Name: The Exponential Power of Generative AI in Business Part 1
Uploaded: 2023-12-18
Duration: 11 min 21 s
Description: Pat Geraghty, President/CEO Guidewell, Jeff Tarr, CEO, Skillsoft, Terry Rasmussen, President/CEO Thrivent, Glenn Fogel CEO and Director, Booking Holdings, Roberto Martinez, President, PepsiCo Mexico Foods

Pat Geraghty, President/CEO Guidewell, Jeff Tarr, CEO, Skillsoft, Terry Rasmussen, President/CEO Thrivent, Glenn Fogel CEO and Director, Booking Holdings, Roberto Martinez, President, PepsiCo Mexico Foods

The Exponential Power of Generative AI in Business Part 1

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The Exponential Power of Generative AI in Business

Pat Geraghty,CEO Guidewell, Jeff Tarr, CEO, Skillsoft, Terry Rasmussen, Thrivent, Glenn Fogel, Booking Holdings, Roberto Martinez,  PepsiCo Mexico Foods

Chat GP T has enjoyed this sort of uh stratospherically fast adoption in the consumer world, fastest adoption of any new technology in history. I can't keep up with the numbers myself, but it's been kind of instantly omni uh present but big business as far as I can tell from various conversations I've had and from some new polling data we have is still being kind of cautious, not about A I generally uh predictive A I data analytics. That's all moving ahead but about generative A I and how to use generative A I in business. I assume you're having a similar experience to what I'm having. And if so, I wonder if you could explain why the caution. Yeah, we are allen. I think it's a great, it's a great question, a great observation as to what's happening. Um There's no question, generative A I and, and particularly Chat GP T is having a moment and that, that moment's been unfolding over the last few months. And I think the reason big businesses are cautious is the same reason that it's having a moment which is, um, largely people were awestruck about the capability that they were seeing and the accessibility of A I tools in a very, very different way than what has been the discussion over the last few years. And those in the tech community know that that didn't happen overnight. And this investment in this capability was being built over time. But for many people who were not close to this technology, suddenly you had this, this moment that unfolded as people watched the capability of generative A I to deliver really, really thoughtful responses, sometimes fully accurate, sometimes not fully accurate. And it, and it opened up this question about, well, how do we use this? Clearly, there's power here. How do we use this the right way? How do we use it in a responsible way? And every single client I'm talking to is trying to figure out how to go fast but how to go fast in a responsible way right now. And so Joe, if you had to sort of pinpoint the three or four things that are causing that caution, say, yeah, we gotta make sure we work out ABC D, what would you, what would you say? Well, I think one is clearly um confidentiality in the proprietary information. How does that actually work in an environment that is by its nature has, has elements that are open. And so everybody is asking the question if I'm really going to use it for my business, I wanna put business data in there. But if I put business data in there and it's in the public domain that, that doesn't work out for any of us. So that proprietary data question is, is clearly top of mind. The second one is, what am I using it for? And I'll, I'll, I'll describe it as the right use for the right business case, the right use cases. And I think because it, it feels very new to a lot of people. They're not really sure what the applicable use is, they see the power, but they're not sure how to direct that power to the right things. And that, that leads me to the third piece, which is how do I prepare my people for what's happening? Um You see all kinds of estimates of what the implications are going to be on productivity, on the ability to take tasks off of people's plates. Well, that converts into people's jobs and that causes large organizations to take a breath and figure out how that all plays out. So preparing people for the change and in our perspective, and many of you probably saw the PWC announcement. We, we think that comes down to training people to take advantage of the technologies because we know that if you don't prepare people for the technology, it's coming anyway. And so part of the responsibility we see for any organization, but certainly big employers is to help your people prepare for the changes that are coming. Yeah, that's good. Thanks. Uh Chris. Let me uh let me turn to you. I wanna go into each of those uh things that Joe mentioned. But I, but I, but I'd love for you to start to just, you have these conversations every day. I would imagine. In fact, I doubt you're getting much sleep these days. Uh But uh I, I wonder if you could just talk about why this moment is so important to business. I think we see the transformative potential of A I and, and it's, it's not only transforming the tech landscape, but it's gonna transform business, it's gonna transform much of what we do as humans. And, and this, as you mentioned, differentiating what we've known as A I, which is more around machine learning and predictive technologies from what we've seen to where we are today, which is really the generative A I era, which is truly changing many, many things. And, and you know, what we see is really a, a bifurcation. As you, you know, Joe, I think well stated some of the, the ways in which larger organizations are approaching A I, you know, certainly in the tech landscape and, and, and the start up world. Um you know, we've seen literally thousands of start ups in the last six months move into this space. Uh There's just a tremendous amount of speed and innovation happening. You know, I happen to sit here in San Francisco and there's literally a hackathon happening nearly three or four times a week and it, it's just the, the amount of energy going into the space is palpable. Uh, and it's, it's, you know, we, we see the innovation opportunities. You know, there's, there's, you know, companies going after marketing, there's companies going after customer support opportunities. Uh There's a lot of tooling, focus areas, uh, speech recognition, you name it and it's just, there's, there's just a number of different