Building Confidence and Imagination in the Age of AI

David Rice: You are in back-to-back meetings all day. Your team keeps asking about AI, the strategy, and honestly, you're not sure. You're supposed to have answers. That's why you got promoted, isn't it? But with AI, everybody's figuring it out at the same time. And the uncomfortable truth is, if you're not using AI yourself, you're already falling behind the people you're supposed to be leading.

Today's guest on the podcast is Charlene Li. She's the founder of Quantum Networks Group, and she's gonna tell us why 83% of people in China's AI is beneficial while only 39% of Americans do. More importantly, she's gonna show you how to break out of pilot purgatory and actually start building AI fluency in your organization.

We're gonna cover why your fear of losing control is the real problem, not the technology, how to deal with shadow AI usage, the four dimensions of AI fluency every leader needs to master, and how one sales leader uses AI to be in every customer conversation without attending a single extra meeting.

I'm David Rice. This is People Managing People. And if you've been paralyzed about what to do with AI, this episode is your permission slip to start experimenting. So let's go.

Welcome to the People Managing People Podcast, the show where we help leaders keep work human in the age of AI. My name is David Rice and I'm your host, as always. Today I'm joined by Charlene Li. She is a strategic advisor and the founder of Quantum Networks Group. We're gonna be talking about the current state of how leaders are using AI and what needs to change for leadership development in this new era of work.

Charlene, welcome.

Charlene Li: Thank you for having me.

David Rice: Yeah, absolutely. We were talking before this and you said that many leaders, they struggle with AI because they feel threatened, they're used to having the answers, right? Everybody goes to them for the answer, and then this shift leads to a lot of uncertainty and change of like what good leadership looks like.

So take me through that for what a lot of leaders are experiencing right now.

Charlene Li: Right. I mean, again, a lot of leaders are, were promoted because they knew how to do the job better than other people, and they're seen as. Being able to, again, as you said, have the answers. And with AI, we're all figuring it out altogether at the same time, and it puts an extra pressure on leaders to say, so what are we doing with this?

Where are we going with it? When there really isn't an answer all the time, we may have a directional travel, so it's really hard for leaders, and AI already creates a lot of fear and anxiety. Add on top of that, that you're supposed to have everything figured out as a leader, that's just not going to happen.

So I think we have to move from needing to have all the answers to being able to ask great questions that were direct people in the way that we wanna go to. It's like, okay, so how are you going to use AI to create value? Not what's the ROI of AI? Those are two very different questions. And a leader needs to understand what the difference is between those two.

David Rice: Yeah. I just come back from a conference and I listen to a lot of leaders kind of talking to each other and obviously talking with me as well. And I feel like one of the big skills, the biggest skill maybe for leadership of the future is just that sort of comfort in your own skin. Your ability to like embrace the uncertainty and just kind of say like, yeah, I don't really know, but I'm interested in this.

I'm interested in that this is the group of people that I've brought together to help me figure this out. You know what I mean? The ability to sort of see the network connections that are gonna make the big difference in your project or in your, you know, initiative. I feel like that's like where leadership is gonna have to flex its muscle, so to speak, rather than expertise.

Charlene Li: Exactly. And especially with AI, I think a really important part is that leaders set, create an environment where people can experiment and learn. This is different from the pilots that people were running because that's a whole different issue of the pilot purgatory that AI's experiencing. This is about you getting in, using AI, experimenting and figuring out what works and doesn't work.

And creating that environment so that you can learn individually, but also learn together is a really important part for a leader in this day and age of AI.

David Rice: You were pointing out to me that Americans are far more likely than people in other countries to see AI is harmful. And I'm curious what you think is behind that fear and how much of it comes down to culture and leadership narratives?

Charlene Li: Again, I think one of the things we have in our society and most Western societies is, a) culture narrative of individualism. And in other countries like China, Indonesia, Thailand, where there's a stronger sense of collectivism as the overall cultural narrative, AI is seen as a incredibly positive force.

