. This has been absolutely spectacular. If people want to connect with you on the socials, what's your preferred platform? And if they're interested in possibly working with you, where do you want to send?

B (44:40)

Yeah, absolutely. You can find me on LinkedIn. Just find me for Kristen Gin. Or you can go to my website as well@transformaishen.com I think there will be a link in the description as well. And there are a lot of good resources for you as well. Like if you're interested in the framework that I walked you through, you can download an ebook that kind of walks you through what the framework is, how it works, and how we might be able to work together as well. And if you're an individual or you know, a smaller business and you're just interested in in some workshops, there's a whole section there for AI for humans type of workshops that's really focusing on like, not the tech jargony type of trainings, but really making it approachable and relatable. So yeah, go to my website and connect with me on LinkedIn. Absolutely.

A (45:20)

Kristin Jin G I N N For those that are listening, thank you so much for sharing your wisdom with us today.

B (45:26)

Yeah, absolutely. It was such a pleasure to have me. Thank you.

A (45:29)

Hey, if you missed anything, we took all the notes for you over@social mediaexaminer.com A87. Be sure to follow this show on your favorite podcasting app. If you've been a listener for a while, we would love a review. And also do let your friends know about this show. You can tag me on Facebook, LinkedIn and or X. And do check out our other shows, the Social Media Marketing Podcast and the Social Media Marketing Talk Show. This brings us to the end of the AI Explored podcast. I'm your host, Michael Stelzner. I'll be back with you next week. I hope you make the best out of your day and may AI help you become more successful.

B (46:01)

The AI Explored podcast is a production of Social Media Examiner.

A (46:09)

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