Driving AI Success: Leadership Strategies from the C-Suite

This is Chuck Reynolds. I'm a Managing director and leader within LEKS Digital and AI Practice. I'm joined by Chris and Surabhi, whom I will allow themselves to introduce themselves in a moment. But we're very excited to have this conversation today around driving success from the C-Suite and the role of leadership in enabling AI value.

So I will, you know, first pass it off to Darren and then Surabhi and Chris to introduce themselves, but very excited for the conversation today. Great, thanks, Chuck, very nice to see everyone and obviously great to see Surabhi and Chris. As Courtney and Chuck mentioned, my name is Darren Perry. I lead LEK's digital service line, which means I have a very fun job of getting to partner with clients and, and helping them solve some of their most challenging digital needs, whether that's strategy and transformation and, or related to customer experience or new product, or, you know, working through operating model choices to really achieve the full benefits of digital.

And of course, as we all know and can imagine, AI has really been front and center in all of those conversations over the last 18 to to 24 months. It's a little bit about me, but you know, one of the best parts of of my job is really getting to work with talented executives like the two of us that we have today or the two that we have with us today, Chris and Surabhi. So I'll hand it over maybe to Surabhi first introduce yourself and then on to Chris. Awesome.

Thank you, Darren and Chuck. Great meeting you here today and thanks for the folks joining for this webinar. My name is Surabhi Pokhriyal. I'm the Chief Digital Growth Officer at church and Dwight, we are a mid size consumer goods company with brands.

I'm hoping all of you are very familiar with brands like Arm and Hammer, Trojan, Waterpik, Batiste and most recently Mighty Patch Hero. So I leave the agenda, all things e-commerce and P&L associated with that as well as digital marketing and transformation, be it media optimization or newer areas now like AI. Look forward to the chat. Hi, good morning, Chuck and Darren.

Thank you for having me. I'm Chris Dill, I'm the Chief Information Officer for Kiewit Corporation, a brand that maybe many of you don't know, but we're a large construction and engineering firm headquartered in Omaha, NE And we build large capital projects, you know, some you would never hear of and, and some pretty high profile you can track along as we rebuild the the bridge in Baltimore. That was big news in the last few months. Those are the kinds of projects that we design and engineer and, and build.

And I'm very excited to be here today to talk about the digital side of our business. Surabhi, Chris, thank you so much for joining us. You know, obviously we've had a, you know, numerous conversations around the role of the C-Suite and how you both are really driving value from deployment of AI and, and a setting the AI strategy.

You know, in addition to the conversations that we've had, you know, Darren and I have been working with clients in, you know, enabling strategies, executing those and really building the transformation, the AI transformation with our clients and, and driving, you know, enabling value creation. You know, one of the key things that, that we've done in addition to working with you all is really we, we talked with 150 of our, of your peers. We, we surveyed them. We, we discussed kind of what, what is changing for them and, and how are they really building value for their organizations.

And Courtney, if we jump to the next slide, one of the key things that we've done is really build an understanding of how are they, how are executives tying AI strategy to business outcomes. And one of the questions that we really we posed was how are functional leaders, CDOSCIOS building AI strategies to and tying those to business objectives. 62% of executives have actually tied an AI strategy to the, to business objectives and really not viewing AI as a, you know, an enabler, but rather viewing AI as the, the path toward growth for organizations. Additionally, you know, what we we also asked was how are executives approaching AI transformation?

Do they view this as just another IT tool? Do they view this as really transformational for an entire business or an entire sector and 64% really believe that that AI has the potential to fundamentally transform an entire business. All of this is, is good backdrop and Surabhi, maybe I'll ask you first, but you know, first and foremost, AI is a business issue and and really we have to understand how AI is enabling our strategy. So why do you believe that having a clear strategic vision is so important to really enable AI transformation?

100%, Chuck, I'll just rephrase that to say AI is much of a business opportunity than a business issue. But you're right, right. I get the context of it. It's definitely a catalyst in the sense it's the technology that enables a lot of outcomes.

I would say strategy, just like the word conveys, is about choices, right? What do we want to do and what do we not want to do? It's about what you say yes to and what you say no to. The fast pace at which AI has become democratized, right?

