Winning with AI: The 12-Week FrameworkThat Actually Works with Charlene Li

Michael interviews keynote speaker and seven-time author Charlene Li about her new book and 12-week program focused on leading AI through leadership and strategy rather than technology explanations. Li and co-author Katia Welsh outline a playbook that starts with existing business strategy and builds an AI roadmap to create value over a rolling 18-month horizon, updating quarterly while keeping strategy “in ink” and tactics “in pencil.” They discuss why organizations overthink AI strategy but under-execute, the need to make AI use safe and expected, provide time to practice, and have leaders model usage to reduce stigma. Li describes leaders’ “AI hesitation gap” between FOMO and fear, emphasizes AI fluency through practice, and frames value creation as engagement, productivity, and reinvention supported by governance and coordinated enterprise efforts.

Timestamps:
00:24 Welcome
01:30 Book Focus Leading AI
02:48 Why a Strategic Playbook
04:10 No AI Strategy Needed
06:32 Rolling 18 Month Roadmap
09:17 Why Execution Stalls
11:56 Employee Fears and Trust
13:52 Leadership FOMO vs FOGI
16:58 Build AI Fluency Fast
19:13 Tools Access and Practicality
22:17 Training AI With Context
24:08 12 Week Sprint Foundations
27:09 Efficiency to Reinvention
30:22 Three Key Takeaways
32:11 Career Inflection Point Story
33:48 Closing

Connect with Charlene:
https://www.linkedin.com/in/charleneli/
https://charleneli.com

Transcript

SPEAKER_01 0:00

Welcome to the Top Voice Podcast, where each week I sit down with leading voices in business, leadership, and transformation to unpack the issues that matter most. Together, we explore fresh insights, bold ideas, and real-world stories from people shaping how we think about change, culture, and what's possible. Hello and welcome to the Top Voice Podcast. It is July 28th, summer's almost done, and we're here with Charlene Lee, keynote speaker, author, multiple-time author, to talk about winning with AI, everybody's favorite conversation, and your new book and your 12-week program to become more fluent. And I think there's never been a better time to talk about this. Uh, Charlene, before I give you the mic to introduce yourself for those of you who are tuning into the live stream, please do let us know where you're tuning in from. We always love to take questions and comments. And as always, please do be sure to subscribe on your favorite podcast platform. It's the best way to support the show. Oh, Charlene, you're you're on mute right now somehow.

SPEAKER_00 1:20

I touched my microphone. It's very understandable.

SPEAKER_01 1:22

There we go. That's okay. It's a live show. We just keep going.

SPEAKER_00 1:26

Yeah, so uh I am a longtime author and speaker. Um, I've written seven books. So this is my seventh book. Uh, and I focus on disruptive transformation, leadership, and strategy. And the the this book, I think, is not about the technology, it's really about leadership and strategy. And in particular, how do you lead AI? How do you show up as a leader? And and in particular, where do you begin? There are so many things you can do, like so many things. It can be very confusing. So, my co-author, Katya Welsh, who has been a longtime chief AI officer for over 15 years, uh, and I collaborate on this book to just say this is what you do first, second, third, and fourth, to see that kind of value that you want from your AI.

SPEAKER_01 2:10

I love that. And I I I want to jump into I've got a question about your strategy leading up to this, because I think so many people are writing about the the doom and gloom and the the big picture disruption that's happening, but you all have taken a more, I think a more tactical approach a little bit. Like here's step one, step two, step three. You you mentioned you started writing this book in November, or maybe it was done in November, you, you, you, it got launched in March. How did you, how did you get this far in front of the conversation when it feels like time is moving so quickly? How how did you how did you do that?

SPEAKER_00 2:44

Well, we started collaborating in 2023, actually. And it just took a lot of different curves along the way. Um, what started out as an explanatory book became a much more of a playbook. And and again, I want to focus. This is not just tactical, this is very strategic. And that was the key difference is that so many other books are explaining the technology, how it works, why it's important. We all get that. We know it's important. Now, what do we do with it? Right. So we dispense with that very quickly and say, what's really important to you? And what is it that you know as a leader? Where can you start? And again, many leaders of the most common question I guess with people is how do I get up to speed and how do I stay on top of things? And and I'm like, welcome to the club.

SPEAKER_01 3:29

Welcome to the club.

SPEAKER_00 3:30

All of us waking up in the morning with our hair on fire.

