Google Cloud Next '24 | Rodney Zemmel | McKinsey & Company

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Rodney Zemmel

Global Leader

McKinsey & Company

Riding the gen AI wave: Unleashing enterprise growth in the digital era

With generative artificial intelligence emerging as the new way of doing business, successfully riding the gen AI wave is top of mind for companies.As a result, how to apply gen AI has become an important topic for an organization’s modernization journey. The conversation is shifting from productivity to growth, given that enhancing customer satisfaction and engagement remains a vital objective, according to Rodney Zemmel (pictured), global leader of McKinsey Digital at McKinsey & Company.“The amazing thing about gen AI is it’s the world’s easiest technology to pilot, but it’s quite hard to get enterprise value at scale from it,” he said

play_circle_outline Empowering Business Transformation: Introducing Rodney from McKinsey and the Power of AI

play_circle_outline The Crucial Role of an Agile Operating Model and Control Functions for Success in Today's Businesses

play_circle_outline Exploring the Overhyped Question and Versatility of Gen AI as the Ultimate 'Swiss Army Knife' of Artificial Intelligence

play_circle_outline Exploring the Future: A Preview of ING Netherlands CEO's Panel Discussion on Gen AI's Impact on Customer Engagement and Creative Content

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Rodney Zemmel | McKinsey & Company

Rodney Zemmel

Global Leader McKinsey & Company

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(bright music)

>> Good afternoon, Cloud Community, and welcome back to fabulous Las Vegas, Nevada. We're here midway through day one of Google Cloud Next, and it is just pumping 30,000 attendees this year. But I have two of the most important people at the show sitting with me. My name's Savannah Peterson. You're watching theCUBE. I'm joined by Rebecca Knight. Rebecca, we're just having the best day.

>> We are. And one of the things that is really striking to me that we talk about all the time on theCUBE, but we're really talking about this show, Google Cloud Next, is that Gen AI is the new way of doing business.

It is. >> Yeah.

>> Part and parcel to the future of work, which is why I'm very excited about our next guest.

>> Yes, me too. Rodney, thank you so much for joining us from McKinsey. Welcome, how you doing today?

>> I'm doing well, I'm excited to be here.

>> It's your first time at the show as well too.

>> It is my first time at the show and first time talking to someone with such amazing earrings.

>> Well, I'll take the flattery. It doesn't always happen on the show, but yeah. I like you already, Rodney. We'll let you stay on. When we were just chatting before the show started, I was asking you, it's your first time you've been leading the digital side of the business for a while. What happened over the course of the last year within McKinsey, within your divisions that brought you here and brought some departments together?

>> Sure. Well, a little thing you might have heard of called, Generative AI. So the way we organize a McKinsey Digital, which we used to be sort of a small part of our firm, now it's about half of what we do is we say we do three things. We do transforming businesses through the power of AI. We do digital business building, and then we do core technology modernization. And cloud was always our core technology modernization practice. So, we have a group of amazing colleagues who lead that, and they were always here, and this was their meeting. Since late 2022, those distinctions have been pretty meaningless. And the most important topic in modernization has been actually how do you apply Gen AI to it? And my colleagues, Leandro Santos and Aaron Balcom, led a fabulous session earlier today on how to use Gen AI for application modernization. We were excited to see it, I think, be the best attended or best signed up session of the conference. And it really just shows how these worlds are coming together. So it's exciting to be here.

>> That is exciting.

>> Oh, and I've got a book to promote as well.

>> Well, that's just where I was going. That was the segue I was looking for. You brought a prop, you brought a brand new book that you have co-authored called, "Rewired." Congratulations. A book is a big deal

and a lot of work. >> Yeah.

>> Can you tell our viewers a little bit about why you wrote it?

>> Thank you. So, nearly 30 years in consulting. It's actually the second book I've written. Almost nobody read the first one. And on this one, we got very, very lucky with the timing. I mean, having a book come out that has AI and McKinsey guide in the title, timed with the Gen AI wave. We were just in incredibly, incredibly lucky.

>> How long have you been working on it then?

>> So we've been working on it. So, the story goes back about four or so years, right? So we've been working on sort of digital transformation topics with our clients probably for nine, maybe 10 years. You know, others have too. And what we realized about four or five years ago, we did sort of a retrospective and we said, "Okay, who's making money and who isn't?" Right, where is this working? Where isn't it? And our math was, this was sort of pre-Covid. 91% of companies have something called, a digital transformation, right?

And I'm surprised. >> Right.

>> It wasn't a hundred percent, but maybe that's the ones who aren't talking to me. But if you then say, "Okay, who's making money on it?" About 25% of them only are hitting their cost objectives, and about 30% are hitting their revenue objectives. So, look, something isn't working.

>> Yeah. >> We said, "Let's actually take 200 of the examples that work and let's develop the playbook." So we did that and initially, it was a playbook just for our own consulting team. So we used it internally for a couple of years. But after having sort of a lot of success with it internally, some colleagues then sort of, convinced me actually and say, "Look, let's actually go external with this and let's publish it as a book," which we did. And, of course, we then got very lucky with the Gen AI timing in there. And, you know, the book I would say, you know, captures the beginning of the Gen AI wave. Obviously, it's moving incredibly quickly, but we actually think Gen AI makes it even more relevant because the amazing thing about Gen AI is it's the world's easiest technology to pilot, but it's quite hard to get enterprise value at scale from it. So there's a bit of a risk. And we've seen many companies in last year go back a bit to sort of 2015 in digital where it's like death by a thousand pilots. Everyone wants to do something cool, wants to show it off externally, but you're seeing impact everywhere except in the actual P&L. So this is supposed to be the guide to how do you actually get it really into the P&L.

>> So what's the answer to that?

>> I was just going to say, yeah.

