>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR, this is "Breaking Analysis" with Dave Vellante. >> A decade of big data investments combined with cloud scale, the rise of much more cost effective processing power. And the introduction of advanced tooling has catapulted machine intelligence to the forefront of technology investments. No matter what job you have, your operation will be AI powered within five years and machines may actually even be doing your job. Artificial intelligence is being infused into applications, infrastructure, equipment, and virtually every aspect of our lives. AI is proving to be extremely helpful at things like controlling vehicles, speeding up medical diagnoses, processing language, advancing science, and generally raising the stakes on what it means to apply technology for business advantage. But business value realization has been a challenge for most organizations due to lack of skills, complexity of programming models, immature technology integration, sizable upfront investments, ethical concerns, and lack of business alignment. Mastering AI technology will not be a requirement for success in our view. However, figuring out how and where to apply AI to your business will be crucial. That means understanding the business case, picking the right technology partner, experimenting in bite-sized chunks, and quickly identifying winners to double down on from an investment standpoint. Hello and welcome to this week's Wiki-bond CUBE Insights powered by ETR. In this breaking analysis, we update you on the state of AI and what it means for the competition. And to do so, we invite into our studios Andy Thurai of Constellation Research. Andy covers AI deeply. He knows the players, he knows the pitfalls of AI investment, and he's a collaborator. Andy, great to have you on the program. Thanks for coming into our CUBE studios. >> Thanks for having me on. >> You're very welcome. Okay, let's set the table with a premise and a series of assertions we want to test with Andy. I'm going to lay 'em out. And then Andy, I'd love for you to comment. So, first of all, according to McKinsey, AI adoption has more than doubled since 2017, but only 10% of organizations report seeing significant ROI. That's a BCG and MIT study. And part of that challenge of AI is it requires data, is requires good data, data proficiency, which is not trivial, as you know. Firms that can master both data and AI, we believe are going to have a competitive advantage this decade. Hyperscalers, as we show you dominate AI and ML. We'll show you some data on that. And having said that, there's plenty of room for specialists. They need to partner with the cloud vendors for go to market productivity. And finally, organizations increasingly have to put data and AI at the center of their enterprises. And to do that, most are going to rely on vendor R&D to leverage AI and ML. In other words, Andy, they're going to buy it and apply it as opposed to build it. What are your thoughts on that setup and that premise? >> Yeah, I see that a lot happening in the field, right? So first of all, the only 10% of realizing a return on investment. That's so true because we talked about this earlier, the most companies are still in the innovation cycle. So they're trying to innovate and see what they can do to apply. A lot of these times when you look at the solutions, what they come up with or the models they create, the experimentation they do, most times they don't even have a good business case to solve, right? So they just experiment and then they figure it out, "Oh my God, this model is working. Can we do something to solve it?" So it's like you found a hammer and then you're trying to find the needle kind of thing, right? That never works. >> 'Cause it's cool or whatever it is. >> It is, right? So that's why, I always advise, when they come to me and ask me things like, "Hey, what's the right way to do it? What is the secret sauce?" And, we talked about this. The first thing I tell them is, "Find out what is the business case that's having the most amount of problems, that that can be solved using some of the AI use cases," right? Not all of them can be solved. Even after you experiment, do the whole nine yards, spend millions of dollars on that, right? And later on you make it efficient only by saving maybe $50,000 for the company or a $100,000 for the company, is it really even worth the experiment, right? So you got to start with the saying that, you know, where's the base for this happening? Where's the need? What's a business use case? It doesn't have to be about cost efficient and saving money in the existing processes. It could be a new thing. You want to bring in a new revenue stream, but figure out what is a business use case, how much money potentially I can make off of that. The same way that start-ups go after. Right? >> Yeah. Pretty straightforward. All right, let's take a look at where ML and AI fit relative to the other hot sectors of the ETR dataset. This XY graph shows net score spending velocity in the vertical axis and presence in the survey, they call it sector perversion for the October survey, the January survey's in the field. Then that squiggly line on ML/AI represents the progression. Since the January 21 survey, you can see the downward trajectory. And we position ML and AI relative to the other big four hot sectors or big three, including, ML/AI is four. Containers, cloud and RPA. These have consistently performed above that magic 40% red dotted line for most of the past two years. Anything above 40%, we think is highly elevated. And we've just included analytics and big data for context and relevant adjacentness, if you will. Now note that green arrow moving toward, you know, the 40% mark on ML/AI. I got a glimpse of the January survey, which is in the field. It's got more than a thousand responses already, and it's trending up for the current survey. So Andy, what do you make of this downward trajectory over the past seven quarters and the presumed uptick in the coming months? >> So one of the things you have to keep in mind is when the pandemic happened, it's about survival mode, right? So when somebody's in a survival mode, what happens, the luxury and the innovations get cut. That's what happens. And this is exactly what happened in the situation. So as you can see in the last seven quarters, which is almost dating back close to pandemic, everybody was trying to keep their operations alive, especially digital operations. How do I keep the lights on? That's the most important thing for them. So while the numbers spent on AI, ML is less overall, I still think the AI ML to spend to sort of like a employee experience or the IT ops, AI ops, ML ops, as we talked about, some of those areas actually went up. There are companies, we talked about it, Atlassian had a lot of platform issues till the amount of money people are spending on that is exorbitant and simply because they are offering the solution that was not available other way. So there are companies out there, you can take AoPS or incident management for that matter, right? A lot of companies have a digital insurance, they don't know how to properly manage it. How do you find an intern solve it immediately? That's all using AI ML and some of those areas actually growing unbelievable, the companies in that area. >> So this is a really good point. If you can you bring up that chart again, what Andy's saying is a lot of the companies in the ETR taxonomy that are doing things with AI might not necessarily show up in a granular fashion. And I think the other point I would make is, these are still highly elevated numbers. If you put on like storage and servers, they would read way, way down the list. And, look in the pandemic, we had to deal with work from home, we had to re-architect the network, we had to worry about security. So those are really good points that you made there. Let's, unpack this a little bit and look at the ML AI sector and the ETR data and specifically at the players and get Andy to comment on this. This chart here shows the same x y dimensions, and it just notes some of the players that are specifically have services and products that people spend money on, that CIOs and IT buyers can comment on. So the table insert shows how the companies are plotted, it's net score, and then the ends in the survey. And Andy, the hyperscalers are dominant, as you can see. You see Databricks there showing strong as a specialist, and then you got to pack a six or seven in there. And then Oracle and IBM, kind of the big whales of yester year are in the mix. And to your point, companies like Salesforce that you mentioned to me offline aren't in that mix, but they do a lot in AI. But what are your