SPEAKER_01 3:33

We're all it's yeah, we're all going through it on some level. So, so you let's talk about the book and maybe some of the details uh here a bit and hit the high points because one of the I think counterintuitive comments that you make is that there's not uh uh it's not for lack of AI strategy. It's it's that organizations are overthinking it. Maybe they're underthinking execution, maybe getting stuck in the swirl. What's the difference in the way that you're thinking about this in terms of strategy and execution and what companies are getting right and what companies are getting wrong?

SPEAKER_00 4:06

It may be a little bit of um looking at slicing the differences a little bit thinly, but we believe that you have a business strategy. You have a purpose, a mission, values, objectives. You know those things really well. You know your customer, you know your industry, you know your employees. Uh so there are a lot of things that you know. And for some reason, and I've seen this now happen with multiple technology cycles, all that goes out the window, and we got this bright, shiny object with the technology here with AI. And like, okay, what do we do with AI? What do we do with it? What can we use it for? And we believe you don't need an AI strategy. You should probably not begin the word strategy with a technology and a tool. Instead, you should be asking, how can we use AI to support what we know our business strategy? How do we use AI to achieve our objectives? Uh, how does it support our purpose and the way we execute it? Are we using it in a responsible and ethical way that's in line with our values? So I saw one organization that came and we were talking to them and they had seven strategic objectives. Six of them were the usual suspects. Grow, customer satisfaction increases. And the seventh one was use AI to make the first six successful, to achieve the first six. And I think that's the right way to think about it. So you need an AI roadmap that shows how you are going to create value against your objectives over the next 16 months, over the next six quarters. And it's long enough so that you can see out into the future to say, this is what we want to be, this is what we want to do, the value you want to create in 18 months, and then know what we have to do today in order to get there. That's what your strategy is.

SPEAKER_01 5:51

Right. Right.

SPEAKER_00 5:52

So you need a roadmap to support that strategy.

SPEAKER_01 5:55

I yeah, I meant roadmaps are important, and I want to talk about that because when we started opening up the conversation, we got uh on the call earlier. You mentioned how quickly things are moving, and we all experience that. You mentioned you're already starting to look at maybe some updates to your book because it's going so fast. 16 months feels like a long time in the new world of AI. How do we how do we balance real strategic planning and long-term vision with the day-to-day disruption? And how does the playbook that you've built help us kind of navigate that?

SPEAKER_00 6:28

Well, I think the 18 months is long enough so it escapes the the constraints of a typical yearly budget cycle. Uh, and it's also long enough for you to think about longer term, even because some people say, well, that's way too long. Other people say, well, that's way too short. We need longer-term objectives. It's sort of this medium stage. But this is the key thing. People think, I don't even know what's going to happen next week, uh let alone 18 months from now. And so your strategy is written in ink and your roadmap is written in pencil. So, how you get there, the tactics versus what are the problems we want to tackle? What are the challenges? What are the opportunities out there, these big boulders that we want to move? How are we going to create value? How are we going to win in the marketplace? You have to have that big thinking, and then you can have the small actions that begin, and then you can scale it as quickly as you can. Think big, start small, scale fast.

SPEAKER_01 7:27

Oh, I love that.

SPEAKER_00 7:28

So the the roadmap should be updated at least once a quarter. So at the end of Q1, you look and say, okay, where are we now? It's kind of like what you do with sprints, but you do it as an organization and say, where are we now? How did we do over the past quarter? What has changed? What new capabilities do we have? How has the technology changed? How have our customers changed? And then you adjust the other five quarters. And here's the key: you add another quarter at the end. It's a rolling eight two-month plan because why have a short, just keep advancing it? Yeah. Like you're three months later, you should have a three months later runway for that. And you just sit in a different place right now, three months later. That the world looks different, and your assumptions change, sometimes radically. So you should make adjustments for them.

SPEAKER_01 8:18

I'm a I'm I'm I'm a big fan of rolling wave planning. I've been doing that for for a long time, and I think it's a really good advice. Let's talk about the a bit of the reality of what companies are experiencing right now. Because I think you're you're laying out uh the beginnings of a framework that help people understand this is my business strategy, this is what I'm trying to achieve. But when we when we look at some of the data coming back from the real-time studies and different articles, there's there's almost feels like a new one every day. Companies are really feeling the execution tension and maybe the lack of returns from just putting it out there. So, so you've said what companies are should be doing and how to get that right, but it sounds like a lot of them are getting it wrong. So, what are they doing that's getting in the way? And I have a couple thoughts on this that are coming from my study, but I want to hear from you first because you talk to so many companies about this.

