 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. Predictions about the future of enterprise tech have never been more uncertain. Predictions become even more challenging when you try to make forecasts that are measurable. I mean, generally our belief is that we should be able to look back a year from now and say with some degree of certainty, whether the predictions that we're sharing with you today came true. With some quantifiable evidence to back that up. Hello and welcome to this week's theCUBE Research Insights powered by ETR. In this Breaking Analysis, my friend Eric Bradley of ETR and I update our Enterprise Technology Predictions for 2024. We're gonna cover the macro, IT spending environment, the state of gen AI, AI ROI, cybersecurity, M&A, data quality governance skills, momentum, and momentum from legacy players and 2024 technology priorities. Eric Bradley, welcome. Good to see you again. Always good to see you too, Dave. I enjoy being on the show every time I get the chance. Thank you. All right, so check this out. I have, again, like every year, over a thousand inbounds from companies, from VC firms, from friends, predictions for 2024. I have been through every one of them with a highlighter for those that I feel like are inspiring and where possible, I'll give credit to those. I mean, there were so many good ones. In a way, I feel like a VC, getting all these inbounds and, you know, only... You shouldn't tell everybody that you read every one, Dave. You're gonna get five times more next year now. I know, I do. I go through them. I scan them. I've been doing it for weeks now and I print them all. I'm sorry, I'm killing trees here, but it's really the only way I can manage it. I was thinking this year of using AI to try to prioritize and sift, but I just, you know, the input range was just too big. But any rate, huge, huge inbound. We have a graphic on this to help you understand it relative to last year. So I bucketize them as best I could. Obviously a big jump in AI. Cybersecurity's down, but it's still huge. In the cloud and data center, we even got some predictions around liquid cooling, which I'm not gonna use, but I love that. Liquid cooling's back. Remember the old mainframe days? It was all liquid cooling. Had a smattering of DevOps again and digital and digital was actually, you know, sort of down, but still some stuff in there. SAS and some other tidbits. So, and then let's just do a quick rundown with the next slide of this year's predictions. Okay, and then we'll really get into it. We're gonna talk about tech spending, like we always do. Gen AI, you know, we got this ROI focus here and you can sort of see here. I'm not gonna go through each one because we're gonna go deep. But Eric, I'm super excited to be with you and really want to get into it. So let's start with the macro. The first prediction you see on this first slide number one, tech spending increases. If you bring that slide up, Alex, tech spending increases. Nope, next one. Tech spending increases 4% to 5% in 2024. So when you take a look at this data, so what I did here, Eric, is I took all the macro drill downs and the expectations for the full year spending increase and I plotted them here. So we exited the isolation economy, very enthusiastic. People thought their tech budgets were gonna increase 7.5%. We know what happened. Ukraine, Fed tightening and all through 2022, we saw those expectations for the year go down. And then we saw that through, even after the Fed stopped tightening, we saw it flatten out at 2.9%. We actually ended up at 3.4% in 2023. And you can see the forecast for 2024 is 4.3%. But it's back loaded. So that's a little bit, Eric, of a concern. You got 2.4% and 3.1% in Q1 and Q2 of 2024 respectively. So we got some work to do to get to 4.3, Eric. Yeah, there's a lot of takeaways on that slide. I feel like we could probably do a whole post on that. But one of the main things I think we have to stay positive about and optimistic is there does seem to be a thaw in the spending of what we went through over the last six quarters, where the spending got a business, Fortune 500 at one point was less than half a percent. It got down to 0.3. Then one of the things I like here is not just the overall spend rising, but the largest companies are starting to participate and getting closer to the mean. Now it's still small companies that are leading the way at about 6.5%, but Fortune 500, for example, has gone from 1% to 3% rise in budgets just since July. So we're starting to see the world's largest organizations participate as well, which is really optimistic. Yeah, and that said, you still have SMB significantly ahead of the global 2000, almost double the rate. So that's something that we're watching. I think generally, Eric, organizations are just, there's a lot of uncertainty. I think people are waiting for earnings. I think people are afraid that earnings estimates are maybe a little bit too high. So they're just going to take it quarter by quarter. Yeah, there's some positive signs, but the trepidation isn't over, not even close. There's still people wondering if there's going to be a soft landing or hard landing, or even if we're just going to continue to grow at all. But as you said in that slide, the Fed still kind of controls the reins here, and it's a wait and see game with them. But one of the things that is positive is in speaking to our IT decision makers in our community, the cloud audit seems to be over. They spent an entire year just answering to their CEO and CFO about where their spend was, and that seems to be easing. We're also seeing in the macro survey data that new IT projects are on the rise. So there's a lot of optimistic signs. We're seeing increased net