Why you don’t need a separate AI strategy - Interview with Charlene Li

0:00So welcome to the next edition of the Punk CX podcast. With me today I have Charlene Li. Charlene is a business transformation strategist and a New York Times bestselling author no less of actually no less than six books including The Disruption Mindset, Open Leadership and Groundswell. But we're not going to talk about those books today. We're going to talk about something completely different which you'll tell us about in a little bit. But welcome Charlene to the podcast. How are you doing? Thank you so much. I'm doing great. Happy to be here. Excellent. Now, for anybody who's been living under a rock, obviously, for the last kind of number of years, give us a bit of a thumbnail sketch on you and your background and some of the work that you do.

0:38Well, I've been a longtime analyst. I started with Forrester Research in 1999, which feels like ages ago, covering the internet. And as technology changes, I've changed along with it. So I started covering things like search and, in particular, social media. started blogging in 2004, again, ages ago, and wrote my first book in 2008, and have been writing books ever since about, not about so much the technology, but in particular, the impact on customers, and in particular, how leaders need to be thinking about these technologies and impacting their organizations in our society. Awesome. Well, books are the theme of the day, because actually we want to talk about a new book that you've uh that you've been working away on and it's called winning with ai the 90 day blueprint for success now ai is the topic i don't know if it's of the day of the month of the year or probably of the decade it will be probably the decade or probably more decades to come but and you co-author this with dr katia walsh and first of all i just want to say well one congratulations on the books i've written for myself so I know how much of an undertaking that is.

1:50But I wanted to actually just give me the quick synopsis. Tell me about the book and how it came about and why you wrote it, the main headlines as it were. Yeah, well, I was thinking about it because we could see already back in 2023 it was going to be hugely transformational. And I was sitting there talking to my good friend Katja, who I've known from Forrester for over 25 years, that said I'm writing this book on AI. And she, having been a chief data officer and a chief AI officer, said, I should write this book with you. And my immediate reaction was, of course, we have to write this book together.

2:25So two years later, we have the book. And the premise has always been the same. Organizations need to have an idea of what they're going to use AI for, and they don't know where to start. There's so much noise. So what do we do? A, B, C. How do we actually create value with AI? So we set off on this adventure to figure that out. And it took us a little while, but now here we are here. Well, yeah. I wanted to ask you a couple of things, just to dig into a few things that stood out for me in the book, just to give people, one, a flavor of the book. And, you know, we don't want to tell them the whole story.

3:01It's super nuts because, obviously, you want people to go out and buy the book. But first of all, I wanted to ask, why 90 days? That's a great question. we wanted people to get a quick head start and we've gotten pushback like that's not enough time or that's too much time and we felt that 90 days for most organizations was enough time to get some actual strategy and roadmap work done and also some detailed planning but not so much that you would fall into analysis paralysis right okay so it was a definable time and we also just know organization, it takes time for you to synthesize and figure out what's going on.

3:46So we say in the very beginning, it may take you longer, it may take you shorter, but we're going to put a stake in the ground and go for 90 days. Excellent. And so as I was going through it, the next thing I wanted to kind of call out was, so I read the line, you don't need a separate AI strategy. And I almost went, oh, kind of like, because I just thought, crumbs, thank goodness. I almost cried out with joy. I mean, so tell me, explain what you mean by that and why you wrote that. Because it's just, it's almost as a bit of an antithesis to some of the noise, as you say, that's going around the industry.

4:26You have to be this, that, the other AI strategy, AI first, AI led, blah, blah, blah. Right. And I always have believed that you should never put a technology in front of the word strategy. Right. Because it's like having internet strategy or a mobile strategy. You know, you have a business strategy. Every organization has that strategy. And the use of AI should be in service of, in support of that strategy. It's not something separate. And it feels like when technology comes into the room, all common sense goes out the window. And there's this bright, shiny object in front of us. Like, oh, what are we going to do with this?

5:04What are we going to do with this? And the best thing you can do is to stop and say, here is our business strategy. How does this technology, how does AI help us achieve the opportunities that we have, that we see in the marketplace? How does it address some of the problems and challenges? And does it create new abilities for us to go and tackle new markets? That is the way to be thinking about it, not what does this technology do? Yeah, at the time of recording, I'm about to do this talk in a few days. And it's to the kind of customer experience community. And one of the, I'm talking about two triangles, but one of the triangles that the, you know, because I want them to get to rethink things.