SPEAKER_00 9:13

Right. Well, well, well, but if the idea is you want to use AI to support your business strategy, and then what you do instead is you go, okay, here's AI. I'm gonna give it to my CIO, I'm gonna roll it out to everyone, get everyone gets a license, and then go use it. And we'll be done. Adopting AI is very different from adapting your organization. To see the real value, to see real change happening, that requires hard work. Because if you want to see growth, if you want to see impact, that means you have to change. And change is hard. I I study disruption, and we think that disruption is going to drive growth. It's actually just the opposite. Growth creates disruption. And so the act, if you're not preparing for that disruption coming your way, then nothing is going to change. So have you made it safe for people to use AI? Are they expected to use AI? Is it clear how they can use it to support the work? Are they given the tools and the training? Probably, but are they given the time to practice it? Or in reality, are they saying, yeah, there's AI stuff, don't mess around with it. Make sure you get your work done. And if you do use AI, you feel like you're showing up and maybe I'm being seen as cheating because I didn't spend so much time on this, and I'm having to use, I mean, it's just all the things we know that 70% of the people in the US believe that AI is going to be bad, that we think it's going to be harmful. You're just pushing against these headwinds. And in the in the in the in the face of all these challenges, where's leadership?

SPEAKER_01 10:48

Yeah.

SPEAKER_00 10:49

They're not using it themselves. So no one goes and says, well, this is that essential. It's not strategic. We're not aligning it with our goals. Uh, our leaders aren't even using it. I can take a bye on this.

SPEAKER_01 11:01

So you've hit a number of things that uh when you start talking about change, you're you're you're speaking my language. So you mentioned two things that I think maybe by by coincidence are the two of the flagship needs of employees from the study that we just released. The first one is experimentation, which is time to experiment. And by the way, it can't be experimentation that's just go do something interesting. It needs to be aimed at something productive. And part of the challenge, I think I'd love to hear your point of view on this, and I've heard a lot of people say it, is when people think they're experimenting to teach AI to take their job, that's not really a motivating experiment to run. So I'm gonna take a bye, as you mentioned. Are there people that do you get that sense that people feel like I'm I don't want to use the tools because I feel like they're just I'm teaching it to take my own job away from me?

SPEAKER_00 11:52

Well, of course. Everyone's asking that. How is my work going to change? Are they just doing this so that I train the AI and can take my job? And again, they're asking these questions, which are very legitimate questions, in the absence of any dialogue from leadership that says, this is why we're using AI, we're using it to support our objectives, and this is what it means for you. Well, what does it mean for me?

SPEAKER_01 12:14

Right.

SPEAKER_00 12:15

How is my job going to change? How do I fit into this roadmap? If they're in the absence of that roadmap, you can't explain what you're going to do with AI. And if the purpose of AI is just to become more efficient and cut your workforce, because I've 10x one person, so I don't need the other nine, that becomes very obvious. Right. If instead the idea is I'm going to 10x every single employee and we're going to have 100x capability, and we're going to do this with that capability. This is our vision, and this is what the future we want to have. That's a very different story. And then the conversation becomes well, this is what we think is going to happen. We don't know exactly. Nobody can promise anybody to have a job, but I hope that you'll come on this journey with us. It is going to be hard. We don't know exactly how it's going to change, but we're going to be side by side doing this.

SPEAKER_01 13:02

I think that transparency and that authenticity is absolutely essential because it hits to the second point that came out in the study. And then it's actually the third point. You mentioned another one, which is being safe to make mistakes and fail and experiment through iterating and testing and learning. It turns out that's a really important way that we learn as adults and and as human beings. And then watching leaders go first. And can you be authentic about that? You mentioned at the beginning that leaders aren't going first. So what what is this is a big generalization. What is the leadership experience right now in companies when it comes to AI? What are they getting? How are they thinking about this? How are they talking about it? And I realize that's this is an overgeneralization, but let's just start with that because I think that'll be helpful.