score spending in IT consulting and command services, which is always a leading indicator. So based on the data, I am cautiously optimistic that this spend and this rise will continue throughout the year. Okay, let's bring up the next prediction. Number two, AI is not a rising tide that lifts all ships. Look, there's this narrative out here that AI is going to benefit everybody. We don't think so. We think AI is a two-edge sword in some cases. It's helpful and you see companies obviously like OpenAI and some others that are really taking advantage of it, notably some of the cloud vendors, but 40% of customers say that their AI budgets are coming from elsewhere. So this chart is just selective here. It shows net score or spending momentum on the vertical axis and the overlap in those 1700 accounts. So it's plotted by the end. So it's a measure of sort of presence in the dataset here. And we just selectively plotted some companies and that red line at 40% indicates a highly elevated spending level. And our premise here is that there's going to be haves and there's going to be have nots. There's going to be some me too AI that lags. And so you can see this is from the January data. It's the spending momentum in 662 ML and AI accounts. So you can see where there's AI affinity, obviously Microsoft with Azure and AWS up to the right and well above that 40% line, notably Google is below it, despite their AI chops. And again, this is selective. You got service now, you got data bricks, you got snowflake, you got CrowdStrike, all either data companies are well positioned it looks like in AI. And it's really interesting here, Eric. You got laptops, Dell laptop and Apple laptops. And we're hearing a lot of talk about AI and laptops and GPUs and more cost effective NPUs and laptops. You got some, we added a SAS player like Workday. You got UI path, that two-edge sword. You got some other observability and security companies like Zscaler and Cloudflare in there. You got Mongo, a data company. And then you got some of the legacy guys that we're going to talk about SAP, Dell, VMware, Oracle, Cisco and HPE. Now, these guys are going to be able to take advantage of AI selectively either because of their market leadership or because they have acquired assets in the case for instance, Cisco and Meraki, right? HPE is acquiring Juniper because of the missed AI. And so you really have, I think a mixed bag here. It's not just, oh yeah, throw your glove in the field and AI is going to save you. We don't believe that narrative. Eric, what do you think? Again, so much there to unpack. The hyperscalers clearly are the ones that are benefiting the most at the moment. And then of course, when you have sophisticated data companies like Snowflakes and Databricks, also very important at this point in the journey in AI. I thought your comment around Cisco Meraki was interesting, Dave, because when I just recently did the quarterly report for Cisco and Meraki by far was the bright spot in that data set and really shining in not only networking but also in unified endpoint management. So I think it's really interesting your case. Gen AI is certainly not lifting all boats. And I think the biggest battleground right now is an RPA. Really kind of curious to watch and monitor that and see what happens. You would think that Gen AI would boost RPA but it could also just sort of piggyback it and just kind of jump right over it. And Gen AI and in itself it's embedded properly could end up just basically taking RPA out of the market and just do it itself. I think that's the battleground I'm most intrigued to watch this year. It was interesting, you and I talked this week actually about the open AI alignment and you guys have a data set on that. We're not going to show it because it's a little too sophisticated for a half hour show like this. But what you saw with the RPA guys and the automation guys is the three leaders. Power Automate, UiPath and Automation Anywhere had strong alignment and affinity to open AI and the others not so much. And so there was some, seemed to be some spending momentum around that. You know, we'll see. But I mean, I think generally our sentiment is that market leaders are going to be the AI leaders if they embed AI, they embrace AI, they apply it, they don't AI wash, they partner and they execute. Mike Finley, CTO of Answer Rocket said, you sent in the prediction and the quote, me too AI vendors will sink. Okay, let's go to the next prediction. Number three, 2024 is a year of AI ROI. But payback is not assured. This is a chart from one of ETR's drill downs. It asks how soon after the initial deployment did your organization achieve or does your organization hope to achieve ROI and Gen AI? 57% expect ROI inside of a year, 40% inside of six months. But you look at things like data quality, skill sets, legal and privacy concerns, those remain challenges and headwinds. And look, if payback may not be high enough to fund massive budget growth, we've seen AI stealing from other areas, we've seen some compression, as Eric was just pointing out, it's a two-edged sword in some sectors. And you should expect pushback on co-pilot seat pricing. ETR has some data on that as well, which I saw in the data set. Eric, very interesting that some of the customers are saying, you know what? We don't want to pay all that extra per seat per co-pilot. Yeah, it depends on how widely you're gonna roll it out, right? If you're just gonna allow it to be in a couple of departments, no big deal. But if you're gonna use it at enterprise-wide, that's a lot of licenses to add $30 per seat to. Right now, I think in the testing phase, there isn't too much pushback on pricing. But when it goes into full-scale implementation, I think