What we call the S curve of adoption and technology has been outrageously impressive. I'll share a personal anecdote. I learnt of AI on November 30th, 2022. I remember the date because later everybody said that was launched but my then 13 year old was doing homework using ChatGPT and I did not understand the enormity of it till two weeks later when I started following all the LinkedIn articles and newspapers.

But that anecdote goes to say, just like the cell phones, AI is so democratized and so self propagating that it is no more a novelty, but it is a norm, which is why for enterprises, businesses like ourselves, it's a strategic choice of how we use it. Because just like in innovation and product development, companies should not be innovating when they need, companies should be innovating when they can. So this is that moment that we all across corporate should be innovating using AI now versus having to do it when it's too little, too late. So back to the strategic choices, I think be the choices on resource investment, tech investment, clear definition of use cases and so on.

All of those I would say are the business blocks. And just like anything else, this is a choice we cannot ignore right now. Yeah, I, I think that's absolutely clear. It's a choice on where and how we're going to invest.

I don't know, Chris, you know, obviously, you know, Surabhi sitting within a CPG business and you building bridges, you know, have a different view. But I, I wonder how you kind of think about AI as a strategic enabler. Yeah, I think the first thing you have to think about is, is, you know, what kind of, what kind of business are you in? What kind of industry do you serve?

And, and, and pragmatically as much as strategically, what are the opportunities in your business for, for AI to, to make an impact? And, and I think, you know, for us, I, I think about not only the opportunities for our business, and there are many, but you also think about the challenges that it might address. You know, we're in a business that is increasingly harder to get enough of the skilled labor to do what we do. And so to the extent that technologies like AI can help us do more work, scale our work without necessarily having to to scale, you know, human beings on a linear basis, that is potentially extremely impactful to our business.

Not because we don't want to hire people, but in many cases we just simply struggle to find enough of them. And so can it be a bit of a force multiplier in our business to help address those kinds of of, of challenges so that we can get to the opportunity. So I, I think that awareness of, you know, AI is not some cookie cutter thing that you can just spread on, on any business and magic happens. I think you have to understand how it applies to your business, your industry, and then make smart choices from there.

You know, it's interesting, Chris, you mentioned that you're in the business of building bridges and people and enabling people to and skilled labor to do a job, yet you're here talking about AII don't know, how do you kind of view and Surabhi I, you know, really love your view as well with with and as you kind of sit more in a digital channel perspective, but how do you both kind of think about the strategy of AI and how do you apply it to enabling your strategic objectives? Well, I think for for me, you know, the, the first thing maybe is what, what we didn't do, which was overreact. You know, as Surabhi talked about, the, the hype has been intense around AI the last, you know, certainly 18 months, maybe 20-4 months. I think there was a on one hand, that hype led to a lot of a lot of noise and and excitement, lots of CE OS calling their CIOs and their chief digital officers asking, you know, what are we doing right? Which I think led to a a perceived pressure to act. And I think some, some of that is now becoming clear that that those early actions were probably, if not outright misguided, probably didn't, weren't based in, in good logic in terms of, you know, are we going to get a return on that investment?

Is it going to have the actual impact that that, that we expect? And so I think, you know, the first thing for me was a bit of a pragmatic approach to step back and say, OK, we're not going to act based on a fear of missing out. We're going to think about how this might actually impact our business in, in important ways. And, and then, and then take the time to try to marry up the, the right solution sets to those opportunities.

And, and so, you know, I, I think, and then, and then work that into a strategy. And, and, and again, I, I, for us anyway, it wasn't like that was a one year strategy and, and it was all going to be done. This is a, this is probably a how we do business going forward or a part of how we do business going forward. And it requires a long term vision of, of how you're going to continue to evolve your business with AI as, as an enabler, as a, as a, as a tool, right.

So, yeah, I, I, I think, you know, pragmatism, I talk about that a lot inside of our company. And I think it's important. It doesn't mean you can't act with urgency, but but it, but I think it, it does help stop you from acting out of out of fear or pressure to, to get something done. 100% Chris, I love that.

Right. I was going to say, just like you said, it's not a cookie cutter answer. It's not a solve for every problem within enterprises. Many times we might notice that AI becomes the hammer looking for a nail like we have a solution.

