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Stop outsourcing your AI agenda, with Rik Reppe
56 Plays3 months ago
For decades, executives have struggled to maintain control over their organizations’ strategic direction due to a limited understanding of emerging technologies. This has often resulted in ceding significant influence to tech partners, both internal and external.
However, the AI revolution presents a unique opportunity. Unlike previous technological shifts, business leaders recognize how behind the learning curve they are. They are actively seeking ways to bridge the knowledge gap for themselves and their people. In this episode. Will chats with Cortico-X VP Rik Reppe about how to enable executives to lead confidently in the AI era.
Get in touch with Rik: [email protected]
Follow Acquis Cortico-X on LinkedIn here.
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Transcript
Introduction to Cordico X and Emerging Technologies
00:00:00
Speaker
Cordico X is an experience-led transformation business that partners with clients and technology companies to drive digital acceleration. We are experience activists, passionate about elevating everyday human experiences through the belief that what's best for people is what's best for an organization. Reach out to us for a chat. A link is in the show notes.
00:00:34
Speaker
Hello and welcome to Speaking from Experience from CorticoX, where we speak to the people with experience of experience. I'm Will Kingston. Whenever the next big emerging technology arrives on the scene, the response from senior leaders is consistent and predictable. They know it will impact their business, even if they aren't quite sure how dramatically. They know their competitors will be adopting it, and so they know they need a strategy for it. There's just one problem. They almost never understand it. If there's one thing that the internet of things, augmented reality, and blockchain have in common, it's that they certainly weren't a part of 1980s MBA programs. The knowledge gap is a big problem because senior leaders end up outsourcing their strategic agenda to well-meaning vendors or internal IT partners with mixed results.
Understanding AI's Holistic Business Impact
00:01:30
Speaker
AI is the emerging technology of the moment.
00:01:34
Speaker
Interestingly, I've noticed one big difference this time around. Business leaders are aware of their knowledge gap, and they seem to be aware that AI is too big and will impact their business too holistically to simply outsource an AI strategy to someone else. They need to take control. So the key question for leaders is, how can you build an understanding that will enable you to lead the AI strategic agenda for your business?
Insights from Rick Repi on Technology Waves
00:02:04
Speaker
To help me answer that question, I am delighted to be joined by CordicoX VP and the leader of the firm's AI practice, Rick Repi. Rick, welcome back to Speaking from Experience.
00:02:15
Speaker
Thank you. i am I'm still trying to recover from the comment on the 1980s MBA program. While I don't have an mp MBA, i as someone who's ah whose age has hit a level where the first integer is such that you cannot deny your old guy's status, I feel like that was a shot. I'm scarred i'm scarred by it, but it's a cogent observation, Will, like in all seriousness. 80s, 90s, this was we haven't had a learning structure to prepare business leaders for when the new hot technology in and of itself can teach itself and adapt. Like that's a little different.
00:03:02
Speaker
And we will get there, but before we do, let's talk about some of those previous emerging technology waves, which you saw. I'll add a bit more salt into the wound. I wasn't around in the eighties, so I actually can't speak to you in a way that you can. You've seen a few more waves than I have. What can senior leaders learn from some of those emerging technology waves that you've observed in the past? I think the, um, I think there are two big ones. I think one is do not rely on ah exclusively on third party vendors.
Strategic Agenda vs. Over-reliance on Vendors
00:03:39
Speaker
Don't rely on those third party vendors until you have created a coherent and value creating strategic agenda. Of course, those vendors are selling you something specific. It's the definition of their business model. They have to. And so by definition, it's going to be limited to what they can deliver on and what they've chosen to bet their business on.
00:04:02
Speaker
And they're smart and they're good, but you don't necessarily know how to you don't necessarily know how to evaluate those vendors. And I saw it back in web 1.0 and extending through insert technology name here. I just kept seeing where, for the most part, businesses are letting those third-party vendors dictate the strategic agenda because they show up with like, hey, I can get you going on something. And it's a totally human impulse to go, oh, thank God, right, help me get out get out of this, you know, kind of feeling behind and overwhelmed. That's number one. Number two.