you're right, it's gonna be difficult. We'll see how they handle that there. Just in general, we've been doing a lot of work on generative AI. If anybody wants to hop into our data and our custom surveys, I'd be happy to go through it. But I think it's amazing to watch the evaluation rates. Only 25% of our ITDM communities say that their organization isn't evaluating at all. I haven't seen a technology ramp up this fast. It's really incredible. But as you said, over a quarter of these people aren't sure there's any ROI at all. That's still a high number, that's a little scary. The other thing I think that's interesting is where is the budget coming from to fund this? Right now, it's split. About half of our organizations are saying that they're funding this with new money. The other half saying they're stealing it from somewhere else. And where it's being stolen from is common sources include non-IT departments and productivity applications. So it's interesting to see as this continues, I want to watch the evaluation rates go into actual use cases, and I want to see where the money's coming from. I'll give you another stat on that when I was digging into some of the RPA data, because that is kind of the obvious two-edge sort area. And only 7% of the customers said they're stealing from the RPA budget. But two other points there. One is when you look at certain industries like financial services and manufacturing and industrials, the figure doubled. So that was a bit of a concern. And when you just mentioned it's coming from other budgets like non-IT budgets and line of business budgets and other sort of productivity budgets, many of those could be automation related. So those categories aren't necessarily mutually exclusive. Yeah, agreed. And anecdotally, we did a panel on this and one CIO laughed at the pushback on the pricing and he said, what do I care about $30 per license if it saves me 100 full-time employees? So it's really a wait-and-see game. If the promise of Gen AI actually delivers, I think the pricing demand is gonna be pretty strong. Okay, let's take a look at number four. The next prediction, the power law begins to take shape in 2024. Now, let's explain this because it's really nuanced. The power law really describes, it takes an example from the music industry where you had a very hard right angle where just a few labels dominated the industry and you had this kind of long tail of music producers. And we see something similar with Gen AI but different. We see the torso, the cloud guys dominating and we take liberties, by the way, with the term power law. We've got here in the dimensions, the vertical dimension is size of model. The horizontal dimension is model specificity and we've identified some industries where we think we're gonna see specific models and potentially on-prem models or likely on-prem models emerging. We're already seeing some of that. And the idea being the cloud guys and the big AI, LLM vendors, they're gonna have very large models and they're gonna initially, they're the ones that are dominating, they're getting all the discussions. But you've got this open source, this red line pulling the torso up and to the right. Lama two is the obvious one, but you've got some other independence and other third party and open source players that are pulling that up to the right. And then the long tail is specialized AI. So cloud continues to outpace on-prem, no question, but we're seeing that privacy use cases are emerging and open source pulling that torso up. Based on the ETR data, just playing around with some of it, I can infer that about 30% of the Lama two deployments appear to be on-prem. Meta has indicated it could be as high as 50%. And I don't think, Eric, that in ETR, you're surveying three letter government agencies. So they're probably doing a lot of stuff on-prem. And we're also seeing the emergence, initial emergence of model integration, like private model gardens. Think things like bedrock, but building your own bedrock. So right now it's sort of a very mixed environment. I guess the prediction really is that you're gonna start to see signs of this power law emerge in 2024. What are your thoughts here, Eric? Yeah, it's a very interesting model and theory that we're kind of rolling out on this one. I do still think that there's a little bit of a bifurcation of what's happening and I think it's too early to tell, but very clearly there's gonna be a long tail to this. We forget how early we are in this. It was just a year ago that OpenAI came out, that OpenAI, excuse me. There's a lot more to come. I think the most important thing that you said there for me is the data that we're seeing right now in cloud is not just public cloud. We're seeing a real resurgence on the hybrid cloud with a strong leaning towards private. And we're hearing this a lot from our CIOs as well. We just recently did a series of eight interviews on 2024 top trends and private cloud was spoken about by six out of eight of those CIOs. And I do think there's a lot of data concern. There's a lot of regulatory concerns still around GenAI and being in control of that data and having that sovereignty in your own private cloud is one way to handle that. Yeah, and you think about companies that have competitive data and they're trying to use foundation models to give access to their internal sales teams on things like knockoffs and other sort of competitive information, pricing information and they want that to be available. They're very nervous about putting that in the cloud. They're very nervous about bringing in other data sources. They're nervous about the legal requirements and so it's going to take some time. Well, they should be too. As well they should be. As well they