takeaways from that data? >> If you could put the slide back on please. I want to make quick comments on a couple of those. So the first one is, it's surprising other hyperscalers, right? As you and I talked about this earlier, AWS is more about logo blocks. We discussed that, right? >> Like what? Like a SageMaker as an example. >> We'll give you all the components what do you need. Whether it's MLOps component or whether it's, CodeWhisperer that we talked about, or a oral platform or data or data, whatever you want. They'll give you the blocks and then you'll build things on top of it, right? But Google took a different way. Matter of fact, if we did those numbers a few years ago, Google would've been number one because they did a lot of work with their acquisition of DeepMind and other things. They're way ahead of the pack when it comes to AI for longest time. Now, I think Microsoft's move of partnering and taking a huge competitor out would open the eyes is unbelievable. You saw that everybody is talking about chat GPI, right? And the open AI tool and ChatGPT rather. Remember as Warren Buffet is saying that, when my laundry lady comes and talk to me about stock market, it's heated up. So that's how it's heated up. Everybody's using ChatGPT. What that means is at the end of the day is they're creating, it's still in beta, keep in mind. It's not fully... >> Can you play with it a little bit? >> I have a little bit. >> I have, but it's good and it's not good. You know what I mean? >> Look, so at the end of the day, you take the massive text of all the available text in the world today, mass them all together. And then you ask a question, it's going to basically search through that and figure it out and answer that back. Yes, it's good. But again, as we discussed, if there's no business use case of what problem you're going to solve. This is building hype. But then eventually they'll figure out, for example, all your chats, online chats, could be aided by your AI chat bots, which is already there, which is not there at that level. This could build help that, right? Or the other thing we talked about is one of the areas where I'm more concerned about is that it is able to produce equal enough original text at the level that humans can produce, for example, ChatGPT or the equal enough, the large language transformer can help you write stories as of Shakespeare wrote it. Pretty close to it. It'll learn from that. So when it comes down to it, talk about creating messages, articles, blogs, especially during political seasons, not necessarily just in US, but anywhere for that matter. If people are able to produce at the emission speed and throw it at the consumers and confuse them, the elections can be won, the governments can be toppled. >> Because to your point about chatbots is chatbots have obviously, reduced the number of bodies that you need to support chat. But they haven't solved the problem of serving consumers. Most of the chat bots are conditioned response, which of the following best describes your problem? >> The current chatbot. >> Yeah. Hey, did we solve your problem? No. Is the answer. So that has some real potential. But if you could bring up that slide again, Ken, I mean you've got the hyperscalers that are dominant. You talked about Google and Microsoft is ubiquitous, they seem to be dominant in every ETR category. But then you have these other specialists. How do those guys compete? And maybe you could even, cite some of the guys that you know, how do they compete with the hyperscalers? What's the key there for like a C3 ai or some of the others that are on there? >> So I've spoken with at least two of the CEOs of the smaller companies that you have on the list. One of the things they're worried about is that if they continue to operate independently without being part of hyperscaler, either the hyperscalers will develop something to compete against them full scale, or they'll become irrelevant. Because at the end of the day, look, cloud is dominant. Not many companies are going to do like AI modeling and training and deployment the whole nine yards by independent by themselves. They're going to depend on one of the clouds, right? So if they're already going to be in the cloud, by taking them out to come to you, it's going to be extremely difficult issue to solve. So all these companies are going and saying, "You know what? We need to be in hyperscalers." For example, you could have looked at DataRobot recently, they made announcements, Google and AWS, and they are all over the place. So you need to go where the customers are. Right? >> All right, before we go on, I want to share some other data from ETR and why people adopt AI and get your feedback. So the data historically shows that feature breadth and technical capabilities were the main decision points for AI adoption, historically. What says to me that it's too much focus on technology. In your view, is that changing? Does it have to change? Will it change? >> Yes. Simple answer is yes. So here's the thing. The data you're speaking from is from previous years. >> Yes >> I can guarantee you, if you look at the latest data that's coming in now, those two will be a secondary and tertiary points. The number one would be about ROI. And how do I achieve? I've spent ton of money on all of my experiments. This is the same thing theme I'm seeing across when talking to everybody who's spending money on AI. I've spent so much money on it. When can I get it live in production? How much, how can I quickly get it? Because you know, the board is breathing down their neck. You already spend this much money. Show me something that's valuable. So the ROI is going to become, take it from me, I'm predicting this for 2023, that's going to become number one. >> Yeah, and if people focus on it, they'll figure it out. Okay. Let's take a look at some of the top players that won, some of the names we just looked at and double click on that and break down their spending profile. So the chart here shows the net score, how net score is calculated. So pay attention to the second set of bars that Databricks, who was pretty prominent on the previous chart. And we've annotated the colors. The lime green is, we're bringing the platform in new. The forest green is, we're going to spend 6% or more relative to last year. And the gray is flat spending. The pinkish is our spending's going to be down on AI and ML, 6% or worse. And the red is churn. So you don't want big red. You subtract the reds from the greens and you get net score, which is shown by those blue dots that you see there. So AWS has the highest net score and very little churn. I mean, single low single digit churn. But notably, you see Databricks and DataRobot are next in line within Microsoft and Google also, they've got very low churn. Andy, what are your thoughts on this data? >> So a couple of things that stands out to me. Most of them are in line with my conversation with customers. Couple of them stood out to me on how bad IBM Watson is doing. >> Yeah, bring that back up if you would. Let's take a look at that. IBM Watson is the far right and the red, that bright red is churning and again, you want low red here. Why do you think that is? >> Well, so look, IBM has been in the forefront of innovating things for many, many years now, right? And over the course of years we talked about this, they moved from a product innovation centric company into more of a services company. And over the years they were making, as at one point, you know that they were making about majority of that money from services. Now things have changed Arvind has taken over, he came from research. So he's doing a great job of trying to reinvent themselves as a company. But it's going to have a long way to catch up. IBM Watson, if you think about it, that played what, jeopardy and chess years ago, like 15 years ago? >> It was jaw dropping when you first saw it. And then they weren't able to commercialize that. >> Yeah. >> And you're making a good point. When Gerstner took over IBM at the time, John Akers wanted to split the company up. He wanted to have a database company, he wanted to have a storage company. Because that's where the industry trend was, Gerstner said no, he came from AMEX, right? He came from American Express. He said, "No, we're going to have a single throat to choke for the customer." They bought PWC for relatively short money. I think it was $15 billion, completely transformed and I would argue saved IBM. But the trade off was, it sort of took them out of product leadership. And so from Gerstner to Palmisano to Remedi, it was really a services led company. And I think Arvind is really bringing it back to a product company with strong consulting. I mean, that's