Engaging Young Talent for AI Innovation
00:04:40
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And these things are linked.
00:04:42
Speaker
You've got a 25 year old in your company right now that knows a lot more about AI than you do. Why don't you go find her and talk to her and ignore the linear hierarchical structure that you have that dictates dictates when someone has a level of gravitas that you will actually see. to learn from As it's the younger folks, matt comes from that comes from the observation that as I've taught digital innovation at the University of Southern California in their Marshall School of Business, what that means, Will, is over the last two to three years in particular, it's rapidly becoming a class about AI, about the strategic application of it. And here's the observation is that every student, graduate, undergraduate, coming into that class,
00:05:32
Speaker
coming into that class knows more about AI than any non-technical business leader I've had the pleasure of working with. As that means coming out of it, they know a truckload more, and you're hiring these folks. You're hiring them. They're out there in their part of your workforce, but they're so far down the food chain that you don't reasonably have access to them, and it's hurting you. We both came from one of those well-meaning consulting firms, a big well-meaning consulting firm. And I recall that there was a an initiative on the behalf of the CEO where he would pick out, well, his chief of staff would pick out an associate at random once a month to do a lunch to be seen, to be engaging with the next generation. And it was inevitably followed with a LinkedIn post
00:06:24
Speaker
and it all came off a bit insincere. How do you actually go about doing this, engaging with the next generation as a senior leader who's got a lot on their plate in a way which is genuine and real and in which there is ah a value exchange there as opposed to it just being a cheap LinkedIn promotional opportunity? So how do we take it out of the realm of theatre into exactly something that's actually useful? but Well first, look, as ah ah as a VP, a senior VP, an executive VP, a C-level executive. It's not like you're hanging out with copious free time. And so you have a real challenge with like, well, how do I even find those
Prioritizing AI Initiatives Strategically
00:07:05
Speaker
folks? You have internal AI initiatives going on right now. I have yet to encounter the client that does. And so this is ah an answer that's going to seem heretical. And I'll ask for the listener's patience. You don't have
00:07:21
Speaker
something that will have a greater impact on your business long-term going on right now that isn't called AI. Because AI is, you know, and it's terribly overhyped, but the reason it's terribly overhyped is artificial intelligence. Sentience, where sentience didn't previously exist, that's big. It fundamentally changes everything. It's not all showing up tomorrow. right you know There's going to be an acceleration path, but that path is happening faster than we anticipated. And so that means that as a senior leader, you should find opportunities to sit in on actual working team sessions. I know you don't have the time in your calendar, but I would challenge you, and I'm saying this just because I did it myself and to myself, I would challenge you to interrogate your calendar.
00:08:20
Speaker
and see if like, really? I mean, like yes, I have a bigger immediate fire burning right now, but is it really bigger than this thing? And in some cases, the answer will be, no, I can't move this meeting or I can't miss this meeting. But you will actually find that there are quite a few that you can. And as you sit at that direct line level interacting with folks, you will find that young talent because they cannot hold back for very long. They're listening to all of us old people get it wrong. I think there are, oh, I think, Will, I think you may have shared it with me. There was an interesting article from Forrester that I just saw today. Look, I promise you, those recent graduates of graduate programs or undergraduate programs, they know that generative AI is bad at math, like so bad at math that it doesn't do it.
00:09:11
Speaker
Like that's that's just not what it is. They know that the real value of generative AI is not generative AI as a standalone, but the other capabilities and forms of AI that you snap it together with, that's what really lets you start solving problems. They know that. The fact that us older folks don't means that we are then you know very much swayed by well-meaning internal and external IT partners. that yeah we need we need and that we're going to work with, but we're bringing them in too soon. And those younger folks are going to help us get to a better answer faster about what we solve, how we solve it, and when we solve it. AI is a big deal. Leaders need to be able to understand it, not on a superficial level. They really need to really understand it if they want to understand how to ingrain it within their business. We will get to some deeper ways of being able to do that. But before we do, I just want to cover off a couple more of the ah problems that leaders may experience if they don't do that.
