 From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. The past 24 months have seen cloud spending based dual headwinds of macroeconomics and the ability to dial down resources as needed, i.e. cloud optimization. Nonetheless, the big four hyperscalers clocked in between 170 and 190 billion in IS and AS revenue last year. Really, depending on how you factor in the leaked court documents suggesting that Azure is much smaller than previously believed. Nonetheless, hyperscalar growth continued to outpace most markets, accelerating between 18 and 19% in revenue terms last year, despite their enormous size. Now, as we progress into 2024, IT decision makers are cautiously optimistic about spending levels, especially for the second half. Moreover, all hyperscalers report that cloud optimization is slowing. But pockets of cloud cost-cutting remain and while AI gets all the headlines, its contribution to revenue is still a small fraction of the overall spending pie. Hello and welcome to this week's theCUBE Research Insights powered by ETR. In this Breaking Analysis, we update you on our latest hyperscale cloud spending and market share data. We'll analyze the ETR survey data on cloud optimization, assess the AI lift for the big three US cloud players and look at some of the industry trend data on cloud spend by each of these platforms. Now, before we get into that, let's review the macro spending climate. It's worth doing, even though we've talked about this before the inflation data came in this past week, hotter than expected. And of course, it sent the stock market reeling. But the interest rate sensitive NASDAQ continues to climb out of Tuesday's lows. This chart from our predictions post shows just how tied spending expectations are to the economic data. As you can see back in late 2021 as we exited the isolation economy, IT decision makers were expecting a whopping seven and a half percent spending increase for the coming year. Those annual spend expectations continued to contract as the Fed tightened. And those forecasts bottomed out at 2.9% and came in at 3.4% for the full year 2023. Now, the other good news is IT decision makers, ITDMs we call them, expect 2024 to come in at around 4.3% growth. But the caution is it's very much back loaded with Q1 and Q2 spending in 2024 expected to increase 2.4% and 3.1% respectively. And we think the reality is companies are staying cautious because they don't really know precisely what's going to happen. Uncertain visibility remains the case for most CFOs, hence the back loaded expectations from CIOs. The other key trend worth mentioning upfront here is when you look at the sector spending, it clearly shows that AI is stealing from other sectors. This chart shows the distribution of responses from more than 1700 ITDMs in the latest ETR spending survey, which took place in January. The data on the vertical axis represents net score or spending momentum. And the horizontal axis represents pervasion within a sector, for that sector within the data set. It's a proxy for relative account penetration for each sector. Remember, this is a percent of accounts doing certain things, not a revenue projection. That red line at 40% indicates a highly elevated spending level. Now we're seeing cloud rebounding. Let's start by focusing on the cloud computing in that squiggly line. We've seen a steady deceleration in cloud spending momentum relative to the January 2022 survey, when cloud computing was well above that 40% mark. And that deceleration trend is hard to see, but it reversed in the latest survey, bringing the sector back above the 40% line. And this is consistent with what we saw in the revenue data, which we'll review in a moment. Now AI continues to steal budget from other sectors. That's the other key takeaway from the data. AI has gained notable momentum on both dimensions since the announcement of chat GPT and other survey data that we're not showing here. Indicates that approximately 40% or higher of new AI projects are being funded by taking money from other budgets. So that's why you saw a number of those sectors get depressed in the previous chart while AI shot up. So where are we today and what is the impact of cloud optimization going forward? I want to share some comments from the leaders of the big three U.S. cloud vendors. The first one, we continue to see the diminishing impact of cost optimizations. As these optimizations slow down, we're seeing more companies turning their attention to newer initiatives and re-accelerating existing migrations. That's from Amazon CEO, Andy Jassy. Satya Nadella said that period of massive optimizations only and no new workloads has ended at this point. So what you're seeing is much more of that continuous cycle by customers, both whether it comes to AI or whether it comes to the traditional workloads. And then finally, the cost optimization in many parts of the world are something we have mostly worked through. That's Alphabet CEO, Senghar Pachai. Let's look at what the survey data says about cloud optimization. The data confirms Jassy's comments that cloud optimization has attenuated. The percent of customers indicating that cloud optimization is the primary cost cutting method has reduced dramatically from one year ago, as shown here. However, in the all-important financial services sector, we continue to see customers citing cloud optimization as a primary method. That's 12%, up from 5% in the October survey and 15% of retail customers say it's their primary method. The point is underscored by this anecdotal comment which says the customers got good at dialing down and optimizing cloud. They've developed some sort of muscle memory here and while they're tuning or turning more attention to innovation, optimization is still an important