 Live from Miami, Florida, it's theCUBE. Covering IBM's data and AI forums. Brought to you by IBM. Welcome back to Miami, Florida, everybody. You're watching theCUBE, the leader in live tech coverage. We go out to the events and extract the signal from the noise. We're here covering the IBM data and AI forums. Scott Hebner is here. He's the CMO and, sorry, VP and CMO of IBM data and AI. Something like that. Yeah, right. I know you as the CMO of the data guy. So, welcome. Welcome to theCUBE. Thanks, always great to be here. Great event. I mean, I'd never attended one of these before, this sort of analytics university. I mean, 1,700 people, everybody's like sponges trying to learn more and more and more. 60% higher attendance than last year. Awesome. Congratulations. A lot of interest. So, if we go back a couple of years ago, you know, maybe he talks about digital transformation, people roll their eyes, they think it's a buzzword, but when you talk to customers, it's real. They're trying to transform their business and data is at the center of that. So, if you go back to like 2016, there was a lot of experimentation going on, kind of throw everything against the wall, see what sticks. It seems, Scott, based on the data that I see, that people are now narrowing their bets on things like AI, automation, machine learning, containers. What are you seeing from customers? Well, I think you framed it well. I mean, if you kind of think about it, digital transformation's been going on for almost 20 years, with the advent of the internet back in around 2000, late 1990s, everyone started getting on the internet, doing business transactions, and slowly but surely digital transformation was taking effect, right? And I think clients are now shifting to what we can call digital transformation 2.0. What's the next 20 years going to look like? And our viewpoint from what we're learning from our clients is, if you think about it, it's data that fuels digital transformation, right? Without data, there is no digital transformation. There's no digital, because it's all data-driven, evidence-based decision-making, using data to do things more efficiently and more effectively for your clients and your employees and so on and so forth. But if you think about it, we've been using data as a way of looking to what has happened in the past or what is happening now. And clients with digital transformation 2.0 want to shift to a word of predictive data. How do you predict and shape future outcomes, right? And if you think about it, it's AI that's going to unlock predictive data. And that's why we see such an intense focus on AI as really the lynchpin of digital transformation 2.0. And of course all that data needs to be virtualized. It has to sit in a hybrid cloud environment. 94% of clients have multiple clouds. So if AI unlocks the value of the data in predictive ways, the cloud in a multi-cloud environment is that platform that has to be built upon. And so that's why you see this enormous shift to AI in terms of an investment priority along with hybrid multi-cloud. So I like this point of view, this digital transformation 2.0, because what's interesting in a business and a digital business, it's how they use data. And IBM's mission, at least in your group, is to help people better take advantage of data to drive business outcomes. I mean that's pretty clearly what you guys are doing. There's 2.0, to me, the innovation cocktail is data plus machine intelligence or AI, and then you scale it with cloud. And so you talk about cloud 2.0 really involves this predictive sort of component of the equation that you're bringing into it, doesn't it? Yeah, when I think of this next phase, there's several things that clients are trying to achieve. One is to predict and shape future outcomes. Whether it be inventory, whether it be patient care, whatever it may be, a customer service call, you want to be able to predict what the call's going to be about and what the client or what the customer has gone through before, what their issue may be, right? So this notion of predicting and shaping the outcome. The second is empowering people to do higher value work. How do you make them better at what they're doing? The superpowers of being aided by a machine, or some kind of software that's going to help you be better at what you do? And then of course this whole notion of this automating task that people don't want to do, automating experiences in intelligent ways, this all adds up to like new business models, right? And that's where AI comes in, that's what AI does. And so I do think it's a linchpin. And what clients are looking to invest in is this notion that you need one unified platform to build upon for the future. That is cloud services, data services, and AI services, all is one thing. One cloud native platform that runs on any cloud and completely opens up where all your data is, you run your apps wherever you want to run them, secure to the core, right? And that's what they're looking to invest in. So you guys use the sort of tagline, you can't have AI without AI, AI being information architecture. So for years in the queue, we've been talking about bringing the cloud model to your data, because you don't want to move data around. Now you're talking about bringing machine intelligence to your data wherever your data lives. So talk about why that's important and what IBM is doing both conceptually and from a product standpoint to enable that. So the number one issue with AI and actually the number one issue that sometimes results in failure with AI is they don't understand the data. Some 81% of clients do not understand the data