should be. It's way too early for people to just be going around and throwing that data around and trusting where it's going to end up. Just some quick hits from some of the other predictions that came in. Some of the thousand. John Rose from Dell. He's the CTO of Dell. He said that GenAI dialogue is going to move from theory to practice and is going to focus more on inference. Quentin Clark from General Catalyst of BC predicts that specialized AI will take shape and open source models will emerge. That's consistent with the power law. Bert Greifender who's the CTO of Dynatrace predicts that hypermodal AI which combines different AIs with other data sources will emerge and much of that is going to happen on-prem in our view. It's interesting. We sometimes forget there's more AI than just GenAI and Brian Harris is the CTO at SAS predicts that GenAI has to be viewed as a feature of industry solutions not a solution in and of itself. Again, we agree that these domain specific AIs are going to see that long tail. Patrick McFadden of DataStacks predicts that we're headed more toward a GenAI monopoly. So that's sort of counter to the long tail. We hope not, but we kind of agree that hyperscalers right now are in the driver's seat. He predicted actually back in November that regulators are gonna come raining down on these big internet companies and that prediction has already come through with Lena Kahn this week, taking recent actions. Okay, let's get- One quick thing to add, Dave, I can on that. I think it's really interesting in the recent GenAI study that we did, it's split 50-50 between people saying that they're going to develop their own AI solutions using open source, whether it's Anthropic or OpenAI. And the other 50% are still hoping that it'll become embedded in their already trusted vendors. And those vendors, they've got a window, but it's not that large of a window. They need to really start rolling that out and start embedding AI into their offerings if we're gonna see that continue. I just thought it was an interesting data point that came from the study I wanted to sneak in. I'm glad you said that. Five years ago, I predicted and worked with, collaborated with my friend, David Michela, who wrote, he's an author, and we kind of predicted, pulled out his prediction that AI, you're going to buy it, you're not going to build it. And then of course, GenAI comes out and it becomes, wow, this stuff is actually pretty easy, even though there's still some barriers and skills issues. But like for instance, the Cube AI, you go to thecubeai.com, you can see our RAG, our Retrieval Augmented Generation Model that we built, and most people haven't done that. You know, we got a development team, but you're going to see RAG out of the box and you're going to be able to point that at your data sets. And so it's going to become easier and you have to build your own AI. So I don't know how much of that embedded versus build your own is simple RAG stuff that you're going to do out of the box versus intense AI, you know, we'll see. It's going to be interesting. Okay, let's bring up number five back to basics in cybersecurity. You know, AI gets all the headlines, but it's going to be embedded into cyber and it's going to support these areas shown. We're seeing identity, single sign-on, vulnerability management, endpoint, network security. These are the areas of information security that are the highest priority in organizations and it's a lot of the same stuff. And we think that consolidation trend is going to continue. We also think that the VCs are going to keep funding cybersecurity startups because it's still broken. So that's counter, but the consolidation trend is going to favor the consolidators, Palo Alto Network, CrowdStrike, Zscaler, even though consolidation of vendors, of redundant vendors was the number one method of reducing costs last year and it's way, way down. There's a premise that we're putting forth here that that is not going to hit as hard in cybersecurity because of the crowded space. The identity crisis remains in play and is a major challenge, pun intended. And again, AI is going to be embedded and begin to change the SOC analyst experience. We saw this at CrowdStrike with the announcement of Charlotte, their LLM, which is very, very powerful. Eric, your thoughts on this data? Yeah, it's very interesting what we're seeing right now in the security space that everyone is really progressing. We're seeing all these vendors roll out different feature sets, really pushing the envelope. And at the same time, we're seeing consolidation happen. And there's so many startups and my CISO friends are much more likely to take a look at a startup than my CIO friends. They're just always looking for an edge and an advantage. So they're willing to test out those series A through C companies where sometimes you don't see it in the rest of technology. I think we're going to just continue to see importance and explosion of new technologies, new features in this space. And I think some of the bigger players are going to have to get a little bit more M&A active if they're going to keep up. We're seeing that a little bit, but I think we're going to see more of it. I think that environment is stalling out. The other thing I want to point out is anecdotally, and I speak to a lot of security experts, their focus this year is not so much on the tool set. You know, we used to talk all the time about, I want best of breed. I want layers of defense. I need this tool, I need that tool. Right now, all they're talking about is employee training, penetration testing, asset management, vulnerability, patching. They really are getting back to the basic hygiene of security and that's where their focus is going