00:10:13
Speaker
I've heard you use the term executives playing whack-a-mole with AI before, and I imagine that is potentially a symptom of this. What do you mean when you say that you see executives playing whack-a-mole with AI? because and This is a totally natural human thing. When you know, oh, wow, man, here's a big thing that I better pay attention to. It's got focus and attention, but you don't know a lot about And I'm not talking about you have to become an expert and in the the underlying mathematics and algorithms or in understanding the history of the evolution of AI for the most, but like I find that stuff fascinating, but I don't need it to apply it at a business level. But you you got to move and you know, you got to move. And so one of your folks comes to you with, Hey, we could get an enterprise version of a gen AI tool that will
00:11:08
Speaker
summarize all of our personnel reports faster than anything that we're using right now. Cool, do it. And oh, hey, here's a generative AI thing that we can use to create all of our marketing content. Nope, sorry, I already got something in the hopper with personnel and we've, you know, our budget is constrained. Well, I'm not, since I just made both of those up off the top of my head, they're real things that I've seen clients doing. One, both of those are low value. They're really not. the highest and best use of the of a new technology. It doesn't mean don't do it. It just means, you don't really want to prioritize that number one chew up budget. So it's kind of like they just respond to the loudest noise, somebody inside their organization who put in the time, who put in the thought and is really pounding it. And they don't have an ability to go, well, that actually sounds like it's prior seventh priority and not our first and our first thing we're going to do. And that's really what we're seeing a lot of will is not
00:12:05
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I'm not working currently with any clients that are applying and implementing Gen AI in a way that is like stupid and zero value or even negative. But I do see a, oh, you're gonna wish you'd gotten a different Gen AI vendor given the three other things that we can now see that you very much need to do that a different tool would do better. right That's the kind of thing, and that's where whack-a-mole leads you. it's not like you know As consultants, we' like we're almost trained to like put things in apocalyptic terms. right If you don't do this, you will go out of business. probably not Probably not. But if you do X or you don't do Y, there's a really good chance that you're leaving money on the table. There's a really good chance that you've put yourself in an unfavorable competitive position. There's a really good chance that
00:12:59
Speaker
you know, just by tweaking something about 15 degrees, one direction or the other, you could have put yourself in an awesome competitive position and instead you either missed it or you missed it badly enough that you knocked yourself back a little farther than when you started. That's, um if I recall my Economics 101A around efficiency in business, that's bad. And there's a solve for that. Well, that's a lovely segue. Let's talk about that
Active Executive Engagement with AI
00:13:28
Speaker
solve. Let's talk about how you teach AI effectively or the receiving end, how you can learn about AI as a senior leader. up One of your passions is teaching. You mentioned earlier that you are a university lecturer when you are not doing your day job. What have you actually learned from teaching students that you would apply to teaching AI to business leaders? And perhaps where does it differ? Well, one, I would rather teach students. And I'm actually using me.
00:13:56
Speaker
as the target of the teaching. You know, I've had a long career and I've accomplished a lot of stuff. Not surprisingly, that means I think I know some things. It can be very hard to teach something new to someone who has had success doing something in a particular way because like we can see it very easily with someone else. It's very hard to see in ourselves like, know dude, you're kind of locked in. you've kind of got an ideological vapor lock and you're just being resistant for the sake of being resistant. Can't teach an old dog new tricks. You can, but you probably got to wrestle with it first. ah You know, or kind of, you know, have a few heated discussions. But the biggest thing I learned when it came to anything, yeah kind of technology in general, but emerging technology in particular,
00:14:49
Speaker
oh Really, it was stuff that I learned way back 100 million years ago when I was young and you know had a waistline and things like that. When I was an undergraduate studying theater, you immediately applied things that you learned and you didn't learn the whole thing before you started applying. Now, once we started applying that structure in the university class, it took off. And so I did away with things like tests. I only do homework because I have to. And so I do the absolute minimum amount and the entire semester becomes, here's a concept, apply it, here's a concept, apply it. And over that course, we build out a, an innovation strategy or over the last two years, an AI strategy for a very specific client and client need. And so, I mean, this came about by talking to a client and he was curious about what I was teaching and I explained it to him and he's like, why don't you do that with us? Like, oh, why don't I do that?