>> Because you're absolutely right. We always hear about executives coming on, "Well, we needed a POC, this is what we really wanted." And that's understandable because you want to see how is this going to work? What is this really going to do? But then having a zillion pilots, that's not going to work either. So what are the attributes that you look for to know, okay, this is a pilot that could really show us something.

>> You want me to tell you the answer without paying $40 for the book?

>> Sorry.

I mean-- >> My mother already told me it's too expensive, so it's okay. I was going to put that in one of the--

>> It's coming out of a McKinsey.

>> Now, now, now, now. It's about value.

>> It's a high quality service, is what I was implying.

>> High level, high level.

>> So, not high level, high quality. I like that better.

>> I do. I got you.

>> So what's the answer, the six pieces to the answer? So I'll walk through them, I should take a minute or two. So it actually starts at the top with business led technology roadmap, right? And that may not be a popular thing to say here with 30,000 technologists, but you actually need a real financial target and you need business and technology working together. The most common failure mode was a CEO says, "We're going to go do AI." And then every part of the organization goes off and does their own thing.

>> Silos. >> And you get this like, not even just like death by a thousand pilots, right? The thousand flowers blooming thing. You actually need a senior team to align and to say, "There's many things we can do, but we're going to pick one big area of the business, one domain, and we're going to drive like an end-to-end transformation in that domain rather than sprinkling it everywhere. And we're going to put a financial target against it. And what we found in the research was, you set a financial target of 15 to 20% of EBITDA, your chance of hitting at least 80% of that financial goal is higher than if you set a target of two or 3% of EBITDA. So, big targets lead to much higher percentage chance of attainment 'cause this is hard. You've got to get people to work together, you've got to sustain investments, you've got to work cross functionally and so on. Anyway, that's chapter one. I'll be quicker on the other chapters. Number two is about people.

>> Great. >> And, you know, one of the most fun findings in the research was the companies that went out and hired all the cool kids, all the technology natives and the Silicon Valley and London, whatever. That's a really great way to change your company dress code. Not a great way to drive sustained business impact. So it's much more actually about up-skilling and re-skilling. And the companies that are in that money making quadrant are investing hard in up-skilling and re-skilling the senior team and the front line. Third thing then is about operating model. And, you know, I wish I had another word than Agile, like, 'cause Agile is like such a cliche. Like somebody told me--

>> I've never heard that word before.

>> You've never heard it. >> Yeah.

>> The Agile manifesto would've been old enough to graduate from college this year, I think.

>> No, is that true?

>> Well, thank you for dating all of us for that one, geez.

>> Okay, okay.

>> But that is still the secret. And in fact, what we found is, it's not only every company says they're doing Agile. What that often means is, a tech team is working in Agile, right? It's the business and the tech team working together. But importantly and importantly in regulated industries, the control functions, right? You need legal, you need regulatory, you need quality, whatever it is. If they're not in the Agile pods, you've got nothing. So fourth is technology. Technology, of course, is in the list, right? But it's never just tech. And what we found is companies can succeed by doing, you know, massive horizontal cloud migration, create amazing, perfect data lakes. That's long, slow, and expensive. Much better to start with the business problem and to do the focus technology modernization in that area. Fifth is data. And in data, we saw two common problems. Number one is most companies overestimate the value of their own data. And the reality is, it's your data plus the world's data coming together, right? That creates really the unique value. And then the other thing is data governance, right? Which is sort of like a boring topic and people think like.

>> But critical right now.

>> Absolutely.

>> Mission critical.

>> Absolutely. >> Yeah.

>> And, you know, every company thinks they're always like one AI use case away from Nirvana, and you never are. Right, our research shows it's like 10 or 11 different ones before you can actually see impact in the P&L. But if you've not done the hard work on data governance, those become more and more expensive instead of cheaper and cheaper as you go. And then the last one, sorry, I know you're looking at me.

>> This is great.

>> I'm literally taking notes. So be very clear, that's what's going on.

>> The notes don't stop you from getting the book.

>> No, I'll still get the book, don't worry. I understand the high quality and the value in.

>> So the last one then is adoption and scaling. And some of these are sort of the traditional change management levers around a consistent change story from the CEO. You've got to involve the front line, you need role modeling, but actually it's about incentives, right? So the number of companies where someone will say, you know, "What's going on with the AI initiative?" And they'll turn and look at the CIO or the CDIO, whereas instead they should be looking at the business leader also, and the two of them together should have a joint incentive. So that simple thing of aligning the incentives between business and tech makes an enormous difference on adoption and scaling. So there you go, that was 400 words and 400 pages in four minutes.

>> Very well done. And you brought it full circle.

>> And it's really terrific. What I'm hearing so much of is that it really is a change management ideas that have to go into it. I mean, it's so much about getting the people on board, getting them aligned, getting them incentivized, getting them motivated toward working towards something. Can you talk a little bit more about the strategy of hiring the coolest kids who graduated with these nerd degrees versus re-skilling the current workforce? Because I think that, particularly at this time where people, where some people who might be skeptical about Gen AI and what it might do for their careers and their jobs, can you talk a little bit about this idea of re-skilling and what you've learned from it?

>> Yeah, so I was in a meeting a few weeks ago with the leadership team of a company and with one of the big Generative AI players. And everyone was sort of swapping notes on the amazing things that Gen AI could do and how much impact it was going to have. And as we were having the back and forth, someone came up with sort of the clever thought that like, you know, the early winners from Gen AI are going to be dogs. They're going to be the biggest beneficiaries, right? Why dogs? Because if Gen AI is saving you 20 minutes a day, what are you going to do? You're going to go home and walk the dog.

>> I love how it goes to dogs and not to kids or families.

>> Exactly.