one of the pillars. And so I think that's, they've got a strong story in data and AI. They just got to sort of bring it together and better. Bring that chart up one more time. I want to, the other point is Oracle, Oracle sort of has the dominant lock-in for mission critical database and they're sort of applying AI there. But to your point, they're really not an AI company in the sense that they're taking unstructured data and doing sort of new things. It's really about how to make Oracle better, right? >> Well, you got to remember, Oracle is about database for the structure data. So in yesterday's world, they were dominant database. But you know, if you are to start storing like videos and texts and audio and other things, and then start doing search of vector search and all that, Oracle is not necessarily the database company of choice. And they're strongest thing being apps and building AI into the apps? They are kind of surviving in that area. But again, I wouldn't name them as an AI company, right? But the other thing that that surprised me in that list, what you showed me is yes, AWS is number one. >> Bring that back up if you would, Ken. >> AWS is number one as you, it should be. But what what actually caught me by surprise is how DataRobot is holding, you know? I mean, look at that. The either net new addition and or expansion, DataRobot seem to be doing equally well, even better than Microsoft and Google. That surprises me. >> DataRobot's, and again, this is a function of spending momentum. So remember from the previous chart that Microsoft and Google, much, much larger than DataRobot. DataRobot more niche. But with spending velocity and has always had strong spending velocity, despite some of the recent challenges, organizational challenges. And then you see these other specialists, H2O.ai, Anaconda, dataiku, little bit of red showing there C3.ai. But these again, to stress are the sort of specialists other than obviously the hyperscalers. These are the specialists in AI. All right, so we hit the bigger names in the sector. Now let's take a look at the emerging technology companies. And one of the gems of the ETR dataset is the emerging technology survey. It's called ETS. They used to just do it like twice a year. It's now run four times a year. I just discovered it kind of mid-2022. And it's exclusively focused on private companies that are potential disruptors, they might be M&A candidates and if they've raised enough money, they could be acquirers of companies as well. So Databricks would be an example. They've made a number of investments in companies. SNEAK would be another good example. Companies that are private, but they're buyers, they hope to go IPO at some point in time. So this chart here, shows the emerging companies in the ML AI sector of the ETR dataset. So the dimensions of this are similar, they're net sentiment on the Y axis and mind share on the X axis. Basically, the ETS study measures awareness on the x axis and intent to do something with, evaluate or implement or not, on that vertical axis. So it's like net score on the vertical where negatives are subtracted from the positives. And again, mind share is vendor awareness. That's the horizontal axis. Now that inserted table shows net sentiment and the ends in the survey, which informs the position of the dots. And you'll notice we're plotting TensorFlow as well. We know that's not a company, but it's there for reference as open source tooling is an option for customers. And ETR sometimes like to show that as a reference point. Now we've also drawn a line for Databricks to show how relatively dominant they've become in the past 10 ETS surveys and sort of mind share going back to late 2018. And you can see a dozen or so other emerging tech vendors. So Andy, I want you to share your thoughts on these players, who were the ones to watch, name some names. We'll bring that data back up as you as you comment. >> So Databricks, as you said, remember we talked about how Oracle is not necessarily the database of the choice, you know? So Databricks is kind of trying to solve some of the issue for AI/ML workloads, right? And the problem is also there is no one company that could solve all of the problems. For example, if you look at the names in here, some of them are database names, some of them are platform names, some of them are like MLOps companies like, DataRobot (indistinct) and others. And some of them are like future based companies like, you know, the Techton and stuff. >> So it's a mix of those sub sectors? >> It's a mix of those companies. >> We'll talk to ETR about that. They'd be interested in your input on how to make this more granular and these sub-sectors. You got Hugging Face in here, >> Which is NLP, yeah. >> Okay. So your take, are these companies going to get acquired? Are they going to go IPO? Are they going to merge? >> Well, most of them going to get acquired. My prediction would be most of them will get acquired because look, at the end of the day, hyperscalers need these capabilities, right? So they're going to either create their own, AWS is very good at doing that. They have done a lot of those things. But the other ones, like for particularly Azure, they're going to look at it and saying that, "You know what, it's going to take time for me to build this. Why don't I just go and buy you?" Right? Or or even the smaller players like Oracle or IBM Cloud, this will exist. They might even take a look at them, right? So at the end of the day, a lot of these companies are going to get acquired or merged with others. >> Yeah. All right, let's wrap with some final thoughts. I'm going to make some comments Andy, and then ask you to dig in here. Look, despite the challenge of leveraging AI, you know, Ken, if you could bring up the next chart. We're not repeating, we're not predicting the AI winter of the 1990s. Machine intelligence. It's a superpower that's going to permeate every aspect of the technology industry. AI and data strategies have to be connected. Leveraging first party data is going to increase AI competitiveness and shorten time to value. Andy, I'd love your thoughts on that. I know you've got some thoughts on governance and AI ethics. You know, we talked about ChatGBT, Deepfakes, help us unpack all these trends. >> So there's so much information packed up there, right? The AI and data strategy, that's very, very, very important. If you don't have a proper data, people don't realize that AI is, your AI is the morals that you built on, it's predominantly based on the data what you have. It's not, AI cannot predict something that's going to happen without knowing what it is. It need to be trained, it need to understand what is it you're talking about. So 99% of the time you got to have a good data for you to train. So this where I mentioned to you, the problem is a lot of these companies can't afford to collect the real world data because it takes too long, it's too expensive. So a lot of these companies are trying to do the synthetic data way. It has its own set of issues because you can't use all... >> What's that synthetic data? Explain that. >> Synthetic data is basically not a real world data, but it's a created or simulated data equal and based on real data. It looks, feels, smells, taste like a real data, but it's not exactly real data, right? This is particularly useful in the financial and healthcare industry for world. So you don't have to, at the end of the day, if you have real data about your and my medical history data, if you redact it, you can still reverse this. It's fairly easy, right? >> Yeah, yeah. >> So by creating a synthetic data, there is no correlation between the real data and the synthetic data. >> So that's part of AI ethics and privacy and, okay. >> So the synthetic data, the issue with that is that when you're trying to commingle that with that, you can't create models based on just on synthetic data because synthetic data, as I said is artificial data. So basically you're creating artificial models, so you got to blend in properly that that blend is the problem. And you know how much of real data, how much of synthetic data you could use. You got to use judgment between efficiency cost and the time duration stuff. So that's one-- >> And risk >> And the risk involved with that. And the secondary issues which we talked about is that when you're creating, okay, you take a business use case, okay, you think about investing things, you build the whole thing out and you're trying to put it out into the market. Most companies that I talk to don't have a proper governance in place. They don't have ethics standards in place. They don't worry about the biases in data, they just go on trying to solve a business case >> It's wild