5:51One of the triangles is it has technology and data at their base, but experience at the apex. And I hear so many people say, now we need to be data-driven decision-making organizations. You go, yes, okay. or we need to be technology first or ai first or you know technology led business yes okay but i said the thing you need to remember both those things are inputs to kind of what is it you're trying to achieve your business outcome or your experience outcomes and and it's it just it always frustrates me how almost people get things back to front they can almost start with the data and they start or they start with the technology and then they turn the handle and and they see what they get on the back end, rather than being driven by what it is they actually want to achieve.

6:40And so I think when I read that, I just thought, thank you. At least somebody's not just banging the drum. Like somebody's putting their hand up and going, hello, no, can I have something different, please? You know, well, the thing is, this goes back to my previous book, The Disruption Mindset. And when I was doing the research for that, I was trying to figure out what was it that these highly disruptive organizations do right? that they're able to just literally see the future and disrupt themselves over and over again. And these are not necessarily technology companies. And the thing that I've realized is that they have a very clear view of who their future customer is going to be.

7:18Right. Okay. They may not be right, but they have a view and a hypothesis that this is where the customer is going. And they're chasing after that future customer and figuring out what they have to do today. and we took that premise into this book too as well just saying and we talk about the ways that you can be created with ai and we always started with the customer first yeah there's customers there's efficiency there's the potential for reinvention but you have to start with your customers first 100 i mean and that brings you on to my next question is that the you that you can talk about I wanted to kind of like dig into which is you talk about how many or most AI initiatives kind of fail and also fail to improve customer kind of outcomes and I wonder if you could sort of paint that picture for me about why they're going kind of like kind of wrong because I think there's a lot of waste around.

8:14It's so much waste and there's a couple of things driving it. It was a great MIT study that came out in the middle of 2025 that said that 95 % of AI initiatives fail. And they said, it's not about the technology. The technology works fine. The problem is that leadership has not committed to these initiatives. They're saying, let's do a pilot to see what happens. We're guaranteed the pilot is going to fail because IT is sitting here going, we don't have to take this seriously. We don't really need to change anything on our legacy system. So great, thank goodness. Phew, we don't have to deal with this.

8:49The business people are saying, well, we're not going to put significant efforts behind this because we don't have to put any serious customer conversations behind it because it's a pilot. And the people working on it like, am I going to take time away from mission critical work and make this pilot's success? No, not unless it's my baby. So there is no, no initiative, no enterprise commitment to a pilot because it's a pilot. Versus if you say this is something that's core to what we do. It's strategically important to us because our business strategy will succeed or fail if we do this. And I didn't do this right.

9:29Then it becomes an imperative to make it a success. Right. And so we like to say, don't do any more pilots. Just don't do any more pilots. Okay, so it's like a binary thing. You're either in or not. And so I wonder, Just as almost like a side question, do you think there's also an AI literacy kind of problem in organizations as well, and particularly at leadership level? I would say it's not just an AI literacy, it's an AI fluency gap. It's not enough to be literate, meaning I can kind of get around it. You really do need to be fluent and we define fluency as understanding what AI can do and also what it cannot do.

10:13Right. okay so why don't they hallucinate well it's a socratic parrot it's guessing here so if you understand it then you can approach it and use it in the right way you have you understand how to use it responsibly and ethically what does that mean what does it look like just because you can doesn't mean you should and then third thing is do you know how to use it in your job yeah to get things done and if you understand the business strategy then you understand how your job and the things that you do impact the success of that strategy. So AI will be used to support your strategy. And the bonus thing is if you can teach other people, then you know you're fluent.

10:53So to your point, I think it's so important. Leaders in particular need to get fluent. And they keep kicking it over to IT because this is a technology, right? IT should take care of it. No, if this is truly a transformational force, and it's strategic, then you have to be at the center of this. You have to be leading and showing people how do you become fluent with AI. And it isn't always pretty. Yeah, no, absolutely. I mean, so maybe it actually brings us back to maybe a reframing of the AI strategy. And the AI strategy should be a learning strategy rather than a doing strategy. Right. Right.