>> It was a tough crowd. Let's assume they're already being looked after and the dog is the marginal choice.

>> Yes, okay. >> But yes. So, you know, that's nice, right? That's wonderful for pet health, right? But like, how does that actually turn into improved corporate performance? You actually need your employees to say, not just how do I take the most boring 20 minutes of my day and automate it, but how do I change a week in the life of, and we actually see this really prominently. I think there's an early use case in software development, right? If you just give people the tools, right? And the tools are amazing and say, go use it, right? You see these like 10, 20% productivity improvements and I'm sure there's lots of happy dogs at the other end of it, but if instead you say, "Let's take a week in the life of, right? Let's think about everything." Not just using it for whatever part is most difficult for you. Let's think about the whole system that needs to go around not just developing the code, but the testing, you know, the commenting, the understanding the business rules that you're trying to code against and so on. Much think about the whole business system, that's where you start to see the 40, 50, 60% improvement, which you can see in the P&L. So it's the structured process of taking your employees through that, both your frontline employees who are using it in a hands-on way, but also the leadership team who need to know how to get value from it. And like a year, a couple years ago, it was trendy to like go take senior leaders and put them on an MIT course and go have them learn to code and so on.

>> Yes. >> Like that can be like fun for awareness, but that's not the same as actually understanding the business potential of what you were doing.

>> But also going back to the dog walking example, that is real, I think it was either Derek Thompson.

>> It's very real. >> Cal Newport or some brilliant future of work journalist who talked about the kind of innovation, the kind of creativity you get when you are doing something like walking your dog. Because you can't, I mean, I guess there are some people who will walk their dog with their phones to their--

>> Or solve a Rubik's Cube on water skis. Depending on what you're doing.

>> Inside joke there.

>> Yeah.

>> But the point being, that is a time where you can have a break away. And that's when you get your big ideas or even your small ideas that can add up to something.

>> You know, it's interesting because, you know, early on, right, people looked at this technology as a productivity tool, right? It's about automation, simplification, da, da da. The two big surprises, number one has been exactly where you were going, a creativity tool.

>> Yeah. >> So first of all, how well the models and in particular, the newer generation of the models can do on being truly creative, right? And purists will say, "Oh, it's not real creativity, it's mimicking creativity, da da da." It mimics it body well, right?

>> It sure does. And it's only getting better.

>> Exactly. >> Yeah.

>> So creativity tool. But also when you take away some of the drudgery, how much time and freedom you actually have to be more creative is amazing. So we're seeing huge benefits in creativity. The other thing as well is we're seeing the conversation move from it being about productivity to it being about growth, right? And there's this one study from the UK last summer, right? That really, I think, opened up lots of people's eyes on growth. And this was a group of academics who wanted to see if patients could tell the difference between were they talking to a doctor who was texting them or were they talking to one of the chat bots, right? So the patient was assigned to one group or the other, they run it, da, da da da. And they ask the patients, you know, which one did you have? And to their disappointment, most patients could tell the difference, right? Even pretty elderly patients, 70% of the time, it's like, okay, Turing test failed.

>> Yeah, yeah.

>> But then they said, okay, but which one did you prefer? Right? The patients overwhelmingly preferred the chat bot, right? They thought it was more informative, right? Knew more than the doctors, but also they thought it was more empathetic, right? And like, listen to them better, right? So listen, it's easy to, like, you turn this into a joke about British doctors or something, and my brother is one, so watch this. But it's really about the power of these things for building human connection. And if done with integrity therefore, how well that can help develop customer and stakeholder relationships and be a tool that's about growth and sales growth, not just about productivity.

>> I think I love that point. And the notion, I mean, doctors are humans too. It's not anyone can have a bad day. You know, anyone can have something going on in their--

>> Not listen very well. >> With their life. Yeah, or be distracted or be hungry or, you know, who knows what's going on. Or you just had a horrible thing happen with another patient. I want to just hold on that anecdote for a second. That the notion of bots being more empathetic than us is not something that we normally think about. Given that we've just talked about all a lot of the good use cases. I got to ask you, do you think Gen AI is over hyped at all?

>> Yes. I mean, you know. You don't get 30,000 people in Las Vegas without some degree of hype, right? But, you know, and I was in a client's board meeting late last year and I was sort of waxing lyrical about how Gen AI was going to change the world. And a board member sort of interrupted me and he said, "You know, will you take a bet with me that Gen AI is going to be worth more next year than my NFT portfolio is worth this year?" Right? You're like, you know, that's a good question, right? But I actually would take that bet, right? And I think you've got to view it, I'm not sure, three years from now we're going to be talking about Gen AI, right? It'll be yet another flavor of AI. So if you take this as the 50 year journey of AI, right? And not the 15 month journey of Gen AI, right? I think it's very, very real. And I think what it does is, you know, it's the Swiss army knife of AI, right? This is the moment that makes it available for almost everybody in a democratized lower cost, easier to learn way, of course, with all kinds of risks and complexities that need to be managed. But we're going to look back on this as a real sort of kink in the curve in AI. But at the end of the day, it is still AI and it's the broader AI story that's important.

>> Tomorrow, you're going to be on a panel here with the CEO of ING. Can you give our viewers a little preview of what you're going to be talking about?

>> Yes, so it's Peter Jacobs, is the CEO of ING Netherlands. So we talk about the 4Cs of where we're seeing Gen AI being applied, right? It's about customer engagement, it's about concision so virtual experts. It's about coding and it's about creative content. And with Peter, we're going to be talking about the first of those, the customer engagement. And ING as many banks, all banks probably have had a chat bot that's been pretty effective for a long time. And what they wanted to do was to try and harness this new technology, essentially to create a better, more engaging front end for their customers. And yes, there's a productivity aspect to it, but also it's back to where we were a moment ago with the doctors. It's actually how do you make it more engaging and the success that they've had in using this to really drive customer engagement and customer satisfaction. And to do that in obviously a highly regulated, highly sensitive, highly important market. And in a culture that is used to innovation, but also has incredibly high standards. I mean, I won't tell his story for him. I well let him tell it, but it's an exciting one to be on stage with him talking about.