into this year. And it's not just one. It's almost everyone I speak to. So I think it's going to be an interesting year and I like the way you phrase that and back to basics and security. I agree 100%. Yeah, thanks for that. That's some good data points and perspective. Just some predictions and trends from the marketplace. Again, the inbounds of Dell's annual data protection survey that Rob Emsley and Michael Wilkie shared with me, says 65% of organizations are not confident that their organization, not very confident that their organizations could fully recover from a data loss incident. The Veeam data protection trend report found that 52% of production data is backed up on tape still. So everybody says tape is dead. No, it's not. And 61% of production data is also backed up on the cloud. Dave Russell and Jason Buffington presented these stats to me recently. Let's see, voice is going to become the new fingerprint according to Aaron England, the CPO and CTO of Rev and Nick Schneider of Arctic Wolf predicts that over-hyped tools driving the need for security operations, which of course are driving the need for security operations of course, which Arctic Wolf provides as a managed service. So some thank you for sending those stats in everybody. Okay, number six, private market shifts, M&A and IPOs pick up. Here's a chart. This is all private companies from the emerging technology survey, ETS, that ETR does, I believe it's quarterly. Again, spending momentum in the vertical axis, actually sorry, net sentiment, which is intent to engage. Do you know the company and you're going to do anything with them? Are you going to evaluate them? Are you going to deploy them? Are you going to deploy them further? So intent to engage on the vertical axis and then mind share. You know about this company and the horizontal axis. And then we've just picked and chosen some names here that showed up on like the top names in each axis. So you can see here, open AI off the charts, Docker, Figma, which I guess was supposed to be acquired by Adobe and they canceled that acquisition. Databricks, OneTrust, BeyondTrust. You got NetScope in there. We've talked about them. You got Grafana, Sneak, Redis, database company, Wiz, very hot security company, DBT Labs, the overlay on, you know, to try to pull metrics out of data platforms. Cohere, an LLM player, Entropic has gained a lot of VC and other investments from the likes of Amazon in particular, $4 billion investment also Google. You got Hugginface in there that a lot of people are doing work with. So we also think you're going to see more smaller seed rounds. Great time to start a company and VCs love it too because they don't have to put as much in all this AI hype and you can do more with AI. We think cyber and AI are going to continue to get all the attention just like all of our inbound. And we think M&As and IPOs accelerate potentially Databricks, Sneak, Arctic Wolf, Beyond Trust. Last year I think there were probably, I want to say 150 IPOs down from the previous year. We think we're going to see more IPOs and more IPO action this year, but we're not going to get back to 2021 levels where we saw a thousand IPOs. Eric, your thoughts. I completely agree. On the private equity side, particularly, they had a lot of money heading into this recessionary period where the headlines got bad and they stopped spending, but they still had the cash. And I think that environment's really warming up where we're seeing a lot on the private equity side. I mean, heck, New Relic got taken private, Ford Rock and Ping are about to be joined and probably rolled back out again. I think you're still going to see a ton of happening on the private side. And I think, yes, IPOs are finally going to warm up again. It's just crazy when you think about a company like Rubrik or Databricks still being private. So I definitely think we're going to see some IPOs. And as far as that M&A activity, there's some names on that list that are just right for the picking. I mean, Cohere, Hugging Face, particularly on that side, I can't believe they're there. And we're constantly seeing Wiz and Sneak, incredible data for young companies, really strong, growing their provision, growing their mind share. You need to take a look at these. If you're a large company and you want to secure up your security portfolio, there's a lot of names out there, like an Arctic Wolf, a Wiz, a Sneak, they need to be looked at. And Mark Sassen of Pinpoint Search Group shared that, I believe this was just a cyber only, 437 funding rounds and M&A transactions with $8.6 billion raised over 346 rounds of 91 total acquisitions last year. So we'll keep an eye on that. Okay, let's go on to the next one. Number seven, data quality and governance concerns favor trusted ecosystems. Let's talk about this. This chart from ETR asks, which aspects of the organization's data and analytics programs are your organization prioritizing? The most to support GNAI goals select up to two options, data quality, data lakes, data diversity, data literacy, data integration, governance, metadata management. And we think these, this favors trusted platforms that have ecosystems to support these types of activities. AWS, Azure, obviously Google, the hyperscalers, even though AWS and Azure are well ahead of Google Cloud, but Snowflake and Databricks, even Oracle, it's a trusted platform, it's got transactions. When you start to think about the sixth data platform that we've talked about moving beyond just separating compute from storage, separating compute from data, actually unifying metadata. This gets complicated because of all these other factors, as well, when you have different data types like transaction data and unstructured data and