west. >> 'Cause that's what they start. It's a wild west! And then at the end of the day when they are close to some legal litigation action or something or something else happens and that's when the Oh Shit! moments happens, right? And then they come in and say, "You know what, how do I fix this?" The governance, security and all of those things, ethics bias, data bias, de-biasing, none of them can be an afterthought. It got to start with the, from the get-go. So you got to start at the beginning saying that, "You know what, I'm going to do all of those AI programs, but before we get into this, we got to set some framework for doing all these things properly." Right? And then the-- >> Yeah. So let's go back to the key points. I want to bring up the cloud again. Because you got to get cloud right. Getting that right matters in AI to the points that you were making earlier. You can't just be out on an island and hyperscalers, they're going to obviously continue to do well. They get more and more data's going into the cloud and they have the native tools. To your point, in the case of AWS, Microsoft's obviously ubiquitous. Google's got great capabilities here. They've got integrated ecosystems partners that are going to continue to strengthen through the decade. What are your thoughts here? >> So a couple of things. One is the last mile ML or last mile AI that nobody's talking about. So that need to be attended to. There are lot of players in the market that coming up, when I talk about last mile, I'm talking about after you're done with the experimentation of the model, how fast and quickly and efficiently can you get it to production? So that's production being-- >> Compressing that time is going to put dollars in your pocket. >> Exactly. Right. >> So once, >> If you got it right. >> If you get it right, of course. So there are, there are a couple of issues with that. Once you figure out that model is working, that's perfect. People don't realize, the moment you decide that moment when the decision is made, it's like a new car. After you purchase the value decreases on a minute basis. Same thing with the models. Once the model is created, you need to be in production right away because it starts losing it value on a seconds minute basis. So issue number one, how fast can I get it over there? So your deployment, you are inferencing efficiently at the edge locations, your optimization, your security, all of this is at issue. But you know what is more important than that in the last mile? You keep the model up, you continue to work on, again, going back to the car analogy, at one point you got to figure out your car is costing more than to operate. So you got to get a new car, right? And that's the same thing with the models as well. If your model has reached a stage, it is actually a potential risk for your operation. To give you an idea, if Uber has a model, the first time when you get a car from going from point A to B cost you $60. If the model decayed the next time I might give you a $40 rate, I would take it definitely. But it's lost for the company. The business risk associated with operating on a bad model, you should realize it immediately, pull the model out, retrain it, redeploy it. That's is key. >> And that's got to be huge in security model recency and security to the extent that you can get real time is big. I mean you, you see Palo Alto, CrowdStrike, a lot of other security companies are injecting AI. Again, they won't show up in the ETR ML/AI taxonomy per se as a pure play. But ServiceNow is another company that you have have mentioned to me, offline. AI is just getting embedded everywhere. >> Yep. >> And then I'm glad you brought up, kind of real-time inferencing 'cause a lot of the modeling, if we can go back to the last point that we're going to make, a lot of the AI today is modeling done in the cloud. The last point we wanted to make here, I'd love to get your thoughts on this, is real-time AI inferencing for instance at the edge is going to become increasingly important for us. It's going to usher in new economics, new types of silicon, particularly arm-based. We've covered that a lot on "Breaking Analysis", new tooling, new companies and that could disrupt the sort of cloud model if new economics emerge. 'Cause cloud obviously very centralized, they're trying to decentralize it. But over the course of this decade we could see some real disruption there. Andy, give us your final thoughts on that. >> Yes and no. I mean at the end of the day, cloud is kind of centralized now, but a lot of this companies including, AWS is kind of trying to decentralize that by putting their own sub-centers and edge locations. >> Local zones, outposts. >> Yeah, exactly. Particularly the outpost concept. And if it can even become like a micro center and stuff, it won't go to the localized level of, I go to a single IOT level. But again, the cloud extends itself to that level. So if there is an opportunity need for it, the hyperscalers will figure out a way to fit that model. So I wouldn't too much worry about that, about deployment and where to have it and what to do with that. But you know, figure out the right business use case, get the right data, get the ethics and governance place and make sure they get it to production and make sure you pull the model out when it's not operating well. >> Excellent advice. Andy, I got to thank you for coming into the studio today, helping us with this "Breaking Analysis" segment. Outstanding collaboration and insights and input in today's episode. Hope we can do more. >> Thank you. Thanks for having me. I appreciate it. >> You're very welcome. All right. I want to thank Alex Marson who's on production and manages the podcast. Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and our newsletters. And Rob Hoof is our editor-in-chief over at Silicon Angle. He does some great editing for us. Thank you all. Remember all these episodes are available as podcast. Wherever you listen, all you got to do is search "Breaking Analysis" podcast. I publish each week on wikibon.com and silicon angle.com or you can email me at david.vellante@siliconangle.com to get in touch, or DM me at dvellante or comment on our LinkedIn posts. Please check out ETR.AI for the best survey data and the enterprise tech business, Constellation Research. Andy publishes there some awesome information on AI and data. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching everybody and we'll see you next time on "Breaking Analysis". (gentle closing tune plays)

from the silicon angle media office in Boston Massachusetts it's the queue now here's your host David on tape hi everybody Dave Volante here with Stu minumum we have some breaking analysis we're gonna break down the acquisition of IBM Red Hat by IBM was announced today that it closed Stu was originally announced in October a 34 billion dollar acquisition so not a surprise surprise that it closed a little bit earlier than people thought people would thinkin you know well into the second half closed in July they got through all the all the issues in Europe what does this mean in your view to the industry yeah so Dave we did a lot of analysis when the deal was announced absolutely the the cloud and the ripples of change that are happening because of cloud are the impetus for this and you know the the question we've been having for years Dave is you know how many companies can stay kind of independent in you know their swimlane to what they're doing or are we going to see more massive consolidations we're not that far off of the 67 billion dollar acquisition of Dell buying EMC to go heavily into the enterprise market and of course there are cloud implications what happened there and you know we're watching the growth of cloud what's happening in the developer world you know we've watched Red Hat for a long time and you know Red Hat has a nice position in the world and it carved themselves out a nice role into what has been emerging as hybrid and multi cloud and in my opinion that's you know the number one reason why arvind and the IBM team you know when to take that 20-year partnership and turn it into you know now just part of the IBM portfolio Arvind Krishna executive at IBM a longtime player there so the the the deal is so you talked about Dells acquisition we've talked a lot about the VMware model keeping the company separate and of course Red Hat is not going to be a separately traded public company it is going to be a distinct unit inside of IBM's cloud and cognitive software group as I understand it is that right so the question is will it be reported separately or is it going to be oh we're gonna throw everything into our cloud number yeah so Dave this is where all of us that have watched