Now let's find out what the problem statement is. And I think you stated that beautifully because the longer term objective of every company is generating higher revenue, better profit and making our stakeholders happy, consumers included. So if that remains the North star in the business goal, AI becomes one of the tools and technological enablers to do that. But one thing I noticed, right, it's beyond the former part that you said.

It was a shiny thing in the 1st 612 months and everybody was keen into it. But I think it also enabled people to be more curious and sometimes move fast and break things, right? There were lots of conversations like should we have Mid Journey or Perplexity or Lamb or Gemini, the 10s of models that are floating out there? What access should we give to our teams?

What is clean room access within the enterprises ecosystem versus what can you access versus your personal Gmail or Yahoo and so on and so forth. So I think a certain degree of FOMO helped, helped democratize the curiosity across the ecosystem because it was not something that only the CIO or CDO could experiment with. It was something every business function could experiment with. So, you know, back to your point, Chuck, I think every C-Suite leader today having dabbled in it in some way, either directly or indirectly makes more accessible.

And hence people are logically understanding by having a business case, which is which can be initially say productivity savings, time saved, you know, man hours saved, more efficiency. Eventually we will go towards the path of efficacy. But right now it's still, you know, the novelty factor makes it more obviously productivity savings. And in the long term, we'll have more strategic outcomes expected.

Yeah, Surabhi, go ahead there. No, sorry, just to to jump in here, I'd love both of those answers. I think when I think about for the strategic, we're looking at AI through a strategic lens.

I typically think of three things and the two of you just hit on the first two of them. So you left me space for the last one, which is great. Obviously, it's a resource allocation problem and the scope of AI is so huge and we think about strategies resource allocation issue. This fits perfectly into that.

We also think about strategy is, you know, how you think about your fundamental approach to value creation and which cost levers or revenue levers can you pull. AI is unique in the breadth of levers it touches. But the third, the third way that I think about AI through a bit of a strategic lens is that strategy is about competitive positioning, of course, and where can you create sustainable competitive advantage. And I think AI is, you know, pretty unique relative to prior waves of digital transformation in that there's so many different ways that you can create advantage.

Or maybe on the flip side, an upstart or a competitor can create an advantage for themselves, whether it's driving low cost, speed, customer service, product differentiation. But of course, it's really hard to do all of those things, which is where strategy comes into play. You have to pick and choose. So I would say those are the three lenses that we typically look at it from as a, as a, as a strategy problem.

And Courtney, maybe just to continue on that team, if you flip to the the next slides, obviously we're talking about having a strategic vision as being particularly important in setting your organization on a good course for AI leadership and and success. Not just the four of us who believe that Chuck and I and our team have actually done some work with the last couple of months, gathering input from 150 different C-Suite executives around the globe, different industries, different functions on their team, mostly tech leadership, CDOSCIOSCTOS, chief AI officers, etcetera, all of whom are down the road with their AI strategy and, and AI implementations.

And we, we tried to understand from that, from that audience a little bit about where their priorities are. What are they doing, maybe what they're doing differently and specifically what those who maybe are seeing earlier success are doing differently than those who are maybe struggling to see the returns that Chris talked about ROI. So this page, this, this question specifically was aimed at asking what makes you ready for AI transformation? What are the most influential factors driving that readiness?

The Gray bars is the total sample. The green bars are those who claim to have had some success and early returns with AI, and the blue bars is is everyone else. And so there's some interesting things that jumped out at US. You know, 1 was the fact that there's some common hurdles here.

And whether you're a leader, a follower, somewhere in between, you're facing common challenges, whether that's the data availability and quality, the technology and infrastructure or the budget and resources. Those are common issues for for every firm that are that's facing this. But the thing that really jumped at us is different is those firms that are having meaningful success and and seeing those early green shoots are the ones who placed the priority on that strategic vision and really saw that as the key enabler driving readiness almost by a 2 to one margin versus others who who aren't seeing some success.

So this, you know, gives us a lot of, you know, confidence in, in, in that claim that having that strategic vision is, is just so critical. One of the other things that jumped out at us in and looking at the data here was that more than 65% of the respondents in this group of 150 told us that their firms weren't ready for AI transformation. And we found that pretty astonishing given that this is not our first rodeo. We've been through multiple rounds of digital transformation, whether it be the Internet or e-commerce or the app economy or IoT, you know, you, you name it.