distributed data and different query types. And when you bring together transactions and analytics at scale, you got to throw an Oracle in there because they're the company with the transaction data I would throw in IBM as well. We're going to talk about them a little bit later. But so you've got some interesting activity going on here where people are really focused on data quality improving. And we think, I don't know if you agree, Eric, that this is going to favor some of those established platforms. Without a doubt, and the data, we're going to get to it in a minute so I don't want to kind of steal the headline. But I love that you're bringing up Oracle, IBM, Dell. Their data set looks fantastic, heading into 2024, something I haven't been able to say in quite some time. But when we talk about this particular aspect, it all comes down to data quality. That's what we're hearing. I don't care who you are. If you want to use a large language model, any sort of AI at all, it comes down to your data quality. And we've run a data company, and I know for a fact it's garbage in, garbage out. You have to have good quality data. After that, it's about the ecosystem. It's about your ETLs, your pipes, and then you can finally get into analysis and getting into your hands of your business users. But I still think we're at the stage of data quality. I think it's utmost importance, and you could see in our data set, I think it was two to one favored, any other aspect in that answer option in that survey. Okay, great, thank you. Let's bring up number eight, renewed importance of new data literacy and skills and yes code, which I'll explain, but this came in from Eric Bradley and I'll just read it verbatim. Gen AI as well as more business user friendly self-service capabilities like low code, no code, RPA and Gen UI tools code generated from screen grabs. That's my little addition. Bring with it new sets of skills that will be in demand in the market, watch for the rise in offerings from IT training companies like Pluralsight, SkillSop, LinkedIn, Learning, Coursera, et cetera, that focus on things like Gen AI, prompt management or ethical responsible use of Gen AI, et cetera, we'll start to see new roles like, I love this, Gen AI prompt engineering Eric, you write on on that in the market, as more orgs let Gen AI proliferate, there will need to be more data literacy training in general across the workforce so that the outputs from Gen AI are used properly and Gen AI hallucinations are seen with a critical eye or minimize and yes code is Gen AI plus front end tools equal generative UI, that's from Lee Robinson, VP of product at Bursell. But Eric, this is your wheelhouse, you shared this prediction with me, thanks for doing that, maybe you can elaborate. Yeah sure, first of all I gotta give all credit to my senior analyst, Dr. Darren Brabham, this was him, he's the one who leads all data aspects for us here at ETR and he's fantastic so I'm gonna give him credit before he sees that and gets mad at me. So this was Darren's but I completely agree with him and one of the things I wanna add anecdotally which I find really interesting is I'm seeing Gen AI prompt as a skill set listed in job descriptions and even in resumes that we're getting, I've never seen that before, that's something that's just new in the last month or so but basically what this comes down to is there's a lot of non-technical business users that need to become more data literate and develop those skills just to stay relevant in their own jobs, whether it's me at age 49 or whether it's somebody young, you have to figure this out and there's a lot of forces that are happening whether it's low code, no code apps or the rise of Gen AI, it's all converging to make sure that the business users themselves can actually handle this type of workflow and you have to become data literate, it's not gonna be difficult because the vendors are making it easy but you do have to make a little bit of an effort to actually stay relevant in today's world and as we're seeing the majority of the budget for AI right now is coming from the business departments themselves, non-IT related so I think this is a trend that's here to stay, I would urge any young people out there to go ahead and make sure you get yourself at least a little data literate. Great, thank you for that, Eric and Darren. Okay, let's bring up number nine, legacy rebound powered by AI, laptops, cloud and acquired assets, so this is really interesting. So first of all, we're showing you a chart, it's a shared net score on the vertical axis and overlap which is plotted, it's informed by the end so it's really a measure of presence and overlap within that 1,700, 1,766 N in the accounts and we plotted, Eric, I just, I picked some legacy companies and legacy I guess is a derogatory term, it's a pejorative but to me it's not, I mean you build a legacy, I got a friend who is a financial earner legacy, he calls it legacy, I mean he's been in business 30 years, he's a very successful financial planner. Anyway, you got Cisco on here, Oracle, IBM, Dell, HPE, but IBM, IBM Watson, SAP HANA, really one of the few up over that 40% mark but in Maraki we talked about before, Red Hat which is the asset, Aruba which is an acquired asset. The most interesting thing here is the momentum that we're seeing in the market on laptops and we know there's a new Windows cycle coming, there's a laptop refresh cycle, Apple has had NPUs in its systems for a long, long time, Dell laptops, I think are gonna power that company this year. Cisco acquiring Maraki, really doing more with that asset, now acquiring Splunk, IBM getting its act together with Watson, you saw its recent earnings announcement, looks like Arvin Krishna