00:15:47
Speaker
And part of what resonated with him and subsequently, well, what has resonated with other clients that we've worked with in our explorations offering is um we don't ever leave you too long in passive reception mode. It's not like a class. What we're really trying to do is accelerate the timeline for you to get up and running in pilot phases with AI. And so you'll learn a concept about AI, you apply it and we give you the next concept, you apply it, we give you the next concept, you apply it. And that is proving to be, that is proving to play even better with executives than it has with students, even though students love it, right? Because it's very active. Because like as an executive man, you don't have, the the one thing you ain't got is tough.
00:16:33
Speaker
Right. And so you you want to be moving fast. That's one. And two, you know, you have a lot of smart people, but you got to do it in such a way that they are engaged and active. Active is really a critical component that they will sustain their enthusiasm and their engagement and their participation, which means you get sustained brilliance from them and from their experience, from their insight. And so we just, The same things work with both audiences. We have to be more succinct, and we have to jump much faster to action when we're talking about an executive audience. But other than that, it's pretty similar. So make cortico explorations real for me. Give me an example of that learn, apply sequence.
Exploration Programs and Creative AI Implementation
00:17:19
Speaker
OK. So okay so we're working with we're working with a life sciences client. We've worked with a few in this space.
00:17:26
Speaker
and They were really struggling with what do we do with Gen AI. And so we ran them through this program. The first thing we did was through asynchronous i'm sorry synchronous learning. So I don't know why I was using asynchronous. as synchronous We did a big old Zoom call and we ended up doing quite a few of them because it proved more popular than we had anticipated. We're two hours and we just kind of gave them, hey,
00:17:57
Speaker
Here are some of the critical concepts about AI. And if you understand these, you are well on your way to being able to create your own AI initiatives. And in fact, we can do that in two hours. And, you know, we thought we were going to get 20, 25 folks to participate. We ended up with over 60 and we had to add additional sessions and all that good stuff. And they were like, okay, well now you're excited. So let's actually help you identify critical problem statements and get just a little bit deeper on some of those core concepts that we taught you the first time so that you can start creating your own proof of concept proposals associated with, you know, right now, to be honest with Gen AI just as the gateway drug. But to throw out a teaser, I guess, Gen AI that is never paired up with predictive AI,
00:18:49
Speaker
is always going to leave you a little bit wanting for more. And so as we taught folks about that, that universe of AI opportunities that exist, and, you know, I mean, it is literally a universe that's not like covered everything or even tried. And that's part of what you kind of outsource to us as we make sure it stays fresh. We arm you with those things and then we turn you loose with some coaches. right, to help these teams of really smart, really capable business executives that do not know a thing about AI walking in the door.
00:19:22
Speaker
And they come up with the coolest stuff, man. Like, I mean, really, just once we've kind of gave folks the um permission to play and permission to dream, and the confidence that they now know enough that they can do that and have it be at least a little bit realistic. And again, it's all stuff we saw in the class that I was teaching at the university level. But also not surprisingly, um those kids that I teach, they are more creative faster, but far less knowledgeable throughout. Not a surprise. The executive audiences and the line level audiences, folks that are grownups that are in the workforce, takes them a little while to believe that they actually can go nuts. And I'll give you an example in a second of what going nuts looks like. That they can go nuts and not only will it be okay, but it has a high potential to be rewarded in the form of something gets adopted and you see your idea all the way through and it can become a very good
00:20:17
Speaker
career move for me. And by going nuts, I guess the best example is one client we worked with, one of the sponsors was saying, well, we don't want people to waste our time by coming up with, I want a 24-7 holographic virtual assistant following me around and I come off. And I was like, that's exactly what we want people to come up with. That is precisely the kind of thing we want people to come up with because while you may or may not hit that anytime soon, if that is your target, and you reverse engineer the path that it takes you to get there, you will come up with wildly creative, differentiating, value-inducing things just to get to that point that you don't believe you can get to. It's kind of like um all the things from the space program that ended up throwing off billions of dollars of new value.
