>>live from Miami, Florida It's the Q covering IBM is data in a I forum brought to you by IBM. >>Welcome back to Miami, Florida Everybody watching the Cube, the leader in live tech coverage. We go out to the events and extract the signal from the noise we're covering the IBM data and a I Forum Scott Hefner series The CMO on uh, sorry VP and CMO IBM Data. Yeah, right, I know. Here's the CMO of late again. So welcome. Welcome to the >>cake was great. Great >>event. Yeah, I've never attended one of these before. The sort of analytics University 1700 people that everybody's like. Sponges trying to learn more and more and more. >>60% higher attendance last year. Awesome. A lot of interest. >>So if we go back a couple of years ago, talks about digital transformation, people roll their eyes. They think it's a buzz word. When you talk to customers, it's really they're trying to transform their business, and data is at the center of that. So if you go back to like 2016 there's 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 their bets on things like Ai ai automation machine learning containers. What are you seeing from customers? >>I think you framed it Well, I mean, if you kind of think about it, this digital transformations been going on for almost 20 years. With the advent of the Internet back around 2000 late 19 nineties, every started on the Internet doing business transactions, and slowly but surely, digital transformation was taken effect, right? And I think clients are now shifting to what we can call digital transformation two point. Oh, what's the next 20 years look like? And our view, our viewpoint from overlay from our clients is, if you think about it, it's data that fuels digital transformation. Right? Without data, there is no digital transformation is no digital. 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, 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 in clients with digital transformation. To point out what a shift to a word of predictive data. How do you How do you predict in shape? Future outcomes, right? And if you think about it's a I that's gonna unlock predictive data. That's why we see such an intense focus on a I as a really the linchpin of digital transformation. Two point. Oh, 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 that unlocks the value or if a Iot of Mark's value the data and predictive ways the cloud in a multi cloud environment is that platform that has built upon, it's. That's why you see this enormous shift today. I in terms of investment priority along with hybrid multi cloud. >>So I like this this point of view, this digital transformation 2.0, because what's in their senior business in a digital business? That's how they used data. Yeah, and IBM is mission. Using your group is to help people better take advantage of data to five business outcomes. I mean, that's pretty clearly. What you guys are doing this to Dato To me. Three innovation cocktails, data plus machine intelligence or a I, and then you scale it with cloud. And so you talk about cloud to two point. Oh, really? Involves this predictive sort of a 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 our clients trying to achieve. One is to predict and shape future outcomes, whether it be inventory, whether it be patient care, whatever it may be. Ah, customer service call. You want Toby to predict what the call's gonna be about what the client or what the customers has gone through before with the issue may be right. So this notion of predicted in shaping the outcome the second is empowering. People do higher value work. How do you make them better at what they're doing? The superpowers of being aided by a machine all right, or some kind of software, it's gonna help you be better what you do. And of course, this whole notion of automating task that people don't want to do automated experiences and intelligent ways. This all adds up to like new business models, right? And that's where a I comes in. That's what I does, and I do think it's a linchpin. 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 service is data service is an aye aye. Service is 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 APS wherever you want to run them secure to the core, and that's what they're looking to invest in. And >>so you guys use is the sort of tag line you can't have a I without. Ay, ay, ay, ay, ay, being information architecture. So for years on the q b been talking about bringing the cloud model to your data? Could you don't move data around? Now you're talking about bringing machine intelligence to your data wherever your data lives, to talk about why that's important and what IBM is doing both conceptually in from a product standpoint, to enable that. >>So the number one issue with the eye and actually a number one issue that sometimes results in failure with a I is didn't understand the data. Some 81% of clients do not understand the data that they're gonna need for the aye aye models. And if they do understand the doubt that they don't know how to make it simple, inaccessible, especially when its ever changing and then they have all the issues of compliance and quality. And is it a trusted set of data that you're using? And that's what you mentioned about? There is no way I without an aye aye, which is information architecture. So it starts there than two. To your point is, Dad is everywhere. There's thousands of sources of data, if not more than that. So how do you normalize all that? Virtual eyes it right. And that's where you get into 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 a I to build. I use a I to actually manage the life cycle of how do you incorporate this into your business and That's what this one platform is gonna d'oh! Versus enabling customers to piece together all this stuff. It's just it's too much. >>So this is what cloudpack for data? Yeah, it is and does. Yes. So you say Aye, aye. Free. Are you talking about picking the functions and automating components? Prioritizing? Yeah. How you apply those those algorithms. Is that right? >>Yeah. So I think Way talk about data with three big things to really focus on his data. And that is the whole nursing. You need that information architecture that's that's ready for an aye aye multicolored world. It's all about the dad 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. I actually generate and build a I optimize eh? So they don't need is, you know, as much skill to do it. In other words, democratize the ability to build a I models for your business. And then finally, the dad is everywhere. You need to have completely open environment. That's the run on any cloud notion. And that's why the Red had open shift is such a big component of this. So think of clients are looking to climb the ladder >>today. I >>modernize their data states, make the data simple, inaccessible, create a trusted data foundation building scale new models and infuse it throughout their business. Cloudpack for data is essentially the foundational platform that gives you the latter >>day I >>that is in earnestly extensible with things that may be important to you or certain areas of additional capabilities. So Compaq for Dad essentially is the platform that I'm referring to hear when you say you know 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 