and known IBM you know for our entire careers because they've been around over a hundred years on ask what's going to happen so from a reporting structure Jim Whitehurst reports to Ginny from a Wall Street standpoint it sounds like it's gonna be just thrown into the cloud piece you know Dave isn't it that the the the standard practice today that you throw lots of stuff in there so we can't figure out what your cloud business really is I mean let's look at Oracle or even Microsoft and what they had you know Amazon's probably the only one that clearly differentiates you know this is revenue that we all understand is cloud and can you know touch and feel it so sure I IBM you know you've got all of the the piece that used to be soft layer it's now the IBM cloud piece there are lots of software pieces in that mix the cloud and cognitive is a big umbrella and you know Red Hat adds a few billion dollars worth of revenue into that stream so IBM's assumptions here juni talks a lot about chapter two chapter one was a lot of front-end systems that sort of the growth was everybody thought everything was going into the cloud that's really not the way it is 80% of the workloads are still on Prem and in Chapter two was all about you know connecting those to any cloud multi-cloud heard her words the IBM cloud or the Amazon Google or Microsoft cloud etc etc she made the statement that that we are the only hybrid multi-cloud open source company okay I guess that's true does it matter that they're the only hybrid multi-cloud open source company and are they yeah so I mean Dave anytime a vendor tries to paint themselves as the number one or you know leader in the space it's you know that's how they're defining it that's not how customers think of it customers you know don't think is much about whether it's multi cloud or hybrid cloud they're doing cloud and they're working with you know more than one supplier it is very rare that you find somebody I'm all-in and then you dig in oh yeah wait I'm using office 365 and Salesforce and oh wait there was that cool new thing that Google announced that somebody off on the sides doing so we understand that today it's a multi cloud world tomorrow to be a multi cloud we're absolutely open source is growing you know at great leaps and bounds Red Hat is you know the you know best example we've had of that that trend something I've been watching for the last 20 years and you know it is impressive to see it but you know even when you talk to customers of you know most customers are not you know flag-waving I must do everything open-source you know that they have a little bit more nuanced view of it sure lots of companies are participating in contributing to open source but you know I've yet to talk to too many companies that were like well when I'm making this decision you know this is absolutely what it is am i concerned about my overall costs and I'm concerned about transparency am i concerned about you know security and how fast I can get things resolved and by the way open-source can help with a lot of those things that's what they need to think about but look IBM you know had a longtime partnership with Red Hat Red Hat has a strong position in the marketplace but they're not the only ones there you know you mentioned VMware Dave VMware cross has a strong play across multi cloud environments you know we see Red Hat at all of the cloud shows you see yeah IBM at many of the cloud shows but you've got Cisco out there with their play it is still you know this this chapter - if you agree with Ginny's terminology we are relatively early in that but you know IBM I believe is strengthened in their positioning I don't think it radically changes the landscape just because you know Red Hat is still going to stay you know working with the Amazons and Microsoft and Google's and and and other players out there so it doesn't dramatically change the landscape it just consolidates two players that already worked closely let me ask a question so I mean was clearly positioning this as a cloud play you know generally and you know in a multi cloud specifically is this a cloud play okay um so I'll say yes but Dave so absolutely the future and where the growth for Red Hat and where IBM and for this thirty four billion dollars to be successful the tip of the spear is open shift and therefore you know how does that new cloud native multi cloud environment you know where do they play but at its core you know red heads still Linux Red Hat Enterprise Linux you know is it stills you know that is the primary driver of revenue and Linux isn't going away as a matter of fact Linux is growing Microsoft you know just revealed that there are more Linux workloads sitting in Azure than there are windows we already knew that there were you know strong Linux out there and Microsoft is embrace Linux we saw Satya Nadella at Red Hat summit and you know we've seen that proliferation of linux out there so linux is still you know growing in it where it's being used out there and in the cloud you know linux is what most people are using so the reason why I think this acquisition is interesting Jim Whitehurst today said publicly that it was a great deal that IBM was getting but then he couched he said of course it's a great deal for our shareholders too so and Ginni chimed in and said yes it was a fair deal okay fine 34 billion you know we'll see the reason why I think IBM likes this deal and IBM you know generally has been been good over in history with acquisitions you know clearly some mega acquisitions like PwC which was transformative me we have time to talk about that Cognos and some of the other software acquisitions done quite well not a hundred percent but the reason why I think IBM likes this deal is because it's a good cash flow deal so I think in many ways and they don't talk about this because it's not sexy marketing but iBM is a services company over 60% of the company's revenue comes from professional services IBM loves complexity because they can bring in services throw the big blue blanket around you and do a lot of integration work and the reason is that I think this is an interesting acquisition from from a financial standpoint and Ginny says this all the time this is not about cost synergies this is about revenue opportunities when you try to put everything in the cloud you always run into the back-end systems and her point is that those back-end systems need to be modernized how do you modernize those back-end systems openshift it's not trivial to do that you need services and so iBM has a large install base probably by my estimate you know certainly tens of billions of dollars of opportunity there to modernize back-end systems using Red Hat technology and that means that it's a front-loaded deal from a cash flow standpoint that they will find automatically revenue Cyn to plug in to IBM's captive install base what are your thoughts yeah Dave III think that your analysis is spot-on so RedHat has been one of these most consistent you know revenue companies out there you steadily when they went from a billion dollars to now they're right around three billion dollars they had the March to five billion dollars they had a couple of minor blips in their quarterly earnings but if you plug in that IBM services organization you really have the opportunity to supercharge this is not the opportunity is to have that that huge IBM services organization really helped you know grow those engagements do more openshift you know get more Linux help ansible you know really become the standard for you know automation in the modern workplace the challenge is that too many IBM people get involved because the the thing that everybody's a little worried about is IBM's done well with a lot of those acquisitions but they don't leave them stand alone even you know VMware for many years was a standalone company today VMware in Dell they're one company they're in lockstep from a management standpoint and they're working closely together what differentiates RedHat is you know iBM has groups that are much larger than RedHat that do some of the same things but RedHat with their open-source mission and and where they're driving things and the innovation they drive they move a little bit faster than IBM traditionally does so can will the Red Hat brand the Red Hat people and Red Hat still stay independent enough so that they can till you know hop on that next wave you know they they jumped early into kubernetes and that was the wave that really helped them drive for what they're doing the open shift you know even Dave you know Red Hat ahead bought core OS which was a smaller company moving even faster than Red Hat and while they've done a really good job of integrating those people absolutely