00:21:08
Speaker
before you ever got to space, just all of those things that it took to get there in those incremental steps. It's very similar. And so I guess, you know, if there's a recurring theme here and it, ah you know, it troubles me to say this because I want to believe wealth is something I will die of being terminally creative. We're not doing anything new in that the techniques that tend to work been around for a long time. The, the prior examples that can give you some measure of comfort that this kind of approach does work existed for
00:21:40
Speaker
centuries we're so much recognizing as such right because it's like well but what does that have to do with ai
00:21:48
Speaker
So you learn? You apply in the form of building out some proof of concepts. My very large, very well resourced research team has informed me that there is an element of showbiz, a bit of theater after that point that you like to incorporate into the process. There's always theater. Yeah, there's always theater. So earlier we were kind of denigrating theater. Oh, theater's good. Just applied in a useful way. It's good.
00:22:20
Speaker
so It can take on a lot of manifestations and it has in the client work that we've done and are continuing to do in this area. where we've done things as outlandish, as staged, essentially a game show with a corporate all hand, where the four top proposals came in and did a presentation in a very TV-esque kind of fashion. that that you know Your calendar doesn't always lend itself to that, and it's not the purpose, it's the vehicle. It's the vehicle to get other folks to want to participate.
00:22:52
Speaker
and Also, we find that some version of theater guarantees that we don't lose an element of play and of fun. And ah that is, we find, critical to getting good outcomes, is that sense of play, that sense of fun. And firmly believe that there's an ROI on fun. But it's very easy to go in with, this is my pet project. And I guess maybe what the example would be, every client I've worked with, when you first start talking about AI, they're like, well, we got to get the basics first. Like one, what is that? What are the basics of AI? I dare you to answer that. I dare you to go to, you pick your five AI experts and ask them what the basics of AI are. You will not get the same answer.
00:23:44
Speaker
Because we're still figuring out what that means as far as its application in business, no matter how mature we pretend to be in our knowledge and understanding of it. That's a lie we tell ourselves so that we can play safe. But why would you play safe with sentience where sentience hasn't previously existed? like on earth would you go now In the long run, you want to have a balanced portfolio and within a corporate setting, you'll have plenty of folks who come up with really smart, really good, incremental improvements at scale by applying AI. And that's fantastic. Those things are going to show up. You don't have to make them show up. The ones where you need that sense of play and thus the sense of theater, whether it's a big game show or whether it's a whole poster campaign that we did inside another organization, where there's a series of
00:24:32
Speaker
animated videos showing what's coming next that your colleagues came up with and celebrating the folks that came up with that. You want to not just come up with some AI initiatives for the next year. You want to come up with a way of creating business value with AI, and you cannot terminally rely on external vendors for that. Or you can, but you've just outsourced the biggest chunk of value. that you have control over to someone else. And that is, by definition, self-limiting. And we would suggest you don't do that. My understanding is that AI is one, I guess, curriculum is is the word within cortico explorations. But there are a couple of other accelerators. It's one of our accelerators. It's the only reason, Will, that I'm pushing on the word curriculum. Because you're right. There is a curriculum. is that Really, we're talking about acceleration.
00:25:29
Speaker
more than we're talking about, hey, let's all go take a class. It's like, eh, class is just a vehicle for getting you some really cool proposals. And so it it's the acceleration that's the value.
AI, Data Excellence, and Machine Customers
00:25:40
Speaker
Learn, apply. Another one, another accelerator within cortico explorations is data excellence. How do you think about the relationship between AI and data excellence? And why have you put those two together within this broader cortico explorations proposition? Well, not surprisingly, it turns out they're related. so you do not So data infrastructure, data governance, and data management, which we roll up under the rubric of data excellence. One of those lies that we tell ourselves in court in the corporate world is, well, if you don't have that, you can't even do AI. Yeah, you can't. You can't sustain it. And you're not going to be able to scale it. But you don't have to use it as an excuse to not start.