tool in the kit. But again, it is down significantly from a year ago from the mid-teens down to 7% of customers saying that that is their primary method. Now, it still could be the secondary or tertiary method but nonetheless, this data supports the comments of the three CEOs. Now, of course, the other big theme we listen for in Ernie's calls is gen AI revenue. Here are some comments from the big three that are worth reviewing. Quote, if you look at the gen AI revenue we have in absolute numbers, it's pretty big number, no doubt but in the scheme of $100 billion annual revenue run rate, it's still relatively small, much smaller than what it will be in the future where we really believe we're gonna drive tens of billions of dollars of revenue over the next several years. That's Amazon CEO, Andy Jassy. Azure and other cloud service revenue grew 30% and 28% in constant currency. That's the number that we use in our forecast including, this is astounding, including six points of growth from AI services. Says Microsoft CEO, Satya Nadella, we'll come back to that in a moment. And then some other AI is definitely something which is driving interest and early adoption. And as you saw, greater than 70% of gen AI unicorns are using Google Cloud. That's something that Google has trotted out as a key data point. I don't know how many of those unicorns are so-called zombie corns. But, and the other point is who knows what other clouds they're using but it's a proof point I guess that Google wants to put out there. All right, so let's take all that and look at the market data. Here we're showing data for the big four hyperscalers both quarterly and full year. And this data, it comes from a combination of our interpretation of the financials. Remember we're trying to pull an apples to apples comparison. We also look at ETR data and other information that we get from our community. For the quarter, these companies, these four companies, we include Alibaba here along with the big three US. For the quarter, these companies generated nearly $50 billion in revenue. AWS and GCP growth accelerated in the quarter and Azure growth was flat which now I come back to, that's pretty remarkable given the six points of tailwind from AI services. So the saying essentially it would have been 22% without AI or who knows, maybe it's stealing from other budgets. AWS is now just about a hundred billion dollar run rate business, amazing. Now Azure is a different story altogether. If you go by the public statements of Azure growth and the statements that Microsoft made saying that Azure comprised 50% of Microsoft's $110 billion intelligent cloud business last fiscal year, you can get to $71 billion in IaaS and pass revenue in 2023. But if you factor in the poorly redacted court documents which we covered on breaking analysis last year and you try to map to those figures, you can't. Azure on apples to apples with AWS's business by that metric comes in at 52 billion significantly lower. Now our hypothesis is that Microsoft agreed with the courts in that Activision case to define Azure in a more identical manner with respect to AWS's business perhaps including certain security and other line items maybe for instance, certain legacy on-prem Azure stack revenue which may be included in the Azure figures that Microsoft reports. So if you adjust for the court leak, you can't map to Azure's publicly stated growth rates nor can you map to the 50% of the $110 billion claim. So that takes Azure market share when you try to do a true apples to apples comparison from the big four, it takes it from 37% down to 31% and bumps AWS up from 48% to 53%. I know it's nuanced. We continue to dig into this issue and to get to the bottom of the story we actually maintain two models. One is that one that maps to Microsoft's public statements about Azure and the other one that tries to map to the poorly redacted court documents to be continued. Okay, here's a graphic of the growth rates for the big three US hyperscalers. AWS is at the bottom line and the blue GCP is the gray and Azure is the orange. You can kind of see AWS reversed the decelerating growth rate trend and actually grew sequentially from last quarter to 13.2% up from 12.5% in Q3 and again, that's for $100 billion run rate company which is insane when you think about it that they can actually accelerate growth at that size. Azure was flat despite that six point tailwind and GCP grew by our estimate which again, Google doesn't give estimates for GCP. They give their estimates for their overall cloud business and they kind of sometimes give hints. They haven't given hints for the last couple of quarters on GCP and part of that was all the analysts just wanted to talk about search getting disrupted and so they really didn't focus on GCP but by our estimates GCP grew but for its size and maturity it should be growing much faster in our view. If you go back and look at where AWS and Microsoft were at Google's cloud size, they should be growing much, much faster and I guess that's the penalty you pay for being number three in the three horse race. Now our assumptions basically follow the macro trends with growth holding and maybe softening a bit in the first half but picking up in the second half bolstered by an ever accelerating contribution from AI. Now speaking of AI, let's look at the spending patterns in 662 AI accounts from the latest ETR survey data in January, the spending intentions data. This chart shows net score or spending velocity in the vertical axis and overlap the penetration within those 662 AI accounts on the horizontal axis. You can see in the lower right that we insert a table that shows how the data are actually plotted with the ends and the key points are from a momentum standpoint AWS and Azure