>> Excellent.

>> Yeah, what a great customer example. And exciting. The whole show is a lot about customer examples. I'm curious, we were mentioning, and we were chatting about your daughter earlier and without incriminating her Rubik's Cube skills. Shout out to your daughter, by the way. Hello. What is your daughter and her friends talking about in terms of Gen AI? Is it a conversation for them?

>> That's funny. So, yes. Our daughter is our youngest, our older two are already in college. And, you know, it's funny, actually. I'll talk about all three of them, so, you know.

>> Yeah, please.

>> Our oldest is about to start a PhD and which in neuroscience. I was a PhD scientist years ago.

>> I was going to say like father like daughter on that one.

Yeah. >> Yeah.

>> And the amount of data, like the extent to which biology labs right now look like computer science labs. It's just amazing. I mean, he got more data in a summer internship than I did in the three years of my PhD. It's just been transformed. Right.

>> That's wild too.

>> Our middle one is poli sci, which he tells me, that is a real science.

>> I studied political science.

>> I did as well.

>> Yes. >> 100% right, okay?

>> We probably got her back, we got her back on this newsletter. Clearly both political science, it's still.

>> Yeah. So, I mean, the role that this is playing, right? In the ability to summarize and ingest like enormous amounts of information and just to really change how the policy field gets done, how the policy process gets done. I mean, nevermind the whole, you know, importance of regulation for sensible use of AI.

>> Yes. >> But just like how it changes someone's life as a policy professional. I saw Politico this morning, they're now sending out like AI generated summaries and so on. It's like if it's reaching like that part of the world, like it's going everywhere.

>> Oh, it's big in journalism.

>> Yeah. >> Yeah.

>> And then our daughter's the real engineer, right? So she's in high school and is very into robotics and so on. And, you know, they have a team that competes in these robotics competitions. And the extent to which they've already adopted Gen AI to like how they compete and win in these like high school robot competitions. It's unbelievable. And, you know, what I'm told, I don't have independent verification on this statistic, but I'm told is this year is the record year for dropouts from computer science in like in elite university programs 'cause people are looking at it and saying, "Huh, why do I need to learn the drudgery of coding?" So we think that's overstated, right? We actually think, you know, the elite coders will have superpowers. There'll still be a need for them. But the shift away from routine coding and into really sort of systems engineering and systems thinking and then into like the human aspects that have to go around that, right? Into how you actually lead and build a team and influence people and so on. That's clearly the wave of the future.

>> Excellent. Well, there's lots of people.

>> And we didn't even mention solving a Rubik's Cube on water skis.

>> We didn't, you know?

>> He brought it up, he brought it up.

>> Well, I think it's really cool. And I think it's interesting too 'cause I mean, I even wonder, you know, we talk about Gen AI or AI, I wonder if to your family for example, it's just a tool. It's not even, you know, delineated as artificial intelligence. They're just, "Oh, I'm using Gemini. Oh, I'm using this product and I'm going to go build this robot, which is rad."

>> Yeah. >> Gosh, things, yeah. Wow. You've been at McKinsey for almost 30 years.

>> Yeah, I prefer to say 29, but yes. (group laughing)

>> That is impressive.

>> 29 forever.

>> And so as a result, I mean, you've been a part of a multitude of hype cycles. Is this hype cycle different, faster, more exciting, or comparable to some of the other technological hype cycles you've experienced in your wonderful career there?

>> So if you say like, this time it's different, right? You set yourself up for that. Like YouTube clip, you know, years.

>> I'm not setting you up, I'm not setting you up. I genuinely want your insight on that.

>> Yeah. >> Genuinely want your insight.

>> But I do, right? So, I think the way we're increasingly talking about this is, this is the fourth platform revolution, right? So, you know, what does technology do in economic terms, right? It lowers the cost of something, right? The first was just in compute, right? Just lowering the cost of doing calculations, right? You don't need, you know, those women with the computers in "Hidden Figures," right? You don't need that anymore, right? When IBM and others transformed basic computing technology. Right, then there was the internet, right? And that transformed, that took down to almost zero the cost of distribution, right? You could get your ideas, your offer anywhere, right? And then, you know, Amazon and others and, you know, many others sort of transform that. And Google, of course, like who would've thought that actually searching the internet would be the most lucrative application that you'd find on the internet, right? Then there's the third platform revolution that was around mobile, right? That was lowering the cost really of access, right? Just the fact that you could have this incredibly high compute power, you know, but really, I guess mobile and cloud together, right? Mobile and cloud together really gave, you know, almost down to zero access to high performance compute. And this fourth one, right? This is lowering the cost of human knowledge and ingenuity and creativity, right? This is like, you know, maybe ultimately driving down towards zero, the cost of being a creative person with all the world's knowledge at your fingertips. So that's a revolution, right? I mean, there have been other revolutions before, but this feels, and certainly for white collar work, right? This feels as transformative or more transformative than any of those that came before.

>> Very well stated and well summarized. Last question for you, Rodney. Well, you've said a lot of exciting things, so I don't know that you can just pick one. When we have you back on the show next Google Cloud Next, what do you hope to be able to say then that you can't yet say beyond the fact that your Gen AI portfolio is worth more than your NFT portfolio.

>> And that he is a bestselling author?

>> Yeah, yeah, exactly.

>> Yes.

>> Worldwide, yeah.

>> So, I would like the dog still to be healthy and happy and warm.

>> Yeah.