So it was pretty astonishing to us that, you know, 65% claimed that they weren't ready. Maybe to that point, Chris, curious to get your perspective, what do you see that's fundamentally different about this wave of transformation versus prior waves, whether they be, you know, process automation or e-commerce or, or other things? What's fundamentally different about AI that's making it so hard for, for firms to get off the ground? I, I think in, in some ways Surabhi touched on this.

I think in some ways, the, the, just the, the broad applicability and the, and the, the democratization of, of AI, especially generative AI, obviously with chat GPC and Copilot and others. I, I think I could see firms struggling with how to get their arms around that and gel that in just into a cohesive strategy. Because in some ways it kind of got out of the barn before you had a chance to stop and think about it. Anybody could go out & up for a ChatGPT license and, and off you go, right.

And so, you know, we, we certainly in our business had had people in, in certain groups and departments that were utilizing it before we had a chance to even think about things like, you know, putting some governance around it or having a, a smart strategy. And, and so I, I think that's, I think that's one thing is, is it was so broad. You know, I, I have, I've made the comparison. I'm old enough to remember when we put our first corporate Internet connection and in my career and and I've made that comparison, except that was a fairly narrow and controlled thing, right?

I mean. Nobody got access to it until we gave them access to it. And and it it required a browser and and as the IT group, we, we would give you a browser if we wanted you to have one. This was just almost instantly available to anybody with that, that that wanted to go out and, and start playing with it.

And so I think, I think that might be a one big component is just, it just got out there so fast and, and especially technology people like to like to have a little time to think and, and plan. And it just didn't afford very much, very much of that. And, and, and it also immediately called into question things like not only your data availability and quality, but what data might that access that you don't want it to right. Do you have good, good data governance inside of your organization to protect the stuff you want to protect and, and expose the things that you're OK exposing?

And so I, I just think there's a whole bunch of factors that made it uniquely challenging maybe versus some of those other kind of, you know, digital leaps that we've dealt with in the last, call it, 25 years. Yeah, I think we're seeing much of much of the same. I don't know Surabhi or Chuck if you see the world differently, are there other other things about AI that you think make it unique relative to prior transformations that are making it so challenging? I'll, I'll share some anecdotal examples which might be relevant and along the lines of what Chris was saying, right, because it is so democratized, the easier use cases are very fast to adapt to.

I can figure out a four day vacation in Italy. I don't have to Google search and tap every link because search labs give you a summary of what generative AI even means, right? You don't have to do all of that at the same time for organizations and large companies, it's hard to figure out the output metric of your strategic vision and connected to all the put things right, Everything that you have on your chart here, data availability, integrity, tech budget, this is all input metrics. So it's very hard to connect the dots, which is why a lot of companies are now in the phase of collecting the dots.

Let's just get all the data. Let's just make our data lake more robust and bigger and more efficient. Even though sometimes we may not know what exactly is the end goal we are shooting towards, which is why I think there might be nervousness because we are in these squirrels gathering acorn mode. And I speak to corporates and right, data gathering mode without 100% clarity on how might that impact the strategic vision and business impact.

Because it is relatively easier to, you know, use chargeability to help your PowerPoint look pretty and make an itinerary for your business trip. But it's substantially harder to figure out what prompts are needed to make your social media content much more effective. So it sticks better, so it generates better conversion and hence it generates more e-commerce sales. We are on that path today, right?

I'm happy to say that there are use cases like that in content and social that we are already experimenting and that's the kind of broader use cases we want to do more of. I think you hit on a really interesting point, Surabhi and Chris you as well, But the the fact that data is such a requirement for AI and I wonder how do you both view data as an enabler for your AI strategies? Are they, is data as a separate strategy? Is it embedded?

How do you how do you think of that as a barrier or an enabler? Surabhi, you want to take a shot? Sure, I'll take a shot. I would say that's almost like, you know how we don't say it's a colour TV anymore, it's ATV.

We don't say it's a digital camera, it's a camera. I think data just is so inherent and such a catalyst in making this happen that it's almost a moot point to say. Do you have the data integrity? Again, the conversations can be around internal data, consumer data, data from your customers, B2B and all of that, but that is almost the foundational layer.

