 Welcome back, everyone, to theCUBE's live coverage here in Las Vegas. I'm John Furrier, host of theCUBE with Dave Vellante, my co-host, head of CUBE Research. We are here for SAS Innovate 2024. Next guest, CUBE alumni, Jay Uptchurch, CIO at SAS. Distinguished guest, Jay, great to see you. Thanks for coming back. Thank you. It's great to be back. It's been a while. We were here last couple of months ago and then saw each other at the SAS Pro-AM, SAS Championship. A lot's changed. The statements that were made at the last event six months ago was, we're going to do this. Right. And it's happening. So you're starting to see great proof points. You're starting to see the flowers bloom. Really good job. Congratulations to the team. A lot of stuff going on. But there's really, there's a lot going on. There's IT departments transforming. What's your view of what's happening in AI right now? You're seeing a lot of it because obviously you got to get the infrastructure done right. Right. A lot of stuff going on in the middle layer and then obviously the applications are changing radically. Yeah. Couple things. I think you're exactly right. Last year we made a lot of commitments about things where we thought things were going to go. Fast forward to where we are now. Amazing announcements today on new product innovations, trying to propel the industry forward right with our technology and the adoption of data and analytics and especially on the GNAI front has been outstanding. We saw it in our cloud numbers, our results, our financial results is coming last year as well. And then of course that brings all the technology delivery challenges to CIOs around the world. And that's really where I sit. So from what I see both in terms of internal operations for SaaS and then also for our customers who have been running our SaaS managed cloud offer. I mean transforming operations and leadership opportunities with AI has been big. What's been the big operational focus in terms of where people are seeing instant value that they're putting the stake down or getting some beach head on? Could you share any thoughts you see there? Well on the generative front, it's not instant value unfortunately. It's really been a lot more of, I'll say instant science experiments. So everybody's got an idea. I've got, I saw this amazing generative AI capability. It was marketed to me more as a consumer than as an enterprise but then they bring it back to the enterprise. They're like, hey, I think I could do this how? And that's created this concept that I keep calling just shadow AI situation where CIOs are finding out that businesses, our business partners are creating all these different science experiments with generative AI technology unbeknownst to the CIO. So I mean, since without some of the IT guardrails or the security guardrails that are required to make sure that we're doing it safe and effectively. So how, I mean, I'm sure it's acute but I think about the loop days, the big data days where shadow big data was rampant and people realized, oh, wait a minute. We got to rain it in. We got to rain it in. Whereas today at least there seems to be between the chat GPT awakening and raining it in, there seems to be a lot more focus on governance and legal and compliance edicts. Or would you liken it more to the big data days? I think last year it was more like the big data days. I think there was a lot of public opinion about what the governing rules should be and there were a lot of governing bodies coming together to meet to talk about it but there wasn't a lot of structure yet. And what happened was the excitement of the innovation hit the street first and so what we saw were business partners who said, well, I have an idea. I think I can streamline my operations with this artificial intelligence concept and so if you didn't have a good tight relationship with your IT partner, you probably went off and did it on your own. Remember, businesses are used to being able to do it on your own. Software as a service, the ability to do it without a lot of oversight is there. The problem with shadow AI is that the risks are higher. Suddenly proprietary data, confidential data, unintentionally leaving your premises going out to an open language model. Next thing you know, you've got leakage and that's a very big problem for our customers. So how do you handle something like this? True example, the developer happens to like chatGPT, whatever reason, pays for it and uses it to help write code but that's not allowed at the company. If I eat it, you can't use that and so the security group comes down and says, hey, you can't do that, no more. Developers says, oh, okay, sorry. What does he do? Goes to his phone. Does it there? Right, and writes his Python script there. How do you handle something like that? Well, I think first of all, putting up Garrelle's and saying you can't do it is probably not realistic. I mean, I think, for that very reason, at SAS, we have the luxury of having a very enlightened workforce because this is the world we live in, right, in data and analytics as it is. So that part of it is