that they're going to need for their AI models. And if they do understand the data, they don't know how to make it simple and accessible, especially when it's ever changing. And then you have all the issues of compliance and quality and, you know, is it a trusted set of data that you're using? And that's what you mentioned about there is no AI without an IA, which is information architecture. So it starts there. Then two, to your point is data is everywhere. There's thousands of sources of data, if not more than that. So how do you normalize all that, virtualize it, right? And that's where you get into this one platform, any cloud, so that you can access the data wherever it sits. Don't spend the money moving things around, the complexity of all that. And then finally, the third thing we're looking to do is use AI to build AI. Use AI to actually manage the life cycle of how you incorporate this into your business. And that's what this one platform is going to do, right? Versus enabling customers to piece together all this stuff. It's just, it's too much. So this is what CloudPak for data is and does. Yes. So when you say AI for AI, you're talking about picking the functions and automating components, prioritizing how you apply those algorithms, is that right? Yeah, so I think we talk about data. The three big things to really focus on is data. And that is the whole notion, you need that information architecture that's ready for an AI and multi-cloud world, because it's all about the data in the end, right? Two is about talent, right? Talent being skills. Are you able to acquire the skills you need? So we're trying to help our customers apply AI to actually generate and build AI and to optimize AI so they don't need as much skill to do it. In other words, democratize the ability to build AI models for your business. And then finally, the data's everywhere. You need to have completely open environment and that's the run on any cloud notion. And that's why the red hat open shift is such a big component of this. So think of clients are looking to climb the ladder to AI. Modernize their data states, make their data simple and accessible, create a trusted data foundation, build and scale new models, and infuse it throughout their business. CloudPak for data is essentially the foundational platform that gives you the ladder to AI that is endlessly extensible with things that may be important to you or certain areas of additional capabilities. So CloudPak for data essentially is the platform that I'm referring to here when we say any cloud, right? So I feel like we're on the cusp of this enormous productivity boom. If you look at the data, productivity in the first quarter went up not if you believe the Bureau of Labor Statistics, but over the long term, productivity numbers, you probably can believe in them. I think for Q1 was like 3%, which is a huge uptick. And I feel like it was much, much higher than the anemic whatever it was, one and a half, 1.7% the last couple years. All this AI, all this automation is going to drive productivity. It's going to have an impact on organizations. So what's your perspective point of view on the pending productivity boom? Do you believe that premise? How are jobs going to be affected? What a client seeing in terms of how they're retraining people, what should we expect? Yeah, and I think AI is going to give people superpowers. It's going to make them better what they do. It's going to make you as a consumer better at how you choose what to buy. It's going to make the automobile drive more efficiently and more information that's relevant to you in the dashboard. It's going to allow, when you call for service on your cable company, for them to already know your history, maybe already diagnose why you're calling and make it a more efficient call. It's going to make everyone more productive. It's going to result in higher quality output because you're able to predict things, right? And you're able to automate things in intelligent ways. So I don't see it as anything that replaces jobs. It's just going to make people better at what they do and allow them to focus on higher value work and be more efficient when you are making decisions, right? And that will result in higher productivity per worker, right? I mean, we've certainly heard examples today of customers that are doing that basically. It's not like they're firing people. They're basically taking away mundane tasks or things that maybe humans would take so long to do and then pointing that talent somewhere else. To higher value. So you're seeing that in your client base. It's starting to hit today. It's going to be interesting to see whether or not that affects jobs. I mean, we'd like to say that's not, I ultimately think it's going to create more jobs. There may be some kind of dip where we've got to retrain people. Maybe we have to change the way in which we do reading, Beth Smith and I were talking about reading, writing, arithmetic and coding. Maybe one of the skills that we have to bring in. But ultimately, I think it is a positive and I'm sanguine and I'm an optimist. But you're seeing examples today of people refocusing their talent. What are they focusing that talent on? More strategic things like what? Well, again, I think it's just getting people to be better at what they do by giving them that predictive power, the superpowers, to be able to do their job better. So it's going to make people better, not replace them. So as consumers, we're probably going to buy more, right? You're going to buy more? You're going to buy the right things more? And the right things are going to be there for you to buy, the