S&P Global Inc. (SPGI) Earnings Call Transcript & Summary

Hello, everyone, and welcome to today's webinar. My name is Sarah James, and I lead the Tech Media and Telecom news team at S&P Global Market Intelligence. I'm thrilled to be your moderator for today's session titled GenAI Fundraising from private rounds to public markets. Today, we are going to talk about both the