well ahead of the pack in this important AI sector and the only two firms above that 40% mark, Google and Salesforce are close. Salesforce is actually doing really well with its data cloud and Einstein and Oracle is respectable with a 17% net score. Now we filtered this data on platforms with N at or greater than a hundred so it doesn't show for example at the IBM cloud or the on-prem hybrid crowd. This next chart filters the data on 267 financial services accounts inside the data set. And the key points to stand out are AWS actually takes the lead in net score within this all important sector. Financial services is a mainstay for Amazon. Google also does well as does Microsoft but it's quite notable given the early cloud backlash from the financial services industry look how far above the 40% line all the US hyperscalers sit within financial services and in this cut we've not filtered the end and you could see the other players that hit the chart. And the last vertical we'll dig into is retail which tells a far different picture or a different story especially for AWS with retail rivals like Walmart not using AWS. Both you see both Azure and GCP show higher net scores on the vertical axis than AWS in this picture but AWS still has a big presence in the sector but it's below that 40% mark from a momentum standpoint while the other two US hyperscalers are above that. So look that's a quick run through of all the latest data and so much more that we're discussing with our private clients but if you have specific questions let us know and we'll try to help. I want to wrap with some final thoughts. First of all cloud optimization is less of a factor we think the macro will still drive consumption trends optimization remember it means a feature of cloud it's not a bug and it cuts both ways meaning what goes up and still come down and a lot of firms got really good in the last two years of dialing down cloud and optimizing clouds. Again that's not a bug it's a benefit that won't always accrue to the cloud vendor and that's okay they're doing just fine. Now we're looking for flat ish cloud growth into Q1 with a more favorable outlook in the second half of 2024 driven by AI and stable but sticky macro trends meaning the inflation data really was no surprise to us and we don't expect the Fed to just come in and rescue the market with Zerp anytime soon. They're going to be very, very cautious and so that's going to be in a large part dictate how companies decide to allocate capital. So that means AI ROI is going to have to be a tailwind but we think ROI is going to remain elusive in the first half of 2024. There'll be some gain sharing in the back half but this idea that AI is so easy we think it's illusory. It's like any new tech takes time to adopt and figure out the right use cases and specifically in this case to govern properly with all the legal and privacy concerns. Now the other theme you'll hear this year is so-called private AI. That is the idea that domain specific smaller LLMs are going to be applied and deployed within industries like healthcare, like financial services with proprietary data even on-prem. And as well the other factor here is open source LLMs are becoming more viable and are going to be a bigger factor and an option for customers is privacy concerns and edge deployments factor into the decision making. Open source models like Lama could really commoditize the big language models so the key is how the developers of such models deploy them. Microsoft's success with GitHub co-piles could be repeated with productivity software but early reports are using co-piles for things like PowerPoint and Excel is still clunky and Google has a lot to lose with the 10 blue links on every page and it's got its auction model which optimizes revenue has created the greatest monopoly in the history of monopolies. That's perhaps not as relevant to the cloud but it's an example where AWS and Microsoft they don't have to worry about protecting their golden search goose they got other challenges but that's not one of them. In fact the Amazon Rufus was really intriguing to us that's essentially they've applied generative AI to help shoppers. I'm shopping for some new headphones or some new sunglasses and here's what I'm looking for what are the best ones as interaction with you like a shopper assistant. Well, if that's effective I'm not gonna have to go to Google to research or purchase as much as I used to. So these sort of uncertain vectors right now are coming into the market in the short term and it makes things a little bit more confusing. Longer term the picture is bright and like most of these waves will likely exceed initial expectations even though they're probably overhyped right now but in the near term expect some disappointments along the way. All right that's it for now I wanna thank Alex Meyerson and Ken Schiffman on production and Alex does our podcast as well. Kristen Martin and Cheryl Knight help get the word out on social media and in our newsletters and Rob Hoef is our EIC over at siliconangle.com. Thank you all. Remember all these episodes are available as podcasts wherever you listen just search breaking analysis podcast. I publish each week on thecuberesearch.com and siliconangle.com. You wanna get in touch? Got a question? You got a pitch? Email me at david.balante at siliconangle.com or DM me at dbalante. You can always comment on our LinkedIn posts please do. Make them thoughtful. And please do check out etr.ai for the best survey data in the enterprise tech business. They continue to innovate. Great partnership that we have with them. This is Dave Vellante with theCUBE Insights. theCUBE research insights powered by ETR. Thanks for watching everybody and we'll see you next time on breaking analysis.