>> But I would like to see many more companies and organizations who can point to real transformational business impact in their P&L. And we're seeing the early wave of that. But I think this is the year of show me the money for impact from Generative AI.

>> Show me the money, show me the real, and get there by reading "Rewired." Thank you so much for being on the show with us. Rodney, this has been absolutely fabulous. I hope everyone picks up a copy. Rebecca, always a pleasure. This was a fun one. We're actually over time, we had so much fun. So, thank you so much and thank all of you for tuning in to day one of three here at Google Cloud Next in beautiful Las Vegas, Nevada. My name's Savannah Peterson. You're watching theCUBE. The leading source for enterprise tech news. (bright music)

Rodney Zemmel | McKinsey & Company

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(bright music)

>> Good afternoon, Cloud Community, and welcome back to fabulous Las Vegas, Nevada. We're here midway through day one of Google Cloud Next, and it is just pumping 30,000 attendees this year. But I have two of the most important people at the show sitting with me. My name's Savannah Peterson. You're watching theCUBE. I'm joined by Rebecca Knight. Rebecca, we're just having the best day.

>> We are. And one of the things that is really striking to me that we talk about all the time on theCUBE, but we're really talking about this show, Google Cloud Next, is that Gen AI is the new way of doing business.

It is. >> Yeah.

>> Part and parcel to the future of work, which is why I'm very excited about our next guest.

>> Yes, me too. Rodney, thank you so much for joining us from McKinsey. Welcome, how you doing today?

>> I'm doing well, I'm excited to be here.

>> It's your first time at the show as well too.

>> It is my first time at the show and first time talking to someone with such amazing earrings.

>> Well, I'll take the flattery. It doesn't always happen on the show, but yeah. I like you already, Rodney. We'll let you stay on. When we were just chatting before the show started, I was asking you, it's your first time you've been leading the digital side of the business for a while. What happened over the course of the last year within McKinsey, within your divisions that brought you here and brought some departments together?

>> Sure. Well, a little thing you might have heard of called, Generative AI. So the way we organize a McKinsey Digital, which we used to be sort of a small part of our firm, now it's about half of what we do is we say we do three things. We do transforming businesses through the power of AI. We do digital business building, and then we do core technology modernization. And cloud was always our core technology modernization practice. So, we have a group of amazing colleagues who lead that, and they were always here, and this was their meeting. Since late 2022, those distinctions have been pretty meaningless. And the most important topic in modernization has been actually how do you apply Gen AI to it? And my colleagues, Leandro Santos and Aaron Balcom, led a fabulous session earlier today on how to use Gen AI for application modernization. We were excited to see it, I think, be the best attended or best signed up session of the conference. And it really just shows how these worlds are coming together. So it's exciting to be here.

>> That is exciting.

>> Oh, and I've got a book to promote as well.

>> Well, that's just where I was going. That was the segue I was looking for. You brought a prop, you brought a brand new book that you have co-authored called, "Rewired." Congratulations. A book is a big deal

and a lot of work. >> Yeah.

>> Can you tell our viewers a little bit about why you wrote it?

>> Thank you. So, nearly 30 years in consulting. It's actually the second book I've written. Almost nobody read the first one. And on this one, we got very, very lucky with the timing. I mean, having a book come out that has AI and McKinsey guide in the title, timed with the Gen AI wave. We were just in incredibly, incredibly lucky.

>> How long have you been working on it then?

>> So we've been working on it. So, the story goes back about four or so years, right? So we've been working on sort of digital transformation topics with our clients probably for nine, maybe 10 years. You know, others have too. And what we realized about four or five years ago, we did sort of a retrospective and we said, "Okay, who's making money and who isn't?" Right, where is this working? Where isn't it? And our math was, this was sort of pre-Covid. 91% of companies have something called, a digital transformation, right?

And I'm surprised. >> Right.

>> It wasn't a hundred percent, but maybe that's the ones who aren't talking to me. But if you then say, "Okay, who's making money on it?" About 25% of them only are hitting their cost objectives, and about 30% are hitting their revenue objectives. So, look, something isn't working.

>> Yeah. >> We said, "Let's actually take 200 of the examples that work and let's develop the playbook." So we did that and initially, it was a playbook just for our own consulting team. So we used it internally for a couple of years. But after having sort of a lot of success with it internally, some colleagues then sort of, convinced me actually and say, "Look, let's actually go external with this and let's publish it as a book," which we did. And, of course, we then got very lucky with the Gen AI timing in there. And, you know, the book I would say, you know, captures the beginning of the Gen AI wave. Obviously, it's moving incredibly quickly, but we actually think Gen AI makes it even more relevant because the amazing thing about Gen AI is it's the world's easiest technology to pilot, but it's quite hard to get enterprise value at scale from it. So there's a bit of a risk. And we've seen many companies in last year go back a bit to sort of 2015 in digital where it's like death by a thousand pilots. Everyone wants to do something cool, wants to show it off externally, but you're seeing impact everywhere except in the actual P&L. So this is supposed to be the guide to how do you actually get it really into the P&L.

>> So what's the answer to that?

>> I was just going to say, yeah.

>> Because you're absolutely right. We always hear about executives coming on, "Well, we needed a POC, this is what we really wanted." And that's understandable because you want to see how is this going to work? What is this really going to do? But then having a zillion pilots, that's not going to work either. So what are the attributes that you look for to know, okay, this is a pilot that could really show us something.

>> You want me to tell you the answer without paying $40 for the book?

>> Sorry.

I mean-- >> My mother already told me it's too expensive, so it's okay. I was going to put that in one of the--

>> It's coming out of a McKinsey.

>> Now, now, now, now. It's about value.

>> It's a high quality service, is what I was implying.

>> High level, high level.

>> So, not high level, high quality. I like that better.