So only 39% of people here in the US believe that AI is gonna be more beneficial than harmful. And in China it's 83% more than twice as many. And so they see AI as an enabler for the collective to do more things, not as a threat. In the US we see it as potentially taking away the things that make us individual.

And I think the leadership narrative that needs to shift is we keep talking about AI, eliminating jobs versus AI will amplify what we do as humans and will help us do more meaningful work. Both are true, but which are you going to emphasize and talk about and steer people towards and work towards as a leader and as an organization?

David Rice: Yeah. I'm going for like, what are your actions gonna support, right. Because I think a lot of people in this country where they're reacting to what they see and they're seeing headlines about all kinds of crazy stuff to all these layoffs. And so it's, the actions aren't lining up with the idea that it's gonna help us be better.

And we do, like you said, it's a very individualistic society, and so there's always the feeling of like, this could be the thing that leaves me out to dry or, you know, we struggle with isolation anyways. It's interesting to see what's playing out, like on the psychology front. There's so many different facets to the, what AI is doing right now, but you know, you can see the fear from a lot of people who don't maybe have a good connection to their community.

Charlene Li: It's also, we have this myth of control. We believe that when you're a leader or you're doing well, you are in control. And what AI, and frankly, if you ever believe that leadership is really about control, then you don't really understand leadership. You're never in control. And the only thing that keeps you in a leadership position is the credibility you have as a leader.

It's not your title, it's that relationship that you form with the people who follow you. So for us to feel like we're losing control because of AI, the threat of it, the fear and anxiety that it creates when you flip onto the other side and see AI as not a loss of control, but a huge enabler. The way you talk about AI, the way you use it, completely changes.

And so I can tell, usually when leaders talk to me about the fear and anxiety side of AI. My very first question is, what do you use it for? And it turns out they're not actively using it. They haven't been given the training, they haven't been exposed to the powerful tools that can really make a difference.

They have experienced a really bad hallucination, so they just go, I want nothing to do with this. It is not good. It is error prone. It gives me bad answers. I can't trust it. So understanding what AI can do, developing a fluency around it, I think is a top priority for organizations.

David Rice: Yeah, definitely at the leadership level too, right?

Like. There's, I've noticed this in talking to a few different CHROs where they're just almost in the state of paralysis around what to do with it, and I'm like, well, you maybe just start experimenting. But even that, some of 'em, especially if you're in a larger org, but if you're in a larger org where there's a lot of pieces to move, to do anything, I think it makes it immensely harder to feel like you have the ability or the freedom or the time, quite frankly, to test things out and just be experimental and be innovative.

Charlene Li: And you have the flip side of that where some organizations have really cut off the use of AI. They may have Microsoft copilot, but that's a slim down version of AI. But the irony was I was talking to is one technology company, and they're talking about AI agents. They built it in their products, but inside the own company, they don't allow the people to use it.

And I go, but you're all using AI. She goes, yeah, we have second laptops, we have second phones and we're doing all this shadow AI. I'm like, does it know about this? 'cause they shut you down in order to not keep you, let you do those things. And so there's a big disconnect. Between how we sometimes talk about AI and actually how we use it, and the more we can be upfront and transparent to say, this is not a fad, AI is not going to go away, so let's deal with it and deal with it realistically.

And instead of putting our head in the sand and hoping that it'll just go away, or that I can outlast it until I don't have to deal with it anymore. It's not a smart way to do it. And so people, your employees are watching to see how you're talking about how you're using AI. And if they don't see you taking a proactive stance about this, they go, well, we have no strategy.

We have no play in this game. And it's coming. It's coming. And it don't wanna be at a company that doesn't know what it's going to do. This is my career, this is my livelihood. I need to be at a company that is embracing AI and running towards it. So I think it's a real retention issue. If you don't have a roadmap of how you're going to use AI, then in that absence, people are going to make things up and assume that there's nothing going on.

David Rice: Well, so you said it there. There's all this shadow AI usage, right? And then that creates capabilities. They're learning, they're becoming more capable and how they're using it. But you have no say in what they're becoming capable of, right? You have no say in how they're developing. So I think like part of the problem is that currently a lot of leaders are thinking of AI purely in terms of productivity measurements, right?