Otherwise IT comes as a smart way to get answers to to problems for which the data doesn't exist in your ecosystem. So I would say it's a fundamental enabler right within your bars. Here you have it rightly pointed out, it's not just about availability, it's also about the integrity and quality. An example I would give is you would not go and use first party data from sweepstakes customers and go after them to say, Hey, would you like to buy my product?

Because, you know, their intention was to get a sweepstake of $5 off while doing that. Spin the wheel, right? So you just have to understand and narrow down where your data comes from and what was it intended to have before you start tying the business use cases to it. But I'd say it's, it's a very the the day is silent.

You know, just like digital is in the air, data is in the air. I was surprised to hear we have titled like chief AI officer. I'm hoping that becomes redundant in the next few years. Not to say people's jobs should become redundant.

It just should be so, so embedded in the ecosystems that you don't, you have a chief electricity officer at a factory, right? It's so embedded in the corporate world. Surabhi, if I just jump in on that point about the data being central to this, I think another aspect of the challenge here is it's a cultural change. It's a DNA change.

It's a big mindset shift to think about data as a strategic asset and we think about realizing the promise of AI. You're thinking about a world in which both the CFO and the hourly employee on the shop floor are thinking about data in a similar way and how you get an entire organization to move in that direction doesn't happen overnight. That's a massive change management problem. I don't know, Chris, if if that resonates with you.

Well, it does I mean, I think, you know, one of the things this has done, you know, Surabhi talked about, you know, it's data as an asset. It's it's just almost a given at this point. But, you know, not only did did AI or has AI democratized kind of equal access for everybody in terms of utilizing again, especially like gen AI platforms, but it's also largely democratized data science. I mean, you know, three years ago, we, we had, you know, that was a specialty, right? That that was a that was a high end skill set. And not that it's not anymore.

I'm not, you know, deflating data scientists. However, those tools have have made it possible for folks that have that that are not career data people to do data science as long as they can get access to to the data that will enable them to do it. And I think that alone has made us think much differently about how we value and manage our data inside of our organization. How do we make it available?

How do you, how do people know they're, they are accessing certified data sets versus just copies of copies of copies, right. All of those things have, have have bubbled to the surface in the last year because of, of this AI rush that we've kind of experienced that we just had had more control over, frankly, in the past because the number of people that were, were capable of, of doing something with it. What's what's much smaller. And so I think, you know, you can just kind of pull the string in all kinds of directions and talk about, you know, how does it make you think differently?

Well, those are certainly some that we've, we've had to deal with inside of our organization. I, I, I think that's such a, you know, an important point. You know, what's interesting to me is that none of us have talked about use cases and, and none of us have said, hey, for AI, we just need to find the next tool, like the next problem for it to solve. We've talked about the strategic vision, we've talked about data, we've talked about value creation, but not, not yet use cases.

And one of the things too we've talked about is how in past transformations, IT and digital has really been a an enabler to kind of execute, right. I wonder how have you both and maybe Chris to start with you, but how have you both thought about the evolution of your role as you know CIOCDO and what has it has evolved for leadership in the C-Suite relative to AI? Yeah. You know, I talked a little bit about this before.

I find myself increasingly in an interesting position. On one hand, I'm, I'm an AI champion and, and, and maybe subject matter expert inside of our organization and, and I'm kind of relied upon to, to be that. And on the other hand, I'm, I'm the voice of reason and, and the pragmatist inside the organization saying, no, we shouldn't just run around and do stuff so that we can say we're doing stuff with AI, right. And so I, I, you know, at times I'm, I've got kind of the whip in my hand and I'm trying to get us to move faster.

And at times I've got the reins and I'm, I'm, I'm pulling on it. And, and you know, my job is to find the right balance between those those two things because I don't want wasted effort, but I also don't want missed opportunity. And so I think that that's one interesting way my role, I think has evolved over the last couple of years is trying to balance those two things and make sure that we're being smart about how we approach this, that we have a real sense of how to get value from our efforts in the, in the realm of AI. And again, not get worried about sort of that fear of missing out or, Oh my gosh, somebody published an article in our industry and are we behind and should we go faster?