really has that company on the right track, it's got the Red Hat acquisition so you're seeing these legacy companies, these established companies, in the case of Oracle investing, they've certainly done a lot of R&D work, they're making huge acquisitions like Cerner and whereas in the old days, Eric, you had situations where the big established companies would poop who the next wave, we saw that with the Dex, the Primes, the Wangs, the DGs, companies that young people in this audience have never even heard of, they were high flyers, sun microsystems, they were the hottest companies going, they're gone now because they pooped the future. These leaders today, they don't dismiss the future, they invest in it because they're paranoid, only the paranoid survive, as Andy Grove said. But I'll throw it to you, this is something that you put on my radar, what are you seeing in the ETR data and what makes you sanguine about some of these legacy companies? Yeah, I haven't been excited about these companies in a very long time, the data looks incredible across the board and it's amazing the breadth of the rebound we're seeing in their spending trajectory, it's not just one area, it's coming from cloud, it's coming from the data side, in the instance of IBM and Red Hat and Ansible, they're just doing fantastic. VMware, what's happened there with Broadcom going away from their channel partner was just stupid, I don't know what else to say. And what we're seeing right now is so much share shifting away from that to some of these other people and they're trusted, they're already entrenched in an organization and what happened, at least what I'm hearing anecdotally, is a couple of years ago, people were saying, I'm sorry, Oracle, IBM, Dell, SAP, you guys are great, but you didn't keep up and I'm really gonna shift over to the cloud, I'm gonna take a look at this. And then what happened, the world kind of paused, spending paused and they didn't do it. Now two years later I'm talking to them and they're saying, you know what, these things kind of got a little bit better, they caught up, I actually think it's a pretty good product now and is it really a priority for me to spend all this time and capital and resources to shift off what's an improving product to go to the cloud. And at the same time, they just went through a cloud audit and found out the cloud's not always as cheap as you think it is. So what we're seeing right now is that these companies were all given a second life without a doubt and we're seeing the data broadly improved for them in many areas and it's gonna be great to see what they do with it. They've gotten a second chance and I hope that they just continue investing using R&D wisely and going after some M&A and just keeping their footing because no one wants to see a world where it's just Microsoft and AWS and the enterprise. Yeah, so I'll share as well just some pros from a recent report you guys just put out. Don't call it comeback. They've been here for years. ETR has data rebound on legacy companies like IBM, Oracle and Dell working thesis. The recessionary environment and budget crunch stopped the planned lift and shift of core mission critical apps to cloud providers giving these companies time to catch up. Now coming out the other side, the existing functionality is good enough and replacing them no longer is the top priority. You know, let's see what they do with this. Second chance as you just mentioned and the legacy names that we just talked about asserting their presence back in the cloud race like Oracle with OCI, IBM sort of in a different way really focusing on the hybrid cloud which seems to be working. Dell as well has got its cloud in the form of Apex HPE with its GreenLake asserting their presence back in the cloud race can be something to watch this year. And with that comes other renewals of legacy software footprints, hardware refreshes, software servers, storage, et cetera. And then as we saw in that chart, laptops and we're going to see a laptop refresh cycle we think we heard it in Intel's Intel had very disappointing earnings but they did point to growth in future quarters really due to PC sales. Okay. The data, real quickly, the data on that is very strong. I easily we could have put a full hardware refresh cycle into this prediction post. I think maybe just it might be a little bit well known so we chose not to but the data across the board in all areas of hardware, not just the laptops and PCs but we're also seeing in storage and servers. There's definitely a refresh cycle coming in the hardware space. And that's good news for these companies and look, there's so much territory that we could cover on these. What we try to do and thank you again everybody who's sending in these literally thousands and thousands and thousands of inbound's we really appreciate it. We try to find predictions that A can be quantified so they're kind of binary where we're right or wrong and B does it align with some data that we have we can actually go back and do that look back but so thank you again. Okay, the last one let's bring up number 10 tech priority cyber analytics, AI, collaboration cloud networking automation remain the top tech priorities. Look, this chart you guys run this this is an end of 890 cyber has always been the top priority. Yeah, it's maybe down a little bit but no matter what industry you look at no matter what geography you look at it's right up there. Analytics holding strong, data warehousing, data matters and even given all the Gen AI hype what you can see is on a nice steep uptake here it's still people got to get their data act together before they can really take advantage of that. Collaboration was obviously top dog or a top dog during the