And I'm curious about how do we shift the conversation away from that into more imagining and thinking about what's possible as people develop those capabilities, whether you are steering it or not.

Charlene Li: I think if leaders need to stop asking what's ROI first, and start asking what's the value, but especially the new value that AI can create.

So instead of just automating your processes, one of the worst things you could do is automating an existing bad process. What if you could imagine a new process that AI enables? How would that not only make things more efficient, but also allow you to do new things? One of the things we companies we spoke with for the book was Call center and they of course use AI to get the call center agents to be more productive and in particular to have higher quality, fewer errors, and they use all those gains to tackle a big, long list of customer experience initiatives that they wanted to tackle but didn't have the time and resources to do it.

Now they had it. Then they realized that with additional capabilities they could take on new products and services, they were reinventing themselves because of this AI capability, and they knew that their clients weren't going to develop this, so they did it on their behalf. Again, it was a three tiered strategy right from the very beginning to create value, not just as efficiency, but also creating a better customer engagement and also reinventing the business.

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Yeah, it's interesting like because based on what you do, value looks differently or it looks different, right? But I am starting to notice more people thinking, okay, I saw this graphic, this guy said go from T-shaped professional to comb shaped professional, but more in thinking about how do I drive a bit of value across each one of these things and have more of the ability to do that rather than being so specialized in my one thing that's the only thing I can create value in.

Because you know, AI for marketing, it's gonna look like one thing versus AI in HR that's gonna look very different, right? So I think it's interesting to see how people are developing themselves as well.

Charlene Li: And the biggest problem I see is that people have this long list of use cases. They have like hundreds of use cases and use cases are not a strategy.

You already have a business strategy. AI is not, you don't have an AI strategy. AI is a technology. It's a tool. It's not a strategy. So figure out how you use AI as a technology, as a strategic initiative, a strategic platform to help you achieve your business strategy, your business objectives. So this is not about having a separate strategy.

It needs to be deeply integrated to what's most important to your organization. So while HR can do their own initiatives. Customer service can do their own existence. Same. Same thing with marketing. Everyone can do all the things that make sense with the departments, but what are we going to do as an organization to take the greatest impact that we can have?

And this goes back to your point, it takes some imagination. We as organizations are not very good at thinking across silos. We're very good at optimizing for our departments. To think broadly and strategically about what are the ways that AI can really help us move that needle, achieve our objectives better, faster, cheaper, all three, and also safer in a more ethical way.

It's really important. These are really important questions to be asking.

David Rice: And just like you mentioned there, it's hard to look at the whole organization, think holistically about what we're gonna do it. It also feels like there's a lot of over-hyping the short term and under hyping the long term, right?

We are thinking about, well, what am I getting out of it now? I mean, we've had this technology in its current form, just a short time, really, and yet we're asking about ROI. I can't think of a lot of other technologies where we just asked that quickly, well, what's it giving me back? The expectation and the demand of it, I feel was different than a of a lot of other technologies that we might've implemented.

So I'm curious, how do leaders find that right balance between like healthy skepticism and visionary optimism in this environment where these expectations exist?

Charlene Li: I think again, the healthy skepticism is important to have. It's not that AI can't create value. Absolutely, it can create value. The question becomes how are we delivering value right now and this quarter and the next quarter and the quarter after that?

And that's why that AI roadmap, again, not a strategy, but a roadmap of how you're going to use AI to create value is so important. Believe me, value is being created left and right. You just may not be understanding. It may not be capturing it, and it may not be prioritizing what value you want to focus on and deliver and drive as an organization.

So just having that plan, that roadmap that says we are going to do this and not that this quarter. And it's transparent to everyone. Everyone knows what they're on the hook to do. When somebody goes, I wanna do this, now you can. We're not doing that now. We are going to do that in two quarters from now and this is why, and we can still adjust things.