And, you know, so I, I think that's one interesting and important way that my role has changed. And, and I, again, when I think back the prior, you know, digital transformation efforts, I don't know that I had to, had to balance it quite the way I do with, with, with AI, right. And then, you know, I think, I think this requires a much tighter, not that my job didn't all along, but a much tighter integration with our business to make sure that I'm helping them understand that the potential and helping them see opportunities and potential use cases, right. And, and some of that's not hard.

I mean, I, the way I've tried to gel this for, for our executive team is, is I think about AI opportunities in three buckets. 1 is personal productivity enhancement. There are lots of roles that you give them a ChatGPT or a copilot or a generative AI and they're going to find personal productivity gains just simply by having that tool set. Now you got to train them how to use it.

They got to know how to talk to it. So it so you get value back out of it. But you know, people who write proposals for US marketing, there's lots of roles that get personal productivity gains that to me, that's one important bucket. The others on the other end of the spectrum, one one of the others on the other end of the spectrum, which is, is deep analytics and data science and what are the insights that AI can help us gain that we either wouldn't have gotten to ourselves through traditional methods or, or we, it would have taken us a very long time to get there.

And, and AI just, you know, kicks that into OverDrive. That's on the other end. The most challenging one for me, I'll be honest with you, is sort of the, the, the territory in the middle, which is how do you transform your operations? How do you change, you know, how you do what you do in your business?

And I think that's the hardest thing also for our business people to get formed in their head is, is, is how to identify those opportunities where AI can have an impact in our actual day-to-day operations. And I think it's because people, so many people, when you say AI, they think ChatGPT, right? And, and generative AI is but one flavor of many and, and, and so helping them understand that there's many, many AI empowered tools that we can apply. And I will also say one last thought here.

AI alone solves very few problems. AI in, in, in conjunction with automation, with process transformation, with orchestration, right? That's probably where the big movers are going to come is when you pair AI with other technologies, other solutions. And again, I think right now that's a little bit hard for, for non-technical people to wrap their head around.

And so, you know, I've just got to take people down down the path on a journey. And, and my job is to help them, help them see it and then help us get there. I don't know, Surabhi, if you felt stiff your role or things have changed now. Very similar to what Chris was saying, right?

I'll, I'll just say to me it, it seems like a moment where we are beyond the linear impact of AI. They're starting to get into the non linear impact, right? Like Chris was saying, you can go from personal productivity against to enterprise wide initiatives. And I think a lot of us are in that journey.

Yeah, I started with giving a lot of data, which I call trivia, right? Data for data, sex is just trivia. But now AI is starting to enable us using that data to go towards insights and then towards actionable insights that then make a significant impact of the business problem. So I'm super excited about teams that have a bold division to what the outcome should be.

And then teams were flexible on the details, right? As long as the end outcome exists in terms of business impact, we can flex on the details. It doesn't matter if it's mid journey or ChatGPT or perplexity or an in house ingrown toll, as expensive as that might be. Yeah, I think that's really interesting.

Both of you made the really pointed point and if we go to the next slide, which is as CDOSCIOS and functional leadership roles in the past, you know year things have changed, right. They've you you've had increased influence, you've had an expanded responsibilities. To your point, Chris, I think you said the CEO calls up and says, hey, what are we doing with AI? But that doesn't create value.

That's all, that's all input things to Surabhi to your point and next year it's all about increase collaboration with executives. And this is exactly what we've, what we've heard and seen, you know, with our clients and in conversations that we've been having as well is that this isn't ACIO or CDO problem, this is ACEO problem. And and it's, it's that strategic vision that really in enabling that collaboration going forward is so important. I don't know, Darren, if there's, if there's other thoughts there.

Yeah, No, I, I think it's been well, well said. I think actually maybe Courtney, if you move to the next slide, try to tie this together a little bit. You know, we're, we're hearing a few different themes here, Surabhi and Chris and Chuck echoing these. I think, you know, as you think about getting off the ground and setting yourself up for success, there are, you know, at the highest level three very important things to, to keep in mind.

One is obviously setting the agenda and, and vision because we've, we've touched on here is that really provides, you know, both the focus and the inspiration for the business, you know, as it embarks on the AI journey. Second is really the alignment piece which we were just touching on that, that point about collaboration across the C-Suite, you know, bringing the the commercial and operational leaders to the table with technology leaders so that none of them have to go it alone and together are able to sort of meet that challenge, find where the real value lies, etcetera. And then lastly, we talked about the, the primacy of data, building the foundation, investing in the data, whether that's the the gathering, cleaning, the governance, etcetera.