easier from an education. People understand the risks a little easier. So we definitely put up our acceptable use policies. We put in some Garrelle's around watching data flow in and out to make sure that there's not things going to places that it shouldn't and we trust our employees. We want to actually harness the creativity that our employees have as opposed to coming in and just putting up a big firewall, says no, you just can't do it. Now, I do have some customers, especially in sensitive areas like defense and others, that are like, yeah, I just don't even have that as an option. I've got to keep everything inside of that tight bubble. Lock it down. And in those cases, that's tough. Now they're trying to figure out, well, how do I engineer that in-house? And that gets really, really expensive. So we try to embrace our partners where they are as a business. I think our relationship manager model, so we take our best consultants in IT and we go out to our divisional partners. We want to understand what are you looking for? How can you help? How can we shape the demand through IT to come back to something that's usable? So that way we're not a barrier, right? For adoption now instead, we're actually accelerating the use of AI, especially in the generative space for our partners. So years ago, I learned from many CIOs because I'm always talking about technology. What about this? What about GNAI? What are the pluses and minuses? I want to know about that. But years ago, I was educated that, look, it's people process, okay, that's the most important thing. Technology's going to come, technology's going to go. That's, it's change management. We got to get that right. And then we'll always figure out the technology. Degree with that, how do you see GNAI in that wave? I totally agree with it. Somebody asks all the time, like, hey, what's your AI strategy? What's your GNAI strategy? What's your data strategy? All of that stuff, those are techniques and tools to realize your business strategy. If you don't start with that end in mind, I'm creating technology and solutions without a problem. And then I have something and I'm shopping it around for to find the problem. That's not going to keep me in my job very long, right? Because we're all underneath certain financial pressures, of course, as a CIO. So I think 100% change management in terms of making sure people understand the destination you're going to, how you're going to get there, let the technology come and fuel you along the way, but it definitely starts with people in process. Jay, I got to ask you, on my question as to, Pivot off Dave says, what do you think about the scenario where, again, we're seeing this on theCUBE as we go out to other events. The common theme is with AI successes, and you guys have someone on the stage here today, but in this case, the question is this, you see an end-to-end workflows being identified pre-Generative AI. So people have apps, financial apps, they have mobile apps, so companies have big workloads already, like they built, okay, cool. Now, Generative AI comes in, rather than reconstructing the house, they just retro it, so remodeling. That's like what I call the remodeling. So here I got a workload, very well-defined, end-to-end, serves a purpose, but all of a sudden, Generative AI comes in, so it's going to change the data modeling, the governance, user experience, so we know I could get that advantage. That's well-formed, that's scoped. You can look at that as an IT guy and say, hey, I can scope that against cost on GPU, compute, depends, are we reasoning? So as you get into the Generative AI, the problem statement is retrofit the workflow that you already have for GNAI. That's a retrofit. Is that, do you see that and is that real? I mean, that seems like what people are doing, but then how do you execute that? That's a complete redesign of a pre-existing workload. And does it really make you that much better at the end? Is the juice worth the squeeze in that case? Well, that would be an executive decision, right? And from a GNAI standpoint, where you plug it in for fit for purpose of what the generative, the creative answer is. So as an example, what you heard earlier today, right? The quantitative answer versus the creative answer. So in that end-in workflow, where are you looking for creativity versus where are you looking for a quantitative decisive answer? So your point is, rightfully so, is you got to know what the juice is and what the squeeze is. Absolutely. And so that's going to be on IT and leadership, right? That's right. Together and then go. That's exactly right. And I think what's interesting too about this whole movement is the role of the CIO having changed so fundamentally because of digital delivery of solutions and services. Now you bring in a GNAI and you're thinking about what's the end game, right? From a financial commercial perspective, or it could end up being an expense management model. How does GNAI plug in? Is it worth it in the end? Because GNAI is not cheap, right? I mean, you've heard it from the hyperscalers. I mean, they're running out. We're