>> I do. I got you.

>> So what's the answer, the six pieces to the answer? So I'll walk through them, I should take a minute or two. So it actually starts at the top with business led technology roadmap, right? And that may not be a popular thing to say here with 30,000 technologists, but you actually need a real financial target and you need business and technology working together. The most common failure mode was a CEO says, "We're going to go do AI." And then every part of the organization goes off and does their own thing.

>> Silos. >> And you get this like, not even just like death by a thousand pilots, right? The thousand flowers blooming thing. You actually need a senior team to align and to say, "There's many things we can do, but we're going to pick one big area of the business, one domain, and we're going to drive like an end-to-end transformation in that domain rather than sprinkling it everywhere. And we're going to put a financial target against it. And what we found in the research was, you set a financial target of 15 to 20% of EBITDA, your chance of hitting at least 80% of that financial goal is higher than if you set a target of two or 3% of EBITDA. So, big targets lead to much higher percentage chance of attainment 'cause this is hard. You've got to get people to work together, you've got to sustain investments, you've got to work cross functionally and so on. Anyway, that's chapter one. I'll be quicker on the other chapters. Number two is about people.

>> Great. >> And, you know, one of the most fun findings in the research was the companies that went out and hired all the cool kids, all the technology natives and the Silicon Valley and London, whatever. That's a really great way to change your company dress code. Not a great way to drive sustained business impact. So it's much more actually about up-skilling and re-skilling. And the companies that are in that money making quadrant are investing hard in up-skilling and re-skilling the senior team and the front line. Third thing then is about operating model. And, you know, I wish I had another word than Agile, like, 'cause Agile is like such a cliche. Like somebody told me--

>> I've never heard that word before.

>> You've never heard it. >> Yeah.

>> The Agile manifesto would've been old enough to graduate from college this year, I think.

>> No, is that true?

>> Well, thank you for dating all of us for that one, geez.

>> Okay, okay.

>> But that is still the secret. And in fact, what we found is, it's not only every company says they're doing Agile. What that often means is, a tech team is working in Agile, right? It's the business and the tech team working together. But importantly and importantly in regulated industries, the control functions, right? You need legal, you need regulatory, you need quality, whatever it is. If they're not in the Agile pods, you've got nothing. So fourth is technology. Technology, of course, is in the list, right? But it's never just tech. And what we found is companies can succeed by doing, you know, massive horizontal cloud migration, create amazing, perfect data lakes. That's long, slow, and expensive. Much better to start with the business problem and to do the focus technology modernization in that area. Fifth is data. And in data, we saw two common problems. Number one is most companies overestimate the value of their own data. And the reality is, it's your data plus the world's data coming together, right? That creates really the unique value. And then the other thing is data governance, right? Which is sort of like a boring topic and people think like.

>> But critical right now.

>> Absolutely.

>> Mission critical.

>> Absolutely. >> Yeah.

>> And, you know, every company thinks they're always like one AI use case away from Nirvana, and you never are. Right, our research shows it's like 10 or 11 different ones before you can actually see impact in the P&L. But if you've not done the hard work on data governance, those become more and more expensive instead of cheaper and cheaper as you go. And then the last one, sorry, I know you're looking at me.

>> This is great.

>> I'm literally taking notes. So be very clear, that's what's going on.

>> The notes don't stop you from getting the book.

>> No, I'll still get the book, don't worry. I understand the high quality and the value in.

>> So the last one then is adoption and scaling. And some of these are sort of the traditional change management levers around a consistent change story from the CEO. You've got to involve the front line, you need role modeling, but actually it's about incentives, right? So the number of companies where someone will say, you know, "What's going on with the AI initiative?" And they'll turn and look at the CIO or the CDIO, whereas instead they should be looking at the business leader also, and the two of them together should have a joint incentive. So that simple thing of aligning the incentives between business and tech makes an enormous difference on adoption and scaling. So there you go, that was 400 words and 400 pages in four minutes.

>> Very well done. And you brought it full circle.

>> And it's really terrific. What I'm hearing so much of is that it really is a change management ideas that have to go into it. I mean, it's so much about getting the people on board, getting them aligned, getting them incentivized, getting them motivated toward working towards something. Can you talk a little bit more about the strategy of hiring the coolest kids who graduated with these nerd degrees versus re-skilling the current workforce? Because I think that, particularly at this time where people, where some people who might be skeptical about Gen AI and what it might do for their careers and their jobs, can you talk a little bit about this idea of re-skilling and what you've learned from it?

>> Yeah, so I was in a meeting a few weeks ago with the leadership team of a company and with one of the big Generative AI players. And everyone was sort of swapping notes on the amazing things that Gen AI could do and how much impact it was going to have. And as we were having the back and forth, someone came up with sort of the clever thought that like, you know, the early winners from Gen AI are going to be dogs. They're going to be the biggest beneficiaries, right? Why dogs? Because if Gen AI is saving you 20 minutes a day, what are you going to do? You're going to go home and walk the dog.

>> I love how it goes to dogs and not to kids or families.

>> Exactly.

>> It was a tough crowd. Let's assume they're already being looked after and the dog is the marginal choice.

>> Yes, okay. >> But yes. So, you know, that's nice, right? That's wonderful for pet health, right? But like, how does that actually turn into improved corporate performance? You actually need your employees to say, not just how do I take the most boring 20 minutes of my day and automate it, but how do I change a week in the life of, and we actually see this really prominently. I think there's an early use case in software development, right? If you just give people the tools, right? And the tools are amazing and say, go use it, right? You see these like 10, 20% productivity improvements and I'm sure there's lots of happy dogs at the other end of it, but if instead you say, "Let's take a week in the life of, right? Let's think about everything." Not just using it for whatever part is most difficult for you. Let's think about the whole system that needs to go around not just developing the code, but the testing, you know, the commenting, the understanding the business rules that you're trying to code against and so on. Much think about the whole business system, that's where you start to see the 40, 50, 60% improvement, which you can see in the P&L. So it's the structured process of taking your employees through that, both your frontline employees who are using it in a hands-on way, but also the leadership team who need to know how to get value from it. And like a year, a couple years ago, it was trendy to like go take senior leaders and put them on an MIT course and go have them learn to code and so on.