We know that that investment needs to be made as that's going to be central to any AI success down, down the road being cognitive of time, because I know we want to open it up for some questions from the audience. Maybe I'll just focus on that first point about setting the agenda and vision. Curious to know, Surabhi, maybe to start from your experience, we've talked about strategic vision a lot today. In your mind, what does a good strategic vision for AI entail and and why do you think that?

Sure, as you all might have noted, I love giving parallels and examples as a way to communicate because English is not my first language. You know, just like in HR function culture and imperatives for DNI are not a CHRO problem. That's a CEROCEO ambition and a board ambition. So similarly, right, setting an agenda and vision for AI or technology or digital transformation is aceo imperative like it is for us.

So I think that defines a lot of things people like Chris and me and a lot of peers including you know you Chuck, we are just at the tip of the spear because we have the opportune moment to be exposed to these technologies in at the front runners. That doesn't mean we are enabled or have the full knowledge of the business imperatives to run with that whole hog. So I think that is shifting like it showed in your previous graphs. The novelty to norm shift is happening because now it is enterprise wide priority.

We are not just aligning the business, the imperative are getting burst in the business like the Chief supply chain officer has asked out of what are the three things AI can do to us? So it's pivoting from what AI will do to us to imperative about what AI can do for us. And I'm super excited about that kind of thinking. Excellent.

And, and Chris, what's your lens on this in terms of the, the strategic agenda and and vision? What does what does good look like in your mind? Yeah, I, I think, you know, so clearly we're a, we're, we're a not a high tech company in terms of the industry that we, we serve. We're a construction engineering doesn't mean we don't use a lot of technology.

But, you know, I think our CEO did a couple smart things. 11 is he knew he needed to set the tone on this topic, but he also knew he wasn't going to solve it himself. And so he, he made it known that it was a priority and he and he effectively set a North star for the company, very high level vision of what he thought AI could, could do in the long term for our company. And then he and then he created a four, four person executive panel to guide the actual efforts going forward.

And, and, and that we just met yesterday. And so it, it continues. And, and you know, I think, I think the, the wisdom there was knowing that he needed to, to show the way and make it a priority, and also the wisdom to know that he wasn't personally going to drive it. It's not what he does.

He, he, he runs a construction company. He's not a, he's, he's not a technologist, right? He's not a data person. And so I I think the lesson there is even in non high tech industries and companies.

Just simply saying this is important and, and here's my, my vision at a very high level for how I think this might impact us or have the, the potential to impact us in, in important ways. And then assign some people who can go execute on that vision and make sure that, that, that activities are, are aligned and, and reviewed and, and prioritized and all those things. I, I just think that's a good road map. It's not the only way to do it certainly, but, but I, I think for us, it's worked.

And I think it's a, it's, it's something that fairly easily, easily could be replicated by others. If you're just struggling to know how to get started, Chuck, anything you'd, you'd add to that maybe before I open it up to Q&A. No, I, yeah, I think that's, that hits on the points. I think setting that strategic vision and aligning with the executives is so important.

So, so as to the point about AQ and A, we've had a question come in here that says, you know, you've mentioned quite a lot that has to start with a strategic vision, which of course is the the realm for the CEO. So the CEO needs to be deeply involved, but can a CEO actually be sufficiently deep on AI to be effective? I think we all recognize that challenge. What are some practical ways that CEO's can be helpful in driving success?

Surabhi, what have you seen practical ways that CEO's can be involved in driving success here? Sure. I believe being curious is is almost a given, right? That is a catalyst for anybody in the C-Suite, not just the CEO.

So I think like Chris was saying, right, CE OS do us a great service by, you know, staying at staying at the tip of the spear in share groups and forums. And they bring back the information beyond the curiosity. I think asking questions that are relevant and thought provoking for their teams that make their teams pause and think and reflect and do do two things right, do things differently and do different things. What I mean by that is it makes your team give them a force function to experiment without having the FOMO hat, but just to dabble in different things and and be curious, but also be open to discard old processes because a big imperative of AI is not just generating new outcomes, but papering and editing the business processes as they exist today.