approaches that, that organizations are taking and, and I wouldn't say that all large companies are, are being cautious, you know, for example, um you know, we've already been working with companies like Carmax as an example that are, that are using generative A I as part of their uh review process and making, you know, really being able to synthesize the information better for their buyers. Uh Epic is another one in the health care software space that's uh that's been working with us on, on A I and certainly PWC and Joe and his team uh are working with us in this, in this like is in this regard as well. So we, we are seeing movement here uh in companies of all sizes. Can you talk a little bit about the first issue Joe raised which is protecting proprietary data, the confidentiality. Uh uh there was a story this morning that says Apple has told its people to not use chat GP T. Now that may be because they have an alternative technology that they want to adopt. But in general, I find a lot of business leaders worried about mingling their proprietary information with the public information that's in these giant large language models. Proprietary information is certainly got a lot of value. And we, that's a common conversation to be having right now with any organization is. How do I make sure that I have good protections, good safeguards around my information. I will just state for a moment by the way, that, that, that was true before. Generative A I, that was, there was a lot of concern in most large organizations around uh protecting their data. But I think that's more, you know, I think most or organizations are trying to understand in the era of generative A I and if I'm gonna use generative A I, how do I make sure, how do I ensure that my information is well protected, it's utilized effectively. And so as I think Joe said it, well, most organizations are just trying to understand exactly how that's gonna work. And that's something, you know, we've, you know, we spend a lot of energy on that with our customers and helping them understand and there's different methodologies that you can use. You'll hear, you'll hear terminology like fine tuning the model. Uh you'll hear terminology like grounding the model. Um There are these are different ways in which organizations can use um generative A I models, large language models uh to, you know, on their own information without passing that information back to the, to the base level model itself. But it's a solvable problem. In other words, it's absolutely a solvable problem. And, and then the other, the second, uh, issue that Joe raised was the, in a way the enormity uh, of potential for these models. I think people have a hard time figuring out. Where do I start? Where's the highest value? What's the, what's the first place where I should apply this? And how, how do you, uh again, I'm sure you're having these conversations every day. How do you walk companies through that uh conversation? They're, they're absolutely, there's absolutely a progression to this, that, that organizations I can think about. I think at the, at the, at the base level, if you will, what I always tell people, certainly leaders is the first thing you can do is just familiarize yourself with using it. That's one of the great things about having, you know, bing chat or chat GP T and some of these tools available in the market. If anyone can use it, a leader can use it. You know, Alan, you could use it to develop the questions you might ask us today. Perhaps you've done that. I did. Yeah, these are not my questions, but you're doing great. So keep going. Uh And, and that, you know, that's a, that's a, just a great way to familiarize yourself with some of the ways in which um these products can work. And then II I think from a, from a productivity perspective, you know, we've approached this by saying the first step is really these co pilots. You know, the first product we brought to market was something called github co pilot. It's a tool to help developers with their co you know, writing code. It, it works alongside the developer, uh the engineer and we're bringing that co pilot capability to a variety of different applications, whether it's Outlook or Word or Excel uh powerpoint. Uh You can obviously we, we're even bringing it to, to cyber security. That was a topic you brought up earlier to help uh those who work in your security operations center to be more effective at their role. So the first, the first step in our in our approach is product activity, bring a co pilot along with you. It'll make your knowledge workers more effective, help them get up to speed quicker on topics. And it's like it's like having this really, really smart assistant who can help you do many things uh in a very short period of time without you having to go out and research large amounts of information. And then from there, you can see how um ultimately you can use this in customer facing operations, you know, customer support category that we believe is gonna have a lot of application for generative A I I think it's an there's opportunities there to provide even better experiences for customers. And then I always advise organizations to think about the long run, which is what's the new thing we can do? What's the new business model we can create or product that we can bring to the market? Uh That's something that should be on everybody's radar screen doesn't have to be today, but it's something you should be thinking about over the long run. Do you on these co pilots or are, are you uh thinking about developing industry specific co pilots, uh role specific co pilots? How, how far will Microsoft go with that? So through nuance, for example, which is a uh a company we bought last year, we're bringing some of the same co pilot capabilities into the health care space through assisting physicians. Uh We work, we'll be working with partners like PWC as an example to go into several industry verticals. Uh So yes, absolutely. We believe that co pilot model is going to be applicable to a variety of different industries. Much of that will work with partners to bring to bear because we're, you know, Microsoft obviously cuts across so many different spaces but and this is where expertise of different partners and different organizations we work with becomes I think really critical to developing the right tool set.