right sales, because everything is going to be able to better understand patterns of what happens and predict, right? And that's why you've seen this enormous investment shift among technologists at companies. What was it? MIT Sloan and the Boston Consulting Group just came out with a study, I think a couple of weeks ago, 92% of companies are looking to expand their investments in AI. Gardner came out with a study of CIOs and they're in top investment areas. Artificial intelligence was number one, data and analytics was number two, which is the information architecture, right? One and two, that's the first time it's been like that. And I think it's for this reason of digital transformation, the predictive enterprise, if you will, and just helping everyone be more efficient, more productive in what they do. That's really what it's about. Not so much replacing people. They're thinking of robots and things like that. That's a small part of what we're talking about here. Well, even when you talk to people about software robots, they love them because they don't have to do these mundane tasks and it dramatically impacts the quality of what they're doing. But again, it frees them up to do other things. Good example, LegalMation is one of our clients that we've been working with. And they do case law for business clients. And sometimes it can take weeks, if not a month, to prepare case law documents. They're able to do that in hours now because they have artificial intelligence. The background is doing a lot of the case law intelligence and finding the right data and the right case law and helping to populate those documents where they don't have to do all the research themselves. So what does that do for the lawyer? It makes them better what they do. They can shift to higher value work than just preparing the document. They can work on more cases. They can spend more time on the subtleties of the case. I mean, actually that's a good example of what we mean here. It's not replacing the lawyer. Well, I've seen a lot of examples of like this in legal fields, also auditing. I've talked to a number of us. You think you'll be able to cut the auditing bill. And the answer is actually no. Because the point you just made is they're shifting their activities to higher value. They might be charging more for activities that take less time. So. You know, customer services is another great example. There's just so many sub examples of that. But it used to be if you called, everyone's treated equal, right? And you get onto a call and then sometimes it's very rudimentary things. Sometimes there's got to be a way to prioritize what are the most critical calls, knowing that there's something already wrong and you know why they're calling. And if you can shift your human agents to focus on those and let AI help with the more rudimentary ones, you're making the clients happier but those people are doing higher value work. And we can go on forever and ever on just different examples across different industries and different businesses of how this is really helping people. And it all comes down to the three big words which is prediction, automation and optimization. And that's what AI is going to do. And with digital transformation, it just shifts the whole notion of using data for evidence-based decision-making and what's happened in the past and what's happening now to, I'm going to understand and shape the future. And you can do so many things with that. It's amazing when you think about it. I mean we've been at this computer industry 50, 60 plus years and you think everything's automated. It's not even close. All this technology has actually created so much more data, so much unstructured data. Actually so many more inefficient processes in a lot of ways that now machine intelligence is beginning to attack in a big way. You won't find a survey of businesses where AI is not a top aspiration. The trick is how do you turn the aspirations into outcomes? And that's what this ladder to AI is all about. It's a very prescriptive approach that we've learned from our clients on how to kind of take that journey to AI. And a lot of things we talk about on this conversation are the real key linchpins, right? You got to get the data right. You have to have the trust in the data that you're going to be using. You got to get the talent and be able to simplify and democratize how you build these models and deploy them. And then ultimately you got to get trust across your organization. That means the models have to have explainability, understand, you have to help people understand how it is recommending these things. And then they're going to buy into it and it's just going to make them better, right? It's a whole notion of superpowers. Yeah, get that down and then you can scale and that's really where the business impact is. Yeah, they all want to get there. Now the hard part is now we got to start doing it, right? It's kind of like the internet was 20 years ago. They know they want to do business transactions over the internet and do commerce, but it didn't happen like overnight. It wasn't magic, it took, it was a journey. I think we're seeing that movie we play in here. Yeah, and in fact, I think in some ways it could even happen faster now because you have the internet, because you have cloud. So I'm predicting a very steep O-Gyve S-Curve here. All right, we'll have to leave it there. Scott, great to see you. Thanks for coming on. Any time. All right, and keep it right there. We'll be back with our next guest. Right after this short break, you're watching theCUBE from the IBM Data and AI Forum in Miami. We'll be right back.