So I think the CEO also gives people the liberty and autonomy to say, move fast and break things and be OK to challenge the status quo in a certain degree. And there are always people like Chris and me who will, you know, like he was saying, we'll use the web, but also keep, you know, leaning in and making people slow down if needed. Yeah, I think, you know, our, our, our organization, I suspect is like many, you know, our company moves on, on the words of our CEO when he says something's important or is the priority, the organization responds. And, and so I think, I think just the act of showing interest of of verbalizing the fact that this is important that that he believes it's a strategic, potentially a strategic advantage for us in the, in the industry that we serve and the challenges and opportunities we have.

I think that alone is a huge thing. Just simply saying it out loud and saying it fairly often and showing interest, that alone creates energy and, and creates action inside of an organization like ours. And so I think that's big and I think it's it, it if on top of that, they can, they can articulate a vision, even if it's a very high level vision that helps channel those efforts, then even better, right? Because you want people to take action, you don't want them to run off in 50 disparate directions trying to take action because there's nothing to channel those those efforts.

So I think the role of the CEO, their, their, their personal ability to do deeply talk and act AI is probably much less important than their ability to move the organization with, with their words and actions in terms of setting priority, letting people know it's important, letting people know they have a vision for how it may impact your, your, your company, your industry and, and then channelling those efforts accordingly. Yeah, I, I think that's really a, a very valid point. I know we're at at time, but another question that came in that I think is really interesting. And I'd love both of your thoughts on which is where are executives not focused on AI today?

What's the biggest blind spot that we're seeing that people really are missing in terms of what the potential is for value creation? I, I'll take the crack first. I, I, you know, I, I talked about, you know, kind of the three, the three big buckets of AI opportunity. And, and I would say, I, I said it earlier, I'll say it again.

I think where we are the most challenged is that that sort of business transformation opportunity. And I think it's, it's a couple things. One is lack of understanding relatively right now. And two, it's these folks are trying to run a business.

I mean that they're they're, you know, engulfed in their day-to-day and they're trying to to run the business as it is today. And it's hard to stop and think about, you know, business transformation over time and the efforts that might require and how to plan for it and think about change management, all of those things. I think that's where my speaking for myself, that's where my influence will be, will be challenged and where the greatest opportunity is for me to influence the organization is to help them understand how we can get started and then how that might play out over time. What are the key things to to to be thinking about it, considering and it and it is definitely not just technology. It is change management, it's reskilling people, it's process transformation on and on and on. It's it's AI in conjunction with other technologies. So, yeah, to me, that's that's the, I don't know if it's a blind spot, but I think it's the hardest piece to to get over the over the top of right now is just that.

And Surabhi, if you had any thoughts on blind spot, I think Chris, you know verbalize it pretty well. It's about business transformation and prioritization and change management, which is the hardest, right be the e-commerce error or any other automation things that we have seen. The only thing I would add to that is we are also the conduits of teaching the organization the risk to reward ratio, right? How fast do you go and what are the risks associated and what's the reward expected?

I'll give an example of as somebody was asking about practical use cases, when my team creates a bunch of new content or creative on social, we just have to figure out the annotations and sources. And I we, we make sure that our legal department is hand in hand with us to make sure we annotate, you know, give hashtags and give all Full disclosure on how the content is created and where it is sourced and so on. So these are the kind of practical guardrails that we have to live within. But you know, like Chris rightly said, if you don't have a business transformation objective, we will be playing a very linear game and not a non linear game.

And that's a classic blind spot that's more apparent today. Wonderful. Well, it sounds like we've had a great conversation today. And I just, we are at time, but I want to take take a moment and thank you all for joining us today.

Darren and Chuck, Chris and Surabhi, all of their contact information can be found on the screen in front of you. And if you have any questions, feel free to reach out to Lek Consulting or Chris and Surabhi. We're happy to continue the conversation. Chuck and Darren, any final thoughts?

I just want to say big thank you to Surabhi and Chris for their participation today. It's always great to see the two of them. And I always walk away feeling like I've learned something. And I have again today.

So really, thank you for your for your time. Yeah, thank you. The feelings are mutual. I've learned so much.

Thank you for having us. Thank you all. Have a great afternoon.