>> Yes. >> Like that can be like fun for awareness, but that's not the same as actually understanding the business potential of what you were doing.

>> But also going back to the dog walking example, that is real, I think it was either Derek Thompson.

>> It's very real. >> Cal Newport or some brilliant future of work journalist who talked about the kind of innovation, the kind of creativity you get when you are doing something like walking your dog. Because you can't, I mean, I guess there are some people who will walk their dog with their phones to their--

>> Or solve a Rubik's Cube on water skis. Depending on what you're doing.

>> Inside joke there.

>> Yeah.

>> But the point being, that is a time where you can have a break away. And that's when you get your big ideas or even your small ideas that can add up to something.

>> You know, it's interesting because, you know, early on, right, people looked at this technology as a productivity tool, right? It's about automation, simplification, da, da da. The two big surprises, number one has been exactly where you were going, a creativity tool.

>> Yeah. >> So first of all, how well the models and in particular, the newer generation of the models can do on being truly creative, right? And purists will say, "Oh, it's not real creativity, it's mimicking creativity, da da da." It mimics it body well, right?

>> It sure does. And it's only getting better.

>> Exactly. >> Yeah.

>> So creativity tool. But also when you take away some of the drudgery, how much time and freedom you actually have to be more creative is amazing. So we're seeing huge benefits in creativity. The other thing as well is we're seeing the conversation move from it being about productivity to it being about growth, right? And there's this one study from the UK last summer, right? That really, I think, opened up lots of people's eyes on growth. And this was a group of academics who wanted to see if patients could tell the difference between were they talking to a doctor who was texting them or were they talking to one of the chat bots, right? So the patient was assigned to one group or the other, they run it, da, da da da. And they ask the patients, you know, which one did you have? And to their disappointment, most patients could tell the difference, right? Even pretty elderly patients, 70% of the time, it's like, okay, Turing test failed.

>> Yeah, yeah.

>> But then they said, okay, but which one did you prefer? Right? The patients overwhelmingly preferred the chat bot, right? They thought it was more informative, right? Knew more than the doctors, but also they thought it was more empathetic, right? And like, listen to them better, right? So listen, it's easy to, like, you turn this into a joke about British doctors or something, and my brother is one, so watch this. But it's really about the power of these things for building human connection. And if done with integrity therefore, how well that can help develop customer and stakeholder relationships and be a tool that's about growth and sales growth, not just about productivity.

>> I think I love that point. And the notion, I mean, doctors are humans too. It's not anyone can have a bad day. You know, anyone can have something going on in their--

>> Not listen very well. >> With their life. Yeah, or be distracted or be hungry or, you know, who knows what's going on. Or you just had a horrible thing happen with another patient. I want to just hold on that anecdote for a second. That the notion of bots being more empathetic than us is not something that we normally think about. Given that we've just talked about all a lot of the good use cases. I got to ask you, do you think Gen AI is over hyped at all?

>> Yes. I mean, you know. You don't get 30,000 people in Las Vegas without some degree of hype, right? But, you know, and I was in a client's board meeting late last year and I was sort of waxing lyrical about how Gen AI was going to change the world. And a board member sort of interrupted me and he said, "You know, will you take a bet with me that Gen AI is going to be worth more next year than my NFT portfolio is worth this year?" Right? You're like, you know, that's a good question, right? But I actually would take that bet, right? And I think you've got to view it, I'm not sure, three years from now we're going to be talking about Gen AI, right? It'll be yet another flavor of AI. So if you take this as the 50 year journey of AI, right? And not the 15 month journey of Gen AI, right? I think it's very, very real. And I think what it does is, you know, it's the Swiss army knife of AI, right? This is the moment that makes it available for almost everybody in a democratized lower cost, easier to learn way, of course, with all kinds of risks and complexities that need to be managed. But we're going to look back on this as a real sort of kink in the curve in AI. But at the end of the day, it is still AI and it's the broader AI story that's important.

>> Tomorrow, you're going to be on a panel here with the CEO of ING. Can you give our viewers a little preview of what you're going to be talking about?

>> Yes, so it's Peter Jacobs, is the CEO of ING Netherlands. So we talk about the 4Cs of where we're seeing Gen AI being applied, right? It's about customer engagement, it's about concision so virtual experts. It's about coding and it's about creative content. And with Peter, we're going to be talking about the first of those, the customer engagement. And ING as many banks, all banks probably have had a chat bot that's been pretty effective for a long time. And what they wanted to do was to try and harness this new technology, essentially to create a better, more engaging front end for their customers. And yes, there's a productivity aspect to it, but also it's back to where we were a moment ago with the doctors. It's actually how do you make it more engaging and the success that they've had in using this to really drive customer engagement and customer satisfaction. And to do that in obviously a highly regulated, highly sensitive, highly important market. And in a culture that is used to innovation, but also has incredibly high standards. I mean, I won't tell his story for him. I well let him tell it, but it's an exciting one to be on stage with him talking about.

>> Excellent.

>> Yeah, what a great customer example. And exciting. The whole show is a lot about customer examples. I'm curious, we were mentioning, and we were chatting about your daughter earlier and without incriminating her Rubik's Cube skills. Shout out to your daughter, by the way. Hello. What is your daughter and her friends talking about in terms of Gen AI? Is it a conversation for them?