11:31I mean, one of the things you hear all the time is let's fail fast and fail smart. I don't know about you, but I really don't like to fail, but I do like to learn. And that framing is really different. And I hear so many leaders saying and asking me, what is a podcast, a course I can take, a newsletter I can subscribe to to get up to speed with AI? And I went, don't bother. You'll never be up to speed. You'll never be caught up because it's constantly changing. So again, I saw like a broken record, start with your business strategy. What do you need to know as a leader to be able to help you execute on that strategy, to be able to use AI?

12:10It's very specific. It's very targeted. You're not wasting your time because you just do not have time. Speed, I love this quote from Vikram Mahidar, who we quoted in the book, speed is the new moat. Right. You don't have the luxury of sitting here waiting for the technology to mature or for everyone to get up to speed on it. You need to start now and you have to learn. Experiment in real time, in public, so that when people see you doing that learning, they know it's okay for them to do that learning too. Yeah, no, absolutely. But then you talk about experimenting, but also in the book, you talk about a use case trap.

12:54And so I wanted you to explain that to me because everybody talks about use cases and i find it's a really internal kind of way of framing things and it's it's not it doesn't it doesn't really kind of speak to what happens in the real world in many cases and so can you tell me what is the use case trap and kind of what should organizations be doing instead i mean is that separate is that the same sort of thing as don't do any pilots yes very similar and akin to that because what happens is okay we need to have an ar strategy Number one, that's an issue. Let's figure out all the ways we can use AI in the organization.

13:28So everyone's picking up the use cases. They're doing this huge effort. They get a long spreadsheet of them. And then they show that to me and say, that's our strategy. No, that's not a strategy. That's a list of use cases. That is not a strategy that aligns with what you're trying to achieve and decides what you will do and won't do. That says who's going to do everything. There's no prioritization. And a lot of it is because the leaders don't want to make hard choices. Right. Because they might be wrong. What if we choose the wrong one? I don't know how to operate in this space. So what they should be doing, again, is figuring out where are those opportunities and the problems and challenges.

14:07How can AI be used to achieve your strategy better, faster, cheaper, and safer? Mm-hmm. And then prioritizing those applications of AI and then making your choices to say, this is where we're placing our bets. And I'll say the other thing is I see a lot of organizations doing readiness assessments or feasibility studies. And to be honest, we developed an entire readiness assessment. I love creating these things. I built an entire career on creating readiness assessments and we threw it all out the window because it doesn't matter because they will show you you're not ready. Well, exactly. I mean, it's almost you're kind of taking a, your assessment should be kind of that you're trying to assess something, which is a moving target.

14:53But actually what the readiness assessments do is they take a snapshot in a point in time, but then the bus is already kind of like is down the street and then turn around the corner and it's like a number of blocks away. So So I can completely kind of get that. But I think the thing that also I liked about the book is because it's like, it's not just about, it's not a theoretical sort of thing. It's like, it's kind of grounded in kind of what people are doing like now and their experience. And there's like a whole bunch of case studies and stories and examples. And one of them that stood out was this, was one by a company called sort of Connecta.

15:29And I wondered if you could tell me about, briefly, Tell me about their story and what they've done and how they've transformed their business using AI and what outcomes are going to drive them. Because I think it gives sort of an idea of the art of the possible, as it were. Right. Connected is a business process outsourcing company. About 140 ,000 people globally, but centered very much in Europe. And they run a lot of call centers. And you go, oh, no, what a potential train wreck. Because AI is just going to decimate call centers. Because it can automate all these various conversations that they're having.

16:03And so they saw AI come in and they got super excited. At the beginning of 2023, again, right when it launched, they put together their roadmap for AI. And they said, no, yeah, we can get some efficiencies here. We can elevate the quality of our call center representatives. But they said, we're not doing this to get rid of people because our problem isn't we have too many people. We don't have enough of the good people that we need to have. So they're going to elevate the quality of the calls and they reduce errors, for example, by 85%. Right. So it's just immediate paybacks. But then they also said, well, now that we have these incredibly capable people, what are the long list of things we've always wanted to do for our customers?