now and if you believe the Bureau of Labor Statistics, but over the long term productivity numbers right, you probably can't believe in them. I think for Q one was like 3% which is a huge uptick. And I feel like it's much, much higher than the anemic whatever it was one and 1/2 1.7%. All this ay, ay, all this automation is gonna drive productivity. It's gonna have an impact on organizations. So what's your perspective? Point of view on on the depending productivity boom boom? Do you believe that premise, How our job's going to be affected, What a client seeing in terms of how their retraining people, What should we expect? >>Yeah, I think a I's gonna give people superpowers. It's gonna make them better. What they do, it's gonna make you as a consumer better at how you choose what to buy. It's gonna make the automobile drive more efficiently and more more information that's relevant to you in the dashboard. It's gonna allow you call for service on your cable company. For them to already know your history, maybe already died. Knows what why you're calling and make it a more efficient call. It's gonna make everyone more productive. It's gonna result in higher quality output because you're able to predict things right. You automate things and intelligent ways, so I don't see it as anything that replaces jobs. It's just gonna make people better at what they do. Allow them to focus on higher value work and be more efficient when you are making decisions right in that will that will result in higher productivity per per worker, right? >>I mean, we've certainly heard examples today of customers that are doing that basically, and 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 re pointing that talent somewhere else. >>Toe higher value. >>So you're seeing that in your client base? Yeah, it's starting to hit today. It's gonna be interesting to see whether or not that affects jobs. I mean, we like to say That's not I ultimately think it's gonna create more jobs. There may be some kind of dip where we've got to retrain people, maybe have to change the way in which we do. Reading right bet Smith and I were talking, reading, writing arithmetic in coding, You know, 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. Um, 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 of super powers to be a to do their job better. It's gonna make people better not replace >>them. So it's consumers. We're probably gonna buy more. You're >>gonna buy more, you're gonna buy the right things more. And the right things are gonna be there for you to buy the right sales because everything is gonna be able to better understand patterns of what happens and predict right. And that's why you're seeing this enormous investment shift among among technologists companies. What was that? M. I. T. Sloane in the Boston Consulting Group just came out with a study. I think couple weeks ago, 92% of companies are looking to expand their investments in a I gardener came out with the study of C i ose and there in top investment areas, artificial intelligence was number one. Data and analytics was number two, which is the information architecture, right? One into as the first time it's been like that. So and I think it's for this reason of digital transformation, the predictive notion predictive enterprise, if you will, and just helping everyone be more efficient, more productive or what they do. That's really what it's about. It's 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. >>Well, even when you talk to people about software robots, they love them because they don't have to do these Monday tests and dramatically impact the quality of what they're doing it again. It frees them up to do other things. >>Good, Good example. Legal Legal Nation 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 ours now because they have artificial intelligence. The background has done a lot of the case law, intelligence and finding the right dad in 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? Right? It makes them better what they do. They can shift a higher value work than just preparing the document. They could work on more cases that could spend more time on the subtleties of the case. Actually, that's a good example of what we mean here. He's not replacing the lawyer. >>Well, I'm seeing a lot of examples like this in legal fields. Also, auditing. I've talked enough. I've asked you think I'd be able to cut the auditing bill? And the answer is actually, No, because to the point you just made is they're shifting their activities to higher value. They might be charging Maur for activities that take less time. >>Customer service is is another great example. There's so many some examples of that. But it used to be. If you called, everyone treated equal right and you get onto a call. And then sometimes it's very rudimentary things. Sometimes there's gotta 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 let a I help with the more rudimentary ones you're making, the client's happier. But those people doing higher value work, we go on forever and ever on just different examples across different industries in different businesses, of how this is really helping people, and it all comes down to it. The three big words, which is prediction, automation and optimization. And that's what I was gonna do. And with digital transformation in just shift the whole the whole notion of using data for evidence based decision making what's happened in the past? What's happening now, too? I'm gonna I'm gonna understand its shape, the future. You could do so many things with that. >>It's amazing when you think about it. 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 on structured data. Actually, so many Maur 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 because, ah, a survey of businesses where a eyes not a top aspiration trick, is how do you turn the aspirations of the outcomes? And that's what this latter day eyes all about. It's a very prescriptive approach that we've learned from our clients on howto take that journey to a I and a lot of things we talk about on this on this conversation or the real key linchpins, right? You gotta get the data right. You have to trust in the data that you're going to be used and you gotta get the talent and be able to simple find democratize how you build his models and deploy them. And then ultimately you got to get trust across your organization. And that means the models have to have explained ability, Understand? You have to help you understand how it is recommending these things, and then they're gonna buy into it. It's just gonna make them better. It's the whole notion of superpowers. >>Get that down and then you could scale. And that's really where the business and >>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 playing here? >>Yeah. And in fact, I think in some ways it could even happen faster now because you have the Internet because you have clouds. That's not predicting a very steep Pogue. I've s curve here. We'll have to leave it there. Scott, great to see you. Thanks >>for coming >>on. >>Any time. >>All right. Keep it right, everybody. We'll be back with our next guest right after this short break. You're watching the Cube from the IBM data and a I form in Miami. We'll be right back.