burning up CPUs, we're burning up energy, trying to get through all the compute, right? So yeah, absolutely fit for purpose. I want to ask, I don't want to ask about SAS and your budget specifically, but I want to ask about... But he's going to ask, okay. But he's going to ask. No, I won't, unless you want to share. But broadly amongst your colleagues, your CIO colleagues, I'll tell you what we're seeing in the data and I wonder what you're seeing. At the macro, we're actually seeing sort of an inverse proportionality to the two-year treasury. In other words, when the Fed tightens, IT budgets tighten, right? And when they signal they're going to loosen, seems like IT budgets get looser. Right now, they're getting a little tighter because of that signal. So that's at the macro level. 40% of the customers we talk to, say they're stealing from other budgets to fund GNAI, the ROI timelines, when we first started doing this survey, were inside of four months to get return on your GNAI projects. They're now shifting, we talk about shift left. ROI timelines are shifting right because people are getting smart. They're like, why should they sign up for all this? And then the use cases that we see today are very chat GPT-like documents, summarizations. Agents. So that's broadly what we're seeing in the data. Can you share what you're seeing amongst your colleagues? Well, do you agree with that? And then what do you think? Yeah, I think, I do, I do. I think that there was early adoption for workforce productivity, definitely for coding. And so if you're looking for a quicker return on your investment, those are probably two use cases or categories that are a little easier to catch up on early. The aspirational that become a little bit longer, those are the ones that I think you can get into a case of, I'm spending a little more and I'm waiting longer to get the return on. And that gets CIOs in precarious positions really quick with their board, if you're not careful. I do think as a budget, it's interesting. I think IT budgets were originally under a lot of pressure in 20, 21, right? And then as we kind of came out of that, everybody wanted to go digital. There wasn't as much of a constraint on digital investments. Then it started to contract a little bit. Everybody wanted their dividends back from all those digital investments. And now we're kind of back on this hype cycle of GNAI and all of a sudden the budgets are starting to grow again. The idea of I'm stealing from different budgets is very real because at the end of the day we all came into our financial years thinking, okay, I know how I'm going to spread it out. And now all of a sudden, hey, wait, I need more for GNAI. So I'm going to steal a little bit from this group and maybe a little bit more for this group. Because that GNAI project actually will help them in the long run. That's the premise. So you might steal from productivity apps maybe because GNAI can maybe help that. Maybe legacy productivity apps or collaboration. Or actually other divisional budgets. That's what I've heard, too. On IT because at the end of the day, if that GNAI actually helps produce productivity gains for those other organizations, they'll fund that IT organization just a little bit more. Okay, so actually stealing is the wrong word. It's being funded from non-IT budgets. I'm going to use that the next time one of my partners challenges me on stealing their budget. That's the right way to use that. Police plot our entry for it. The struggle there is very real, right? The investments in AI and GNAI and how to keep up with it, especially if that return on investment period is longer than what your CFO is comfortable with, you got to do a very careful negotiation internally. You got to be able to tell the story of where you're going to get to with it to justify it and you got to get the buy-in from the business. And that's where back on that relationship manager role is so important. If I don't have credibility in the IT services that I'm delivering to that division, they're not going to want to help me. And the data is so clear. I mean, during the pandemic, it was cloud, RPA, AI and containers. We're all way up there in terms of spending momentum. And then just one month prior to ChatGPT, you could see AI doing this. And then once ChatGPT hit, AI's doing this, everything else kind of came down in the data. It was very clear. The other thing too we learned at the multiple events we've been through this year and recently validated at Google Next last week was that the IT workforce has been busy, not overfunded. And then digital transformation, seat at the table has been going on for years. And now the boards are saying to that table, where's our growth from Gen of AI? What's your Gen of AI strategy? That person comes down to the organization and there's a huge gap between where people need to be leveled up. So there's a huge like issue around, okay, now how do we execute? So, okay, take the scenario. Jay, where's the growth? What's your Gen AI strategy? Okay, boss, I'm on it. Okay, then you go back to your team. What's our Gen AI strategy? What