16:47Let's start picking those things off. Right. And so with this new capacity. And then they said, how can we get into new businesses too as well? And they realized law firms they serve a lot of, and they had this one particular problem, and they could solve that problem with them because the law firms were not going to develop AI anytime soon. They already had a lot of the information, and they said, we could do this for you. They're opening up new business lines and services for their clients. So I think it's a great example of how they moved beyond just efficiency to also think about new ways to engage their customers and then also ways to reinvent themselves.

17:25Yeah. I mean, I think there's a great, I mean, so there's two things that occur to me there. One is a recurring theme that I've been talking about over the last few months. And one is that they've taken a very, very early on, they've taken a very much as a service dividend type of approach to their strategy. Whereas rather than just taking, implementing the technology to drive efficiencies, which can allow them to save costs and maybe reduce headcount and things. And many people are going, oh, thank you very much. Put that in my back pocket and off we go. Whereas some of the more mature thinkers are going, I can use the technology to create efficiencies, to create bandwidth, to increase productivity.

18:10And then I can choose what I want to do with that freed up resource in order to add greater value. And I think that's kind of great and enlighten the position. but the one thing i also think that i think is fascinating about their story and i think it's a real opportunity for people in that sort of bpo sort of like space is that many organizations are struggling to develop this capability or its expertise kind of like in the house and whereas many of these larger or many the more innovative kind of bpos are being able to do that at scale because they're learning across multiple domains and kind of customers and if you can centralize that and then kind of reframe it and redeploy it sort of thing.

18:48There's this huge, huge opportunity there for the right sort of people. Right. And I think, again, this takes somebody who's thinking strategically about the business and about their customers. And they're not sitting here looking at a spreadsheet to say, how can I use AI to gain these efficiencies that go down to the bottom line? Again, you can do that. And I think you're shortchanging what this technology can do. truly impact that experience that you're creating for your customers and your clients. So again, I thought it was amazing to hear what Connected was doing so early. Again, this is 2023.

19:26And again, it keeps just pushing that edge. And what we saw consistently across all the case studies is that people were very much focused on how do they improve their experiences? How do they think about their business differently? they're looking at it again even for efficiency they're using it not to just cut costs but efficiency can also be very strategic so they're looking at these things from a strategic point of view rather than just saying oh how do i move the bottom line by a few inches yeah i mean i'd go so far in this kind of era to say if you are if you're ultra focused on managing your margins then i'm I'm going to say that you possibly don't believe in the longevity of your business.

20:14Yeah, exactly. And the market tends to want to support that, right? Because we reward quarterly results. And it takes a really strong leadership team to say, okay, quarterly results are important, but we can also tell a longer term story about where we're investing and where the future is going. And that takes a really strong leadership team to do that, to consistently do that. Excellent. so one final question uh on the on the on the the the book is you talk about the five traits of an ai ready culture and i wonder if you could briefly kind of like describe those to me because um i love a checklist and is it if you've got five things you go like yes no oh no no yes okay maybe so yeah give me the give me a brief a brief kind of synopsis of the five traits if you will Sure.

21:05The first one is speed. Okay. So you're agile. Can you, do you trust your decisions at speed? Focus. So avoiding distraction is focusing on what's really important. Customer centricity. I think you'd like that one. Lifelong learning. Right. This is commitment to experimenting. And then the hardest one is continuous reinvention. Right. The idea that you're going to challenge assumptions and constantly ask why, that you're iterating and improving. so those five things are the foundational traits of an ai ready culture yeah and i like the the continuous kind of reinvention because i would link that back to kind of customer centricity and it's also something that you said to before is like if you stay close to your customers and also start to follow kind of behavioral kind of trends and changing preferences and changing demographics and all of that sort of like good stuff you start to reimagine or imagine what the what your customer of the future is going to look like, then you can start to always be thinking about, well, what does that business need to look like in order to serve that customer of the future as well?

22:09So, yeah, no, I like that. It's all connected. Brilliant. So, Charlene, I hope that's given people listening in a flavor of the new book. I mean, yes, it's very practical. It's 90 days. It's all about getting clear on your thinking. But is there anything I've missed out that you'd like to add or highlight before I can ask you some quickfire questions to finish off? I think that the one thing I would say again is that it's going to feel really uncomfortable. But I talk to most people that are saying, this is really hard. I don't know what I'm doing. And I'm like, you know, you're doing it right though, if you are feeling uncomfortable.