from what I've heard it is slowed things down a little bit just because Red Hat compared to core OS was a much bigger company and of course IBM is a be a myth compared to Red Hat so will they throw these groups together and you know who will be making the decisions and can they you know maintain that that culture and that growth mindset well the point is structure we bring up VMware a lot as the model and of course when EMC bought VMware for paltry six hundred million six thirty five million dollars it folded it in and then spun it back out which was the right move certainly allowed the ecosystem to blossom I don't think IBM is gonna take that same approach blue wash is the term they'll probably blue wash that now cuz no Dave they said iBM has said they will not blue eyes there's no purple red stay separate absolutely there's concerns you know so to get those revenue synergies there's there's you're gonna have to plug into IBM systems and that requires some some work and IBM generally good at that so we'll see we'll keep our eyes on that it's but but I would predict that IBM is not going to do a VMware like well it's going to be some kind of hybrid Dave one of the other things is you talked about so Jim Whitehurst you know executive respective had him on the cube a lot he's reporting to Ginny you know the question is is this Ginny's last big move and who replaces her yeah let's talk about succession planning so a lot of a lot of rumors that Whitehurst is is next he's 52 years old I've said I don't I don't think they would do that but but let's talk about it first of all just you know Jim white her side sort of interviewed him the number of times but but you know I'm quite well you think even watch the job so you know I talked with Jim a little bit at red hat summit you know he kind of makes light of it he said you know knowing IBM the way we all know IBM IBM has always taken somebody from inside to do that he feels that he has a strong mission still to drive Red Hat he is super passionate about Red Hat he wrote a book book about the open source culture and is still driving that so I think from everything I see from him that's still the job that he loves and wants to do and you know it's a very different challenge to run IBM I'm not saying he would turn it down if that was the direction that it went if it went down to it but I did not see him angling and positioning like that would be where he wants to go well and of course you know Jim is from North Carolina he's got that kind of southern folksy demeanor you know comes across as the so the nicest guy in the room he's also the smartest guy in the room but oh we'll see we'll see what happens there I've said that I think Martin Schroder is going to be the next CEO of IBM Martin Schroder did three years of combat duty as the CFO in in what was a tough time for IBM to be a CFO they were going through those big transitions talking about you know they had to had to do the the SoftLayer acquisition they had to put together those strategic initiatives and so he's has he has CFO chops so he understands finance deeply he ran you know when IBM's big services business he's now responsible for IBM's revenue generation he's a spokesperson you know in many ways for the company he's like the prototypical choice he would not be surprising at all to see IBM plug him right in a little bit of history as you know still him a bit of a history historian of the industry have been around for a while John Akers back in the early 1990s when IBM's mainframe business was was tanking and the whole company was was tanking and it was at the risk of actually believe it or not running out of money they were gonna split up the company because the industry was breaking apart Intel and microprocessors Microsoft and software C gated disk drives you know Oracle and databases and to be more competitive from a product standpoint they were gonna split the company up into pieces Gerstner came in and said no way Gerson it was you know CEO of American Express said no that's not how customers want to buy he bought PwC for a song compared to what Carly Fiorina at HP a Carly Fiorina at HP wanted to pay I think 15 billion for it I want to say IBM paid five billion or maybe even less for PwC it completely transformed the company it transformed IBM into a services company and that's where what IBM is today they don't like when you say that but that's where the revenue was coming from what that did now and they also started to buy software companies IBM was restricted from getting into applications for years and years and years because of the DOJ because they owned the mainframe they had a monopoly while Microsoft and Intel changed all that IBM started to buy software companies and bought lots of them so they became a services company with a collection of software assets and the main mainframe and you know the power they have a storage business and you know Finance I'd be a global finance business etc etc so my my point is I'm not sure Jim Whitehurst would want to run that you know it's it's kind of messy now what you need run that is somebody who really understands finance knows how to turn the knobs and that's why I think you know Martin Schroeder is actually an excellent pick for that to keep the cash flow going to keep the dividend going to keep the stock buybacks going it's still in my view not a growth play I think there's certainly near-term growth that can be had by modernizing applications but I don't look at IBM as a growth company I look at IBM as a portfolio company that throws off a lot of cash and if and when the market stops rewarding growth and profit list growth a company like IBM will become more favorable to investors yeah and the question at the end of the day is after spending thirty four billion dollars for red hat does IBM help weather the storm of what is happening with the phenomenal growth of AWS the changes happening in Microsoft build more of a relationship than they've already had with Google and help position themselves for this next wave of IT there's IBM helped create a lot of the waves that you know happen in IT well the pure play cloud players are in it for the long game you know you know Amazon's philosophy is give tools to builders and allow them to disrupt the you know traditional old guard whether it's old guard technology companies or old guard industry players and you've seen the stat of how many Fortune 1000 companies or you know have gone out of business in the last 20 or 30 years or whatever it is that's going to continue and Amazon and and certainly Google and Microsoft want to support that disruption by providing cloud tooling and put the data in the hands of people that allows them to create new business models now that doesn't mean everybody's gonna throw up there mainframes it's it's not gonna happen it's certainly not gonna happen overnight and probably will never happen but I just don't see how IBM becomes a growth company in that scenario the growth is going to be continue to be with the cloud well but Dave we had seen IBM I'd say struggle a little bit when it comes to the the developers these days and the Red Hat acquisition is definitely going to be a boon to them in this space because Red Hat all about the developers that that's what you know that their customers are so you know that that's such a huge community that they've already tapped into so Ginny has said this hybrid multi-cloud is a chapter two with a trillion dollar opportunity so who else is going after that trillion dollar opportunity let's let's lay it out there who are the multi cloud players VMware obviously IBM Red Hat with open shift is in there Google with anthos Cisco is coming at it from a network perspective so they have coming at it from their position of strength even though you know you know they're relatively new entrants well ever everybody wants to be the new management layer in this multi cloud environment what VMware had done is had you know vCenter became you know the console for everyone as they were consolidating all of their silos and when I go to a multi cloud environment right where do I live you know Microsoft has a strong play there that's the other you know VMware IBM Red Hat anthos Google Mentos Cisco and Microsoft yeah and of course the one that while they won't say that they are multi cloud you can't talk about multi cloud without talking about Amazon because Amazon is a piece of everyone's cloud environment we were seeing what they're doing with outpost there so they are the kind of Spectre looming over this entire multi-cloud discuss yeah right on I think you got to put Amazon into that mix they will be an entrance into this multi cloud play and it's not gonna be a winner-take-all deal I could say cisco