is that like? Take us through that narrative of what happens next. Is that the aggregation of successful shadow AI? Or, hey, thank God we ran some shadow AI because now I have to have a growth strategy. Take us through the mindset and what happens in that progression. Yeah, I mean, I think internally there's always a lot of ideas around how you can use Gen AI. So you can definitely harvest that from the collective workforce and come back with a story if you need to. Is there real shadow deployments behind that sometimes? And then you've got to kind of rain those in a little bit. I think the idea of growth tied to Gen AI inside of corporate IT is really tough. It's much more of an idea of can you do more with less? It's a productivity gain model more than anything else. It does give you a chance like digital transformation to re-engineer some of those key processes that you referred to before. That's an interesting return. But again, your board sometimes isn't really looking for that. They're looking for where the commercial gains from it. But yeah, are you materially changing your expense profile or are you really materially growing revenue? I think on the Gen AI front for some of our corporate announcements today, that absolutely is a revenue game, right? Because we're going to create more productivity in our developments, right? And so that's where we're driving most of our business. You're actually doing both. You're actually reducing the expense profile and driving revenue. That's right. That's the holy grail right there. So most companies I see are hitting singles right now with Gen AI. But the interesting conversation here around industry specific AI is notable to me because there's some really complex use cases that ain't going to be four month ROIs. They might be four, five, six year ROIs or maybe more drug discovery and things of that nature. Maybe transformation and fintech is- But they're building AI. They're not using AI. Drug discovery will be a builder of their own AI system. Yeah, but so, right, okay. Someone who's using AI might get a faster payback. Yeah, yeah. Not if they're going to solve cancer. That's what I'm talking about. Really big, complex problems. And I'm wondering what you're seeing amongst your colleagues in industry. I think that dynamic between a creative answer and a quantitative answer is very real in terms of delivering an enterprise result. This idea of we're going to take a governance model to the creative answer that it can return is very positive. I think right now being received by our CIO forums and explaining how SaaS is augmenting that GNA AI capability to create real enterprise business decisions and results. I think that will actually condense down that ROI period from just the science experiments and the creative experiences that are going on right now with primarily all the gender of AI. Jay, it's been great to see you. I know we got a hard stop. We got to get in and see the chicken, the hot wings competition. It's going to be fun. So, final question. Next year when we're sitting here talking, what's going to be the conversation? I think it's going to be continued growth of cloud from SaaS, because that's been a fantastic story now for us for many years. Our customers are enjoying the consumption of our innovation through software as a service and or hosted managed services. So I'm incredibly pleased with that continued growth. I think that enables them to continue to adopt that innovation. The announcements you saw this morning, the more they're going to come throughout the next 24 to 48 hours, we'll continue to be front and center and we want to make sure we're delivering that to them. I think the GNI I front is very real. I think the market is hungry for enterprise examples of GNI delivering real results. I think SaaS is well poised to do that. And I hope next year when we're on stage, we're giving you examples of that. Well, you had one great one on stage, great stack with the customer this morning. So great job. And that will potentially open up, maybe not the floodgates, but that's a gain sharing model. I want you to start throwing off some cash. Oh, absolutely. And that's going to see, it's because you got big GNI backlogs right now. Yeah, that's right. You guys did a great job from the last event, your shipping production workloads with customers, monetizing 30% growth in the product line and more coming. 30% growth in Vine, 30% growth in SaaS Cloud and then on the industry solutions up as well. So very, very proud of the performance, very proud of the innovation that we dropped today too. So I think kudos to the R&D organization and we're looking forward to the market reception. Yeah, the models is the first company to kind of do that in that level. Congratulations. Yeah, great job. I love the update, no, I love the save prompts. I think that's an indicator of where it's going. More save prompts, prompt plus is coming. That's right. Yeah, yeah. All right, that's going to wrap up day two. I'm John Furrier with theCUBE, with Dave Vellante theCUBE, the leader in enterprise tech coverage. Thanks for watching.