22:50And so the new skill we have to learn, and actually what we have to unlearn, is that we have to have all the answers before we can get started. And the new skill you have to have is how do you ask great questions instead of having all the answers to help you get to the answer and help your team get to the answer collectively. Yeah, absolutely. That's a brand new skill that we in the past haven't really had to really pull on. Yeah. I mean, domain expertise has taken us a long way, but we almost can't have that sort of domain expertise because the domain's kind of changing so fast and therefore you've got to be able to sort of rely on people to give you the answers.

23:27And you end up having to be in many ways, particularly at a leadership level, a proper leader where your role is not to be the most skilled in the room, but the person that can guide and get the most out of things. And that's kind of where, yeah, that's a real challenge for many people because it's not necessarily the culture that we've been raised in. we reward people having making good decisions and right having the right answers we reward being right a hundred percent of the time and so we don't dare do anything if we're not a hundred percent sure it's going to be successful yeah and and that has served us for a very long time but now is not the time to necessarily be a hundred percent right because there's it's just impossible yeah and especially when domain expertise is being done by this ai tool you can just go into it, it just gives you the answer.

24:23But it can't ask you the really tough questions that no one else is asking. And that is the role of a leader. Yeah. There was a piece of research that I saw that was conducted by a professor, I think it was Northwestern or Northeastern University called Dr. Paul Calagheri, and looked at some of the soft skills that leaders are going to need to develop to thrive in the future. And the top one that came out of the research was this idea about curiosity. About being, people understand, pretty much everybody agreed. They also pretty much everybody said, yes, they agreed it was important. But the problem that they had was that they found it really, really hard to make time to develop that sort of almost a more curious kind of mind or to go and find out kind of things.

25:25And it seems to me that that is more of a challenge of self than anything else. Like how you manage your time, how you manage your mindset, how you manage how you view things and how open you are to some of those things. So I think the challenge is very simple to leaders. It's very doable, but sometimes you've always got to take control of your own environment and your own time and your own focus rather than getting caught up in all of this other stuff that keeps the treadmill running. Absolutely. Perfect. Perfect. So Charlene, a final few quickfire questions before we can like wrap up. So the first one is all about best advice.

26:14And what I've been doing or what I do is to ask people to boil it down by asking them to complete this sentence. And the sentence is, if you want to improve your customer experience, Charlene says, do this, dot, dot, dot. Complete that sentence. Get your workforce AI fluent. full stop full stop I mean what excuse do you have right what are you waiting for and all the materials are there educate them on how to use AI responsibly and ethically show them how it can be used and those two things can be done from the top down but the third part of fluency is how to use it in your job so give them the tools give them the freedom give them the time to experiment and use AI to do their job better.

27:05What I hear from organizations is, yeah, I know we should do it, but we've got all these other things we have to do first. And again, it is not a priority. So I'll say this. I challenge you to get your workforce AI fluent in the next three months. What would it take? There you go. What training would you have to have? What ground up frontline, online peer-based experiences which you want to create. All the people who need to and want to get fluent with AI, you got three months. It's not training everyone, but it's saying for the core people who are going to truly drive your business strategy, you want to arm them with AI and truly make them not just literate, but fluid.

27:50And you've got three months to do it. What are you going to do? How are you going to make that happen? Charlie drops the mic and then walks off stage it is completely 100 % under your control you already know that technology is not going away it's not going to change that radically I'm not even talking about using agents I'm talking about just the fundamentals of how do you use AI in a thoughtful advanced way where people feel like I'm confident about my ability to use AI. I'm not fearful of it anymore. I know what I can do with it. I know what it can't do. And I'm looking around me and my peers also do the same thing with me.

28:34I think the last part that you said was I think it's really important is that I know what it can do and I know what it can't do. I would perhaps add to that and say, understand what you gain and also what you give up within that as well. So I see too many people that are giving up critical thinking to some of these kind of tools, and it should be more a thinking aid rather than a critical thinker for you, as it were. So don't arrogate responsibility for critical decisions to these systems. The decisions are still your responsibility. And having the ability to think and think critically is important.