is coming at it from a position of networking strength Microsoft has its software estate and it's gonna do very well there IBM Red Hat coming at it from a standpoint of modernizing applications and there's a services could play and services component there and VMware of course coming at it from the the infrastructure operating system I don't see Oracle as interested in that market there may be some smaller players like turbo anomic you know who probably get gobbled up by one of these guys that we just mentioned but that really is the landscape and this is you know five six companies a trillion dollars there's plenty to go around all right Stu final thoughts on on the the Red Hat news the IBM news that they've finalized the Red Hat acquisition yes so you know what you want to look for is you know first of all you know what's happening organizationally you know if open shift is the primary you know the the tip of the sphere what we're talking about here for this you know cloud native multi-cloud world you know what does you know the IBM Cloud messaging looked like they're gonna have an analyst event here in a couple of weeks that you know that they've invited all the analysts to going into what does that cloud portfolio looks like how do they sort through all of the kubernetes options that they've had today do they try to elevate IBM cloud to be a stronger player or will they let Red Hat continue to play across all of the cloud environments that they have so you know organization and product positioning of the two things that I'm looking at the most Tom Siebel said publicly yesterday that IBM is a great company national international treasure but they miss cloud and they missed a I I wouldn't agree totally they didn't miss cloud they were late to cloud they had to buy software they're in cloud just like Oracle's in cloud not as competitive as the AWS cloud but they're they've got a cloud yeah HP doesn't have a cloud Dell doesn't have a cloud these these two companies that I just mentioned do AI yeah they're not sound of generalized AI like what Google and Amazon and Facebook and Microsoft are doing IBM's trying to solve you know big chewy problems iBM is a services company as they said so you know Watson you see a lot of negative stories about Watson but Watson requires a lot of services to make it work and it's as they say solving different problems so they're a player in AI multi cloud is new and this move the acquisition of red hat yes thirty four billion dollars expensive it's not gonna be pretty on the balance sheet but they get good cash flow so they'll deal with that over time it puts them right in the mix as a leader in multi cloud so thanks to for breaking down the the acquisition and thank you for watching this is Dave Volante what's do min and then we'll see you next time

>> Announcer: Live from Las Vegas, it's theCUBE, covering InterConnect 2017, brought to you by IBM. >> Welcome back to InterConnect 2017 in Las Vegas. We're here at the Mandalay Bay hotel. This place is packed. We're right by the escalators, jamming all day, roughly 20,000 people here. Mohammed Farooq is with me. He's the GM of the cloud brokerage services under the GTS division of IBM. Mohammed, thanks very much for coming on theCUBE. >> Thank you very much, I appreciate for having me here. >> You're welcome. We were talking, having a great conversation off camera about your history, coming over from India, getting an education in Oklahoma, doing startups, selling companies and ultimately ending up at IBM. Let's start where you are today. Your role as GM of brokerage, cloud brokerage services. What does that entail? What does that mean, cloud brokerage services? >> Two things here, right? My role at IBM is one part of the question and what is cloud brokerage is the second part. I'll start with cloud brokerage. Cloud brokerage is the concept that has emerged in the last five years where as cloud services became one of the choices for consuming IT, the role of enterprise IT had to change from being a manager of technology to brokering what services businesses use either from internal IT or from external cloud providers. The CIOs and ITO organization had to take on the role of a broker. To play, effectively to play the role of IT broker, you need to really change the current IT model, which is people process technology. That had to be automated into a new platform that gave birth to the new requirement that you need a broker via technology in a platform where you can connect demand to supply. Demand can come from any business unit, either for infrastructure or applications or managed services, and you can connect it to the right supplier, just like manufacturing, just in time. The CIO would optimize the demand and supply and make sure the right services are available to be pulled at the right time for the right user. This is what Amazon has done. This is was Azure is doing. This is what SoftLayer has done. Give access to IT services on demand. But can you aggregate that and provide a standard consumption operating model for the enterprise? That is the new broker role and the broker's platform from IBM basically enables that role for the enterprise. >> Is that software? Is that an abstraction layer, a manger of managers, or is it people in process? >> It is both. It is an abstraction layer that connects to all cloud providers, internal or external. It has automated new processors for consumption, service management and governance, and it creates new roles in the enterprise for IT organizations and business users. It's a complete rethink of how IT operates, but importantly, it connects to the current processors. That's where you can run hybrid IT. You can connect to service now, to the current i2 processors in the enterprise. You can connect to the current governance dashboards and you can connect to the current data centers. We do have current applications on. It connects to the current and it connects to the new world of automated self-service and brings it together. >> So, you go back 20, 25 years, this business that you're in now was a break-fix business. It's totally transformed. Talk about the CIO. What's on his or her mind today? What should they be focused on? >> I think the CIO's role changes every two to three years. The areas of focus changes. Previously, they were in the business of building applications and managing it and managing the infrastructure. Then the packaged applications came, SAP Oracle. Then they were in the business of implementing. Then they started building web applications again for awhile and managing it. Now we have SAS, software as a service, so you can just rent an application. You have a pass. You don't have to build a bigger web. You can rent it. You have infrastructure, you can rent it. Excuse me. The CIO's role now, the CIO's role now is how do I govern it? That's the priority. I don't have to go build it. I need to govern what I have, but effectively. Second, I need to provide access to services that my business needs, and I need to do that at speed. Third, I need to be able to manage it security wise, compliance wise, whether the data is staying in the right places. It's not being exposed because data breach is a big issue. My infrastructure doesn't have holes for security. It can scale. So the concerns of the CIO are now different. The risks are different and that's a new role the broker is taking on. The most important role for the CIO right now is give me visibility into where my stuff is. It's in Amazon, Azure, SoftLayer. I've lost control of it. Tell me where it is and it's very complex, simplify this for me. >> It's interesting to hear you, Mohammed, talk about the CIO used to develop apps and then commercial, off-the-shelf applications came and then the web apps, they started developing apps again, et cetera, that progression. Now there's SAS. I wonder if I can get your comment on this. The other sort of trend that we see, we talk about it all the time, is that the, the companies talk about digital transformation all the time, part of that digital transformation is becoming SAS companies. Every company's becoming a SAS company. What's the role of a CIO in this new-- I think Benioff said it. There'll be more SAS companies for non-tech companies than tech companies. What's the role of a CIO in that world? >> If you look at it, the differentiation that a corporation has today is the digital experiences it requires either on the supply chain side or it's customers. Those applications are custom SAS applications that they're building. The CIO's role is to make sure it becomes the operator of SAS apps. Right? >> Interviewer: Whether internal-- >> Internal or external. So if his business units develop custom SAS apps, either mobile apps