00:26:28
Speaker
and Start, play, experiment, but know that you better get data infrastructure, data governance, and data management locked down because AI is driven by data. deal like there's There's not the non-data form of AI. It doesn't exist. And so we've been able to have, and that's going to drive every one of my colleagues who's a data scientist nuts to hear me say, what i'm about to say we've been able to be sloppier because the technology was less advanced. Now, all those data scientists are going to like hunt me down and, and harm me for saying that because it always would have had a benefit. But because we've opened this gate with AI and how valuable it can be, and because, oh boy, we do not have a governance structure in place that allows us to deploy AI strategically. And like, you know, I'm, I'm not,
00:27:23
Speaker
someone who gets excited about governance, never have been. But I have seen a lot of good AI initiatives fail because you didn't have governance in place. And so we did what we do inside a consulting company like Cornecoax. We went out and hired some data scientists to help us solve that problem. And it's really resonating with clients. And so we have those clients who are much farther down the road thinking about ai and their understanding of it to the point where it's like, oh God, what do we do with the data? And we wanted to have something that would allow us to help them as well. And so whether it's a, you know, hey, we'll do an AI exploration followed by a data excellence exploration, or we'll do one or the other or any permutation of combinations across those things.
00:28:08
Speaker
We found that it was really helpful for our clients as we just thought about the maturity arc around AI to make sure that we had a mechanism to help you when it came to governance management and infrastructure. Another accelerator is machine customers, which may be something that that some people haven't heard of before. What is a machine customer and why is that in the mix? A machine customer is literally, is exactly what it says. So, you know, if I look at any one of our corporate clients, big clients, medium clients, small clients, small size clients, they're, they're all seeing the value of turning bots loose on their customers. B2B, B2C, B2G doesn't matter, but they're all saying, Oh wow, we can actually do a lot with gen AI slash conversational AI fueled bot. And they're right. How are we missing?
00:29:02
Speaker
that a customer might just turn a bot loose on you because that's faster and more efficient for them in the same way that it is for you in some areas. In addition to that, once you start thinking like that, then you also start thinking like, ah do I make a product that should be a customer? ah Think about that. right That's a new thing. Can I turn the product that I make into a customer? So to just use an example that I think a great many folks will be familiar with, Tesla. Now, a lot of the things you buy, services and goods, you buy for a Tesla, you don't buy. Tesla buys. Yeah, yeah, yeah, you gave it permission, et cetera, et cetera, whatever, whatever. But you ain't in the transaction. I have sitting next to me an HP printer.
00:29:49
Speaker
I do not buy the ink for that printer, but I never run out of ink. The computer is its own, or the device is its own customer. It buys for itself from the same company. Now that's a, without spitting out down a ah big rat hole, that's a bound relationship, right? So a curing coffee maker can order more coffee pots, but that'd be cured pots. So, okay, cool. But I guess it's phase one. And same kind of thing we're seeing, we're seeing the same kind of thing with machine customers. Well, that we were saying with generative AI and its application of business, it is so close to a tipping point that we think that the predictions for the speed at which that is going to become a significant driver of GDP globally is wrong. And so the most aggressive forecast that we see of that is in the 2030s. We think it's going to be in the late twenties. And the reason we think that is because it's already happening.
00:30:45
Speaker
This is not a, this is not futuristic. And so we think that that's going to be the same kind of thing. Like what does this even mean? All right. Well, let's help you understand what it could even mean. And then you'll figure out where your own products become customers or how you're going to interact with customers. You just think about it, right? Like everything we have around journey maps. What's a journey map for an ah algorithmically based customer? There is one, but it ain't the same one. felt It's going to be pretty substantially different. Fascinating. So we want to help you with that. Add machine customers to the list of things that weren't on a 1980s MBA curriculum.
00:31:24
Speaker
we No, but it was probably in a computer science masters. Rick, this has been fascinating. Your details are in the show notes for anyone who wants to reach out to you and chat about cortico explorations in more detail. Thank you for all the work you're doing in this space and thank you for coming on the show today. Thanks for having me. you know I love being on. And thanks for doing the show, man, and reaching helping me reach out to an audience.
00:32:02
Speaker
what