>> That's funny. So, yes. Our daughter is our youngest, our older two are already in college. And, you know, it's funny, actually. I'll talk about all three of them, so, you know.

>> Yeah, please.

>> Our oldest is about to start a PhD and which in neuroscience. I was a PhD scientist years ago.

>> I was going to say like father like daughter on that one.

Yeah. >> Yeah.

>> And the amount of data, like the extent to which biology labs right now look like computer science labs. It's just amazing. I mean, he got more data in a summer internship than I did in the three years of my PhD. It's just been transformed. Right.

>> That's wild too.

>> Our middle one is poli sci, which he tells me, that is a real science.

>> I studied political science.

>> I did as well.

>> Yes. >> 100% right, okay?

>> We probably got her back, we got her back on this newsletter. Clearly both political science, it's still.

>> Yeah. So, I mean, the role that this is playing, right? In the ability to summarize and ingest like enormous amounts of information and just to really change how the policy field gets done, how the policy process gets done. I mean, nevermind the whole, you know, importance of regulation for sensible use of AI.

>> Yes. >> But just like how it changes someone's life as a policy professional. I saw Politico this morning, they're now sending out like AI generated summaries and so on. It's like if it's reaching like that part of the world, like it's going everywhere.

>> Oh, it's big in journalism.

>> Yeah. >> Yeah.

>> And then our daughter's the real engineer, right? So she's in high school and is very into robotics and so on. And, you know, they have a team that competes in these robotics competitions. And the extent to which they've already adopted Gen AI to like how they compete and win in these like high school robot competitions. It's unbelievable. And, you know, what I'm told, I don't have independent verification on this statistic, but I'm told is this year is the record year for dropouts from computer science in like in elite university programs 'cause people are looking at it and saying, "Huh, why do I need to learn the drudgery of coding?" So we think that's overstated, right? We actually think, you know, the elite coders will have superpowers. There'll still be a need for them. But the shift away from routine coding and into really sort of systems engineering and systems thinking and then into like the human aspects that have to go around that, right? Into how you actually lead and build a team and influence people and so on. That's clearly the wave of the future.

>> Excellent. Well, there's lots of people.

>> And we didn't even mention solving a Rubik's Cube on water skis.

>> We didn't, you know?

>> He brought it up, he brought it up.

>> Well, I think it's really cool. And I think it's interesting too 'cause I mean, I even wonder, you know, we talk about Gen AI or AI, I wonder if to your family for example, it's just a tool. It's not even, you know, delineated as artificial intelligence. They're just, "Oh, I'm using Gemini. Oh, I'm using this product and I'm going to go build this robot, which is rad."

>> Yeah. >> Gosh, things, yeah. Wow. You've been at McKinsey for almost 30 years.

>> Yeah, I prefer to say 29, but yes. (group laughing)

>> That is impressive.

>> 29 forever.

>> And so as a result, I mean, you've been a part of a multitude of hype cycles. Is this hype cycle different, faster, more exciting, or comparable to some of the other technological hype cycles you've experienced in your wonderful career there?

>> So if you say like, this time it's different, right? You set yourself up for that. Like YouTube clip, you know, years.

>> I'm not setting you up, I'm not setting you up. I genuinely want your insight on that.

>> Yeah. >> Genuinely want your insight.

>> But I do, right? So, I think the way we're increasingly talking about this is, this is the fourth platform revolution, right? So, you know, what does technology do in economic terms, right? It lowers the cost of something, right? The first was just in compute, right? Just lowering the cost of doing calculations, right? You don't need, you know, those women with the computers in "Hidden Figures," right? You don't need that anymore, right? When IBM and others transformed basic computing technology. Right, then there was the internet, right? And that transformed, that took down to almost zero the cost of distribution, right? You could get your ideas, your offer anywhere, right? And then, you know, Amazon and others and, you know, many others sort of transform that. And Google, of course, like who would've thought that actually searching the internet would be the most lucrative application that you'd find on the internet, right? Then there's the third platform revolution that was around mobile, right? That was lowering the cost really of access, right? Just the fact that you could have this incredibly high compute power, you know, but really, I guess mobile and cloud together, right? Mobile and cloud together really gave, you know, almost down to zero access to high performance compute. And this fourth one, right? This is lowering the cost of human knowledge and ingenuity and creativity, right? This is like, you know, maybe ultimately driving down towards zero, the cost of being a creative person with all the world's knowledge at your fingertips. So that's a revolution, right? I mean, there have been other revolutions before, but this feels, and certainly for white collar work, right? This feels as transformative or more transformative than any of those that came before.

>> Very well stated and well summarized. Last question for you, Rodney. Well, you've said a lot of exciting things, so I don't know that you can just pick one. When we have you back on the show next Google Cloud Next, what do you hope to be able to say then that you can't yet say beyond the fact that your Gen AI portfolio is worth more than your NFT portfolio.

>> And that he is a bestselling author?

>> Yeah, yeah, exactly.

>> Yes.

>> Worldwide, yeah.

>> So, I would like the dog still to be healthy and happy and warm.

>> Yeah.

>> But I would like to see many more companies and organizations who can point to real transformational business impact in their P&L. And we're seeing the early wave of that. But I think this is the year of show me the money for impact from Generative AI.

>> Show me the money, show me the real, and get there by reading "Rewired." Thank you so much for being on the show with us. Rodney, this has been absolutely fabulous. I hope everyone picks up a copy. Rebecca, always a pleasure. This was a fun one. We're actually over time, we had so much fun. So, thank you so much and thank all of you for tuning in to day one of three here at Google Cloud Next in beautiful Las Vegas, Nevada. My name's Savannah Peterson. You're watching theCUBE. The leading source for enterprise tech news. (bright music)