or social media apps or analytics apps, those apps should be available and running and scalable in the cloud 24 seven. Basically, he becomes a SAS operator. When you're a SAS operator, you're also a governor. Industry is calling it hybrid cloud, many clouds, multi-clouds and the role of the CIO is to operate them and make sure they're governed. Third, that it's business get access to the right services at the right time because that time is very critical. The connected stakes of an operator and governor is real-time access to services, continuous innovation and speed, and control. >> This is a huge skilling issue for CIOs. Is it not? The skills transformation, you're going from provisioning LUNs to being a cloud broker. How's that going for your clients and how are you helping? >> That's where IBM comes in. IBM is saying for us to play a role in a digital world we have to change the way our relationship work with our customers. So if the CIO is becoming a broker, then what is my relationship with a cloud broker in the enterprise? As adoption is stating now, in the beginning, there's no skillset in the enterprise to operate this model. IBM has developed the technology and the skills and telling the CIO we can build this and operate it for you. And when you are assured, we can transfer this to you. It's a build, operate, transform relationship that we are building so that the CIOs in Fortune 500 can strategically partner with IBM and take this journey together. The role of a broker will be different in every enterprise, customized to that enterprise based on it's priorities. IBM is basically redefining the experience and the relationship to it's customers. In turn, we are enabling our customers to transform faster, develop value to it's business faster and become digital faster. >> Let's talk about IBM's business GTS specifically. I said off camera and I'll say it again, many people may not realize 60% of IBM's business is still services, combined GTS and the consulting services, about 30% is software, but only about 10% is hardware these days, including the operating systems. It's quite a transformation that Ginni has effected. I certainly remember the days of John Akers when IBM was splitting apart and trying to focus on different parts of the industry and Gertsner said no, single point of contact for the customer, we will become a global service provider, very successful strategy. Now we're entering this cognitive age. What's the strategy, specifically with regard to GTS? Are you trying to codify that deep expertise and put into software, like that abstraction layer we talked about? It is sort of a hybrid model? I wonder if you could summarize. >> Two things. What was true when Lou Gertsner said we want to provide a single point of contact and we're going to put this together, that was systems integration business. We will take all the piece parts for the customer and we will take the responsibility to deliver it reliably and make sure it's available and it's performing. The large corporations will depend on us to run their enterprise IT systems. Fast forward 2017, we are now a service integration business. We are integrating services from cloud providers, either internal or external. We're still playing the same role. We are the single point of consumption and integration and delivery for the new supply chain. The supply chain now is 100 times more fragmented than it was before. >> Interviewer: It's way more complex. >> It's more complex. >> Yeah, this is a huge opportunity. >> This is the biggest opportunity, again, for IBM and we are practically going after that opportunity. Hey, our role is the same. We are the single point of consumption and delivery and governance for our service integration and service delivery. That's how IBM is defining it's role, again, in the services era from a systems era. Second, how does it impact our revenue? We have a massive opportunity, every dollar spent on cloud services, customers have to spend money on managing it, integrating it, operating it and enhancing it. We are building offerings that provide value on top of the cloud providers in all these areas and we manage it. We see significant revenue opportunities. The way you distributed the revenue structure of IBM, we see a 10x opportunity for us doing that. >> Well, so there was a while where people thought that, that to the extent that you could automate, it would eat into the services business. That's not happening you're saying. >> Right, so two things are happening, right? That is happening, but we see a tremendous opportunity there for IBM because IBM has invested significantly in automation and big data software and cognitive. Basically, what we're saying is, yes our core business is getting commoditized, our basic business, but we are adding higher value at your services in software. We are becoming a software plus services business, practically. From a software side, on GTS, we will drive higher margin revenues and differentiation in higher value added services that are digital. We'll complement that with our services business that can scale at volume. In effect, we are creating a hybrid business model for the software plus services era for IBM. >> You're becoming a software company like everybody else. >> Mohammed: Yes. >> Right? >> Right. And IBM has, IBM has seen it and IBM has responded to it. IBM is invested in it, so we are building the ideas of service platform. We have invested in it. We're delivering to the market. We are re-skilling our workforce and we are creating a superior method of delivery for the cognitive era using a cognitive technology services delivery platform. >> You actually have a, as a service component of software in your PNL, is that right? >> Mohammed: Exactly. >> And that's the growing part of your business? >> Mohammed: We're tracking that line item as software as a service. >> We have to break, but I just want to spend a minute on your personal story. You came from India. You were highly educated, both in India and in this country, and now you're a senior executive at IBM. Quick story about your journey 'cause I love it. >> My journey started in India. I was always fascinated with technology in the United States because when I grew up, the United States was the country that put the man on the moon. We always looked at, I always looked at the United States as, as the pioneer in technology and I wanted to see how I could learn from it. How could I professionally grow from it? I did not know how, but a life is a journey. It got me to Oklahoma on a scholarship from a Master's program in operations research and computer science and then an MBA in finance. I move to Austin looking for a job, from Oklahoma. I worked for the government, the governor's office for a while, almost three years and then in the dotcom wave, I wanted to be in giving birth to new technology. I joined a startup in Austin that got acquired by Commerce One. From there, the journey took me to working with SAP, to building their middleware platform and then brought me back to Austin as a CTO for Texas again where I worked very closely with IBM for managing the state's data centers and building the software platform using the soul from our client and the software portfolio from IBM. What I realized during that time is really, the nature of IT services, consumption and delivery will change with cloud and it needs a new operating model of CIOs and CTOs. I created a company by CIOs for CIOs of how they would operate in a new utility model of it's combined cutbacks and outbacks and it's unified consumption across a very diverse supply chain. >> This is 2007 timeframe, right? >> Mohammed: 2007 timeframe. >> Just before the downturn. Perfect timing. >> Right, so leverage the tailwinds of cloud to build an operating model for hybrid, which is not being called hybrid, but was really a consumption centric model and a supply chain model from manufacturing that I learned at Commerce One and SAP. I said the supply chain concepts are very true for IT now because every unit within the supply chain is a service. >> The vision was to transform IT consumption. >> To transform IT consumption, delivery and governance in the enterprise. That led to Gravitant and the brokerage platform that IBM acquired in 2015. Currently my role at IBM is to drive this transformation into the enterprise and in turn, transform the delivery model for GTS. >> Well that's where we started. We'll have to leave it there, Mohammed. Thanks very much for coming on theCUBE and sharing your story. >> Mohammed: Thanks very much. It's a pleasure to meet you today. >> Okay, keep it right there, buddy. We'll be back with our next guest right after this short break. It's theCUBE. We're live from InterConnect.