That roadmap is written in pencil. Your strategy is written unique, but your execution roadmap is written in pencil, so you can adjust it depending on skill advancements, technology change, maybe there are some issues that come up with your customers that you now understand better, so you move things around.

Having that plan is really important because what we're seeing here isn't an issue in a hype cycle gap. What we have is a transformation gap between us understanding this technology that's ready to use, and our organization's ability to actually adopt them and adapt our organization. That's the gap.

So it's not that this technology can't do it, we see hundreds and thousands of companies. Doing really amazing things with AI and they're not the usual suspects. They're not the big technology disruptive companies. They're universities, their healthcare clinics, those small companies that are finding and extracting value from AI today.

So buckle down, learn how to use AI and then figure out how it's gonna create value right away.

David Rice: Yeah. It's interesting you said that the sort of understanding your capabilities. You mentioned there, there's hundreds of use cases, right? And we even created this thing, it's like a transformation explorer.

It's got 146 use cases in it for HR alone. Right. But the problem is that if you don't have an understanding of your maturity, we realize this pretty quickly, that if the person using it doesn't understand that the maturity of their organization and their readiness for AI, all of that information is kind of, I mean, it's very difficult to navigate or understand what's possibly useful for you.

Not that it's useless, but it lacks the true value of what it's intended to do, and so.

Charlene Li: Lemme challenge that a little bit because I don't think any organization is ready for AI. Again, nobody knows how to use this stuff. Show me an organization that says, oh yeah, we got it all. We know exactly how to do this.

It's nobody knows how to do it. And so if you are waiting to be ready or if you're looking at feasibility, you're waiting for perfect data. I hear that all the time. We gotta clean our data before we can use AI. I'm like no. You can use it now. Go and clean up your data, but figure out all the other things you can do.

Go find data that may not be perfect, but it's usable. You can use AI to clean it up pretty quickly and start extracting value from it. Learn from that. It may not be the biggest use case that you could have. Then the other thing is why are we looking at the use cases and deciding based on feasibility when instead we should be looking at our strategic priorities because we already know what's important.

And then based on the biggest priorities that we have, what are the biggest challenges or opportunities that we have with those strategic objectives? And then ask how can AI help us accomplish those things, overcome those challenges, or actually tap into those opportunities? That should be the prioritization matrix that you use.

How welcoming, what's the value of achieving our strategic objectives and what's the speed at which we can realize that value? Because in this space, everyone has access to the same technology. So speed is the new moat. There's no other competitive advantage that you have other than the speed of which you can adopt these technologies and adapt your organization.

That's it. So if you're trying to be ready, well get ready, improve all the things that you need to do, but there's no substitute to getting into it and having a focus. We talk about the traits of an AI ready culture. Speed is one of them. Focus is another one. And there are things that continuous learning and being able to experiment and being absolutely customer focused. But speed and focus are the two foundational ideas, half SB and the focus that it is absolutely focused on your strategic objectives.

David Rice: I always say, we've all got this thing at some point. It's like you gotta realize it's the people using it and how they're using it and how they're essentially directed to use it.

That's gonna be the big difference for you.

Charlene Li: Yeah, but that's your podcast. This is what this audience is all about. I've been in transformative technology and disruptive technologies for three decades now, and the thing I've seen is that it's never about the technology. It is always about the people. So this is a people problem.

Again, I don't wanna say people problem. People opportunity.

David Rice: Yeah.

Charlene Li: To really take AI and the speed at which it is being used. And I guarantee you people in your organization are using it. They're using it. All the time. So you may have to declare what I call AI amnesty to say, come out of the dark. Show us what you're using with AI.

Use our preferred tools that are locked down, not training the model. Secure everything but come out of the shadows. No more shadow AI. You have amnesty. We won't care that you used this in the past. We just won't care. But please bring it out into the open and let's figure out how to do this together.

David Rice: It's interesting that you say that, you know, come outta the shadows 'cause I, there's a lot of executives who are curious about this, but like you say, they're reluctant to commit. I'm curious what have you learned about helping risk averse leaders see AI as a strategic ally instead of a threat?