SPEAKER_00 13:48

I I think it's interesting because they're pulled in two different directions. They have FOMO, which says, I want to get into this space. I'm missing out. Opportunity costs are huge. We got to get in. And then there's an opposing emotion, which is Fogi, fear of getting in.

SPEAKER_01 14:05

Yeah.

SPEAKER_00 14:05

The water looks really murky. I have no idea what I'm doing. I am way in over my head. This stuff can be dangerous. It hallucinates. There's no way I'm going to trust it with my business. I really don't want to deal with this. But I know I have to.

SPEAKER_01 14:20

Yeah.

SPEAKER_00 14:21

So they just like this is AI hesitation gap, is what I call it. And you just are just sitting on the sidelines watching it speed by you. And it's just nerve-wracking. So what do I do? What do I do? What do I do? And I recently did a leadership workshop where people could ask me. So people keep telling me to use AI to do what? And this is the executive team. Like, we know we have to use AI, I use it all the time, copilot, but I don't get like what am I supposed to use it for? And so the way I explained it is you're a really good leader. And you're a really good leader because you focus on solving some very specific problems. These are challenges that you see or opportunities you want to pursue, and you're just laser focused on them like a bowdog. Like, we're gonna get this done. Use AI to address those problems. And if you don't know how to use AI, this is the meta point. Uh use AI to ask, ask AI how you can use AI to solve that problem. So it and they go, Oh, that seems pretty straightforward. I'm like, exactly. To my very first point, sense and logic tends to go out the window when you see these bright, shiny objects.

SPEAKER_01 15:30

Yeah.

SPEAKER_00 15:30

I say to executives, keep coming back to the things that you know. Focus on those. And so when somebody comes to you and says, hey, I've got this bright new shiny technology, I've got this agentic AI or physical or whatever the latest rendition is, I think we should try it. You go, great, love the enthusiasm. How does it help us support any of these top strategic goals that we have?

SPEAKER_01 15:51

Yeah.

SPEAKER_00 15:51

Spell it out for me. Because if we can do it better, faster, cheaper, safer, then yeah, let's do that.

SPEAKER_01 15:57

I I think there's real wisdom in this. A lot of people get AI and they go, hey, go solve a new problem. And I think what you're reminding people is take a problem that you work on every day or in some periodic time frame and go have a conversation with AI that says, how could I solve this problem differently? And I I'll just use a very little simple example from my learning journey, which is I used to manage this entire podcast in a spreadsheet. And I one night started a conversation with Claude, is the one that I use mostly in co-work, and built a CRM system on my computer that manages it all for me. It took me a couple of weeks, but I figured it out. And it was something that's right in front of you that you see every day. And I think some of what it sounds like the paralysis that leaders are getting into is seeing the forest for the trees and just going, oh my God, I'm supposed to do all this cool stuff. How about I just solve something that's been an irritant for me in my business today and start there?

unknown 16:54

Yeah.

SPEAKER_00 16:54

And I think what happens then, it creates that aha moment. And you go, oh, now I get it. Now I get how we use AI. And I think this is the point that I'm really hammering home these days, which is you have to develop AI fluency. And I'll give you an example. Do you remember the time when you first picked up chopsticks? Oh, yeah. You're like, how on earth am I going to eat with chopsticks? Like you, this is insane. And then you slowly kind of manage it and you get a few pieces of food in your mouth. And then over time, you're just shoving food into your mouth. Like you're not even thinking about it. And so until you hit that slippery noodle, and then you go, like, how am I going to pick that up? Right. And that's what AI feels like. You've been handed a pair of chopsticks and you really don't know how to use them. And so you have to practice and make it useful. Use it to pick up the food, pick up the problems that you want to solve and address in all aspects of your life. And just practice it. And then share your learnings. And every once in a while you hit that slippery noodle. You're like, oh, I don't, I don't get this, or the results aren't what I expected. And instead of chucking it out the window and say AI doesn't work, you go, hmm, maybe I should adjust my grip here a little bit. So I I this is the advice I give the leaders. Start using it, use it to prepare for a meeting. And then go to the meeting and say, hey, everyone, I use AI to prepare for this meeting. This is what I did. I I'd love to hear from you all how you use AI to prepare for this meeting. And it does two things. It sets the expectation that you're going to use AI to prepare for these meetings with me. And the second thing is it destigmatizes the use of AI. That if I'm using it, then you can use it. And what we're doing is we're making it safe and we're making it acceptable. And we're also sharing it. So all these different ways to again change the mindset around AI is really important right now. And that's a leadership challenge.