pandemic, still important. Cloud, yeah, it's tapered off a little bit. Cloud optimization was a big thing last year but cloud is still where a lot of the innovation is happening, the optionality in cloud the ecosystems in cloud are still really powering innovation. Networking becomes more important in the world of AI it's like the new bottleneck and we've talked about RPA it's been a hot market for a long, long time so it makes the cut here and as you can see it's picking up a little bit it's the classic two-edged sword Eric with RPA. Your thoughts on this? I think the most interesting aspect in that and we do run this all the time and it doesn't change that often so even a small integer movement is actually of interest and that cloud migration number that's a big drop. To me that's the main takeaway when I first ran the study and we looked at it I always expect security to be the number one I was not shocked by the movement and machine learning and artificial intelligence cloud migration was. So after we ran the survey I did eight interviews, top trends series which I'll be releasing that on Tuesday it's an amalgamation of all the findings and we asked people about this why is cloud migration showing it's slowing and they said basically that everyone always anticipated their cloud workloads to get to 60, 70, 80% but it's happening much, much slower than they ever anticipated. It's still happening it's just not happening as fast and the majority of the people I interviewed again were talking more about building out private cloud assets they wanted more of a hybrid model not directly going to cloud migration in the public cloud. Yeah, this is interesting because I think that is a somewhat of a concern I've been forecasting we saw last quarter Amazon's growth rate the deceleration of that growth rate stabilized and I'm expecting an uptick this quarter not a huge but an uptick maybe a couple points in growth really from Gen AI I would expect the same for Azure and we saw a little Azure action or Gen AI action last quarter from Microsoft, Microsoft announced I think on the 30th or Amazon shortly thereafter I think you're right I think a couple things is I think the prevailing narrative that 90% of the work remains on prem a big chunk of that is telco and that telco and that whole telco market that communications market is probably as big as the traditional IT market. So if you take that out a much higher percentage of the workloads are actually already in the cloud. So it's not so much a story of migration anymore it's a battle for new work, new workloads, new spending much of that AI work is being done in the cloud today but because of the reasons that we mentioned before and the whole discussion that we had talked about around the long tail of the Gen AI power law and the fact that budgets just aren't going through the roof like they were in 2020 and 2021 people have to make choices and they have to make trade offs. I'll give you the last word on that Eric. Yeah very interesting on that I agree. I also I just wanted to point out your comment about AWS anyone that actually follows our data you wouldn't have been surprised in the slowdown on AWS in the cloud. You really wouldn't. I'm looking at my chart right now just going straight down to the right went from 70% down to 40% over the course of 2022 and 2023. What we are seeing now however was a really significant rebound. So that cloud audit does seem to be over and it totally when I speak to people and I do think your comment was spot on. It's not anymore about the migration of it's just actually what work is being done there and it's going to have a very long tail. The digital transformation is not over it's a long tail game and I still think cloud is healthy but you can't really keep those growth rates up forever. Yeah that's definitely the new way but it's not about cloud migration anymore that lift and shift occurred where we squeezed a lot of juice from that lemon there's maybe some left but now it's all about innovation and I think a lot of that is coming from Gen AI. We've noticed, I've noticed just anecdotally looking at the data from the drill downs and the ETR data that when a company announces a Gen AI and it goes of GA, you get a big uplift. We saw this with Vertex at Google Cloud Next. We certainly saw this at Microsoft. I would expect we're going to see this with Bedrock going GA. I think it went GA late last summer maybe September, maybe even October time frame so I would expect to see that in the Q4 numbers. Yeah but hey, as always, Eric, appreciate your time and we're going to be here tracking this on an ongoing basis. You guys do tremendous work. Really appreciate the collaboration. I think this is our third predictions, right? Third year. It's a therapy in a row, yeah. Always enjoy it. So thanks again. Okay, that's it for now. Thanks to Alex Myerson and Ken Schiffman on production Alex also manages the podcast. Kristen Martin and Cheryl Knight they'll get the word out on social media and in our newsletters and Rob Holt is our EIC over at siliconangle.com. Thank you all. Remember these episodes are all available as podcasts wherever you listen, just search, breaking analysis podcasts. I publish each week on the Q research.com formerly Wikibon and siliconangle.com and you can email me at david.balante at siliconangle.com or DM me at dbalante comment on our LinkedIn posts and definitely check out etr.ai. Not only do they have the best survey data in the business, we're going to market together. You know, we're working very closely with the Q research analysts and the ETR data. So check that out. This is Dave Boulante for the Q research insights powered by ETR. Thanks for watching. We'll see you next time on breaking analysis.