Because I think we agree it's always about the people, right? It's not really about the technology, but what does that look like as organizations start leading humans and autonomous systems side by side? Like what do we have to do differently to get the best out of both?

Charlene Li: First of all, you have to overcome the fear and anxiety 'cause people will not use, they will not learn about AI.

They won't go near it unless you address that fear and anxiety. I know one organization in their training process, they have a special training that if you're skeptical about AI, go to this training first and all they do is answer questions. Again, this is not about. Watching show and tell. This is about really addressing that emotional blockers that somebody may have and to understand where they're coming from and to say, yeah, I hear that.

Let's go and address that in our training session the next time, step by step address, all of those issues, and the fact that they're not seen as crazy or dismissed for their fear and anxiety means a big deal. It's not like they're being, you know, curmudgeonly or anything. These are very real fears and anxieties.

Once you can address that, then you can say, well, how do we use this? And the only way I've been able to reach across to people is to take something that they are actively working on themselves. So this is not about the use cases that I have inside of a book or in a presentation. Hands-on, what are you working on, professional or personal?

What are you working on? A question that you have, a task that you have to do. Something that's just a pain to get done. Let's go and look at how AI could potentially help with that, and it may not. And that's the important thing to understand too. So when I think about AI fluency, there are a couple parts.

It's, do you understand what AI can do and its limitations? Do you understand how to use it responsibly and ethically? Do you know how to use it to create value in the work that you do? And then final step, can you teach somebody how to use it because you know you're fluent when you can explain it to somebody else.

It also has this nice boomerang effect that when you are fluent, then you are teaching other people in the organization to be fluent too. So there's a nice cycle there that's going on too. So this is about developing that fluency and it is a very individual lies process. You can do some training that's highly centralized, but the reality is it's a lot of individual experimenting, handholding, sharing of best practices with people who are doing similar work to you and then learning along the way, and you only learn and become fluent if you practice it.

David Rice: Most people learn by doing right. My final question for you is, if you were redesigning leadership development for this era of work, what would you include that's missing today?

Charlene Li: I would definitely talk about AI fluency, and this is about knowing how to use it in those four dimensions, three dimensions, and they'd be able to teach it.

I would also include very specifically, how do you use it to become better leader in terms of expanding the scope of what you need to know and understand. How do you speed up your decision making? And then also how do you scale the impact that you have, for example, through communications. So these are all things that in the past kept us from expanding the scope of our leadership because we just only had so many hours in a day.

And if someone asked me, well, how do I have find time to use AI after my 15 back-to-back meetings all day long. I'm like, well, why don't you use AI to not have 15 back-to-back meetings all day long, first of all.

David Rice: That'd be a good start.

Charlene Li: And then use it, for example, I know one sales leader has all the transcripts from every sales meeting that the team has, and he uses AI to analyze them.

All of them to understand what are the biggest customer needs that kept coming up this week? What were the key themes that customers were asking for? What were the areas that our team was struggling with? So he could see across all of the activities, across all of the teams. He could be in every single conversation.

You couldn't do this before. You couldn't be on every call, but now you can with transcripts. And having them all in one place where everyone can see them and use them is a significant change in how you manage and lead a team. I can use AI to understand my development conversations with a team member, and it's hard to remember everything, but I can have notes that are taken from our confidential information.

Again, it's all protected. The person knows that we're recording them, but I can understand like these are the things that they've been doing. These are the things that I can now look across the past quarter and understand here are some ways that we can do development. Have a development plan that's highly tailored to that person.

I mean, all the things that we wish we could have had time and the ability to go do all these things we can now, but requires us to say how do we want to use it in our leadership capacity to help us be better leaders.

David Rice: Charlene, thanks for coming on the show today. I really appreciate it. It was fun talking with you.

Charlene Li: Thank you again for having me.

David Rice: Alright listeners, until next time. If you haven't done so already, head on over to this website, get signed up for the newsletter, create your free account. You'll be able to download all our templates, use any tools that you find on the website, so be sure to do that.

Until next time, experiment. Don't be afraid.