SPEAKER_01 18:58

That's it's I want to talk about it. That it's it's great advice, and I love that um comparison. I don't know that I'll ever use AI again without thinking about chopsticks. So that was really helpful. I've heard another scenario when it comes to leaders, and that is that leaders are getting all the good stuff and employees are not. And then some companies, many companies that are maybe built on the Microsoft stack, they're using Copilot, and then they have maybe some niche tools that are industry specific, and that those are going to leaders, and leaders are getting trained up on maybe some of the more specific or advanced technologies, and the rest of the employee base is left to work with copilot or some maybe more generic version. A, are you seeing that? And B, how does it affect the leadership dynamic in the opposite direction? Because you're telling a story about maybe leaders being hesitant, but I've heard some, maybe it's just one or two cases of the other side where leaders are like, hey, everybody, how come you're not doing the cool stuff like me?

SPEAKER_00 19:57

Well, I think again, that's just a leader being clueless that they don't understand people don't have access to these tools. Yeah. And also, again, what are you trying to do? Are you trying to do cool things or useful things? It's great to play with Claude and co-work and all these other things, but now co-pilot has anthropic co-work in it. And and this company that I was working with, you know, I could use my generic version of co-work, but their of co-pilot, but their version of co-pilot, which has all their information, just gave them so much richer information than even Claude that isn't connected to the systems can't meet. Yeah. So I again, I I think you don't need the latest, greatest technologies. And in fact, the worst thing you could do is try to read all the newsletters to keep on top of the latest models and all the new capabilities and all the new agentiard workflows that are out there. It doesn't help you if you're not using that knowledge to apply it to the problems that you have at hand.

SPEAKER_01 20:54

Yeah.

SPEAKER_00 20:54

So you're better off using a lower-powered model to actually do real work and know that it is reliable, it is trained, it is not hallucinating, and you can trust it. I've I've been playing with Fable Five, and it's great for some things and terrible at other things. It's not working it out.

unknown 21:13

Yeah.

SPEAKER_00 21:13

It's not necessarily the best.

SPEAKER_01 21:14

I I you're hitting on something that I just want to say back because I think it's important is the value of AI is not dropping into an empty uh screen and asking a question. That's helpful, but it's actually in the training of that agent or that tool on your unique situation, your goals, your strategy, your obstacles, your your language, the way you speak. Then it becomes, and that that takes time. And I'm curious because your framework inside of your book is a is a 12 week sprint to become fluent with AI. And I know you don't have to walk through all 12 weeks, but there's this time dimension of I need to iterate and practice. And you've said that so beautifully. But walk us through that 12 weeks in the broad strokes. And then how do I get from an empty screen that doesn't know me into something that's been trained where the value starts to really accelerate?

SPEAKER_00 22:13

Well, let me talk about that question first and then I'll come back to the 12 weeks. Again, your AI will know so much more about you the more you practice with it, the more you use it. You can also force-feed it information. Again, some people call it RAG, retrieval, archival, augmented uh retrieval uh generation, uh, retrieval augmented generation. And so that's when you give it information and you tell it to learn it, it learns all your information. Um, and then recently there are these new things called knowledge layers and context layers that will pull information from across your enterprise and understand the decisions, the reasons for those decisions. So you may have a discount of 20% in a CRM record, but why was that discount given? And so it's connecting all these different places so you understand context. And that is what agentic AI needs. It needs context and traceability back to a decision so it can verify that that was the right decision and why it was made. Uh so these there are different ways now to train it. I have a context and knowledge layer on underlying my AI so that I can take that knowledge from one um from Claude over to anthropic to um to open AI to perplexity, even guaca can put it on top of that and have it read those files. So I'm not dependent on just the AI's memory. So there are ways you can you can do this uh to make it more relevant. And one of the things I do as soon as I can is to get into executive hands to make it as relevant for them as possible. So just even uploading a bit of their writing, of a bit of their um their speaking voice, their strategy, their objectives, their development plans, whatever it is. We just give it that little bit of context and it becomes so much more relevant to them.

SPEAKER_01 24:02

It does.

SPEAKER_00 24:03

Yeah. Yeah. Uh to the 12-week point, uh, we we lay it out in 12 weeks, and we don't promise that you're going to like change the world in 12 weeks, but you will have a roadmap. You will have that 18-month roadmap. You will know what the key points that you want to support in your strategy, how you're going to use AI to support it. And you also will have what we call the building blocks, the mindset or your culture, uh, the people set, the skills that you need to have, uh, the platform and technologies that you want as a foundation, and very importantly, your governance, your decision sets. So all of those foundational pieces are in place, may not be complete, but they're in place. You've got the beginnings of them, and you can then run. That's the thing. At the end of the 12 weeks, you've done all this foundational work, you can go at speed then, and you can go with confidence. Because everyone has the same plan. Everyone knows what's what you're executing on. You've done the leadership and the communications of this. And the problem right now is you have all these different siloed efforts. No one really knows what's happening, no one's really coordinating things at the enterprise level. And you're at that enterprise level value that you keep hoping for just doesn't materialize because no one's focused on it.

SPEAKER_01 25:18

Yeah. That I've I recently met a former colleague of mine who's now at a private company, and she has the job of being that governance, enterprise governance layer. And as she described to me, her whole job is just running between functions, trying to get them to talk and share all the great stuff they're doing and get them to coordinate something that becomes more than just finance or product or HR building some cool app. It's like, hey, how do we coordinate this across the enterprise? And and this governance conversation came up. So I just I love that you're describing building a foundation. And the house analogy always comes to mind when you say that is it sounds like everybody's being caught up in chasing the shiny object. And I think what you're encouraging is no, get caught up in building the foundation and then point your organization at the goals you already have to get a lot better. And so I just, it's really simple and maybe overlooked advice. So I'm sure your book is crushing it. I want to go back, we kind of have time for one more big question that it's maybe unfair to ask, but I'll ask it anyway, which is you're you're describing um scenario A where don't come up with new goals, take your existing goals and figure out how AI can support them. And I think that's that's great. There are companies out there that are reimagining business with AI and not taking their existing goals and they're maybe disrupting in a different way. This is like the dot-com boom where you went from brick and mortar buildings to selling products to online e-commerce. What do you say to companies that are maybe being threatened by this? Is it enough to just take our existing goals and chase them with AI? Or should we really be thinking more dramatically about the business model itself?

SPEAKER_00 27:05

Well, we think that there are three ways to create value. Clearly, there's there's better engagement with your customers and employees in your ecosystems. There's efficiency and productivity. So, again, just fantastic if you can augment people in the work that they do. And then the third one is reinvention. And to your point, uh it and I think companies that think about all three and invest in all three as a portfolio of opportunities is the right way to think about it. The problem is that reinvention requires imagination. And it requires that you test and challenge the assumptions that you've hold dear for decades in some cases. And that's not easy for many organizations to do. And you're asking somebody who doesn't even know how to use it every day to imagine how they can use AI to reinvent their business. And I think there was some foundational work they need to do first. They need to trust AI, understand what it can do, and then you can ask the questions. Then you have earned the ability, you always have the right, but the ability to actually answer those questions. What else could we do? What are the possibilities? If we could have a hundred X capability from our people, what could we do? Yeah. And we have lots of case studies in the book about how organizations started doing this back in 2020, early 2023, just when they were getting their hands on it. They go, oh my goodness, the things that we could do now that we've always wanted to do, but we could never do it. And could you imagine growing now with just a little bit more headcount? We're not talking about cutting people, we're talking about adding people.

SPEAKER_01 28:43

Yeah.

SPEAKER_00 28:44

Because of the opportunities we see.

SPEAKER_01 28:46

Yeah.

SPEAKER_00 28:46

So do we operate in a world of scarcity, which is where if you look in the status quo where you are now, and that's all you see, of course, you're going to optimize for the status quo because you don't see anything changing. Or we do you see a world of abundance where there are opportunities, there's growth, and you wouldn't you would never think about letting go your people because they know your business, you like them.

SPEAKER_01 29:10

Right.

SPEAKER_00 29:10

So you want them. And so you're investing them and change with them and look for these opportunities and point them at it.

SPEAKER_01 29:18

I love that.

SPEAKER_00 29:18

And if you have employees who are like, I don't know about this, I just don't think I want to do it, then you have to have a conversation with them. Like they're we want you to come along on this right. But if you don't want to, then totally understand that. And this may not be the right place for you.

SPEAKER_01 29:30

Yeah, yeah. I it's really well said. And I just think one of the great statements you said in there, I want to say back is you've always had the right to reimagine your business, but you've got to earn the ability to do it. And I think that's a really well said and well-reminded concept because I think we often do jump to the shiny object or to the possibilities, and we don't understand that we lack the foundation, which is what your book is all about. Uh Charlene, we're we're at time. We could keep going. And and uh I we've talked about so many things here. I'd I'd love to, what are two to three really deep core concepts that you want the viewers and listeners to take away from the moment we're in and winning with AI and how to really get this foundation right?

SPEAKER_00 30:17

Yes, I I think the first one is start with your strategy. Start with what you know, and then use AI to accomplish that strategy. Uh, second, make sure you are using AI, that you understand it, that you feel comfortable with it, that there's a flow in your use of it, that you turn to it, that it becomes a habit. And it really is a fluency that you know how to use it and also when not to use it. And I think the third thing is when you can have those two things in place, the strategic use of AI, and that you're comfortable using AI, that's when you unlock these new options, these new possibilities. Because then you can see it, you can see where the opportunities are, where the challenges are that you could never have imagined that you could go after. So I think those are the three things. Focus on strategy, get fluent, and then invest in the re-imagination and reinvention of your business.

SPEAKER_01 31:16

I I think it's those are those are three great pieces of advice. And I know we'll give everyone a chance to know where to follow you here and get the book, because I think it's it's clear what you've put together is really foundational work. We keep coming back to that word, and I just think so many people are struggling with where to start, how to start, what to start on. And I think your book is a great place to give people some perspective and some strategies and some tactics all wrapped up into one. So I I know everyone's gonna be excited to get that. Um, Charlene, we also have a closing tradition on this podcast, which is we asked the guest a question left by the last guest, and they always have a way of working out a little bit. And you've been in this space for a long time. So the question that's left for you is what was the inflection point in your career that prompted you to do what you do now?

SPEAKER_00 32:07

Well, I graduated from Harvard Business School in 1993, and the internet was just coming online. Um, we had, you know, AOL and CompuServe, but the World Wide Web uh was literally invented the year, the same month I graduated. And so I went to newspapers. I joined the San Jose Mercury News in the middle of Silicon Valley when most of my classmates were going to consulting and investment banking, and they thought I was insane. And I I wanted to be at the the front row, I wanted a front row seat at the edge of disruption because I could see the internet coming and that one of the first businesses that would be impacted by that were newspapers. And the entire business model was going to be at risk. So I was like, I want to be in the middle of that, yeah, figuring that out. Like, how do you lean into that disruption? And that has been the foundation of my entire career. The the way I have been expressing that disruption has changed from the internet to digital to social media, mobile, cloud, digital transformation, and now AI. But the core problem that I wanted to solve was this whole point about leading disruption. And that's the advice I give to people today is especially people coming out of school, don't focus on what you want to do, focus on the problem you want to solve. And the way you want to solve that problem is probably going to change over the years, uh, maybe months at this point too, as well. So focus on the problem, not what you do.

SPEAKER_01 33:33

I love that. I love that. And that is, I was gonna ask you about the arc of the dot-com boom to now, but we'll probably save that for the next conversation because we could get into all the ways it's it's the same but different. Um, Charlene, where can people follow you? And most importantly, where can they get your book? Uh, tell us where we can track all that down.

SPEAKER_00 33:52

Yeah, you can follow me on my website, charlenlee.com. And I am very active on LinkedIn. I'm also starting up on Substack uh and YouTube. So uh just follow me in all those places and I would love to hear from you. I again uh will include information to all the links and everything, but please get in touch, send me messages. Uh, I love to hear from people and I always encourage uh people to share what you learn, what your challenges are, what your takeaways are, because that's how I do my work and my research.

SPEAKER_01 34:22

Yeah, there's nothing better than a conversation with a real person about what they're struggling with. So we will include all of that in the show notes and make sure everyone has that resource. And, you know, we talk about AI a lot on this show, as you would expect. And I just really do appreciate that you've not just furthered the conversation, but you've provided a great resource. And I hope everyone checks it out. For those of you that tuned in today live, thanks for being a part of the show. Those of you that are listening on your favorite platform, again, please do subscribe. It's the best way to support the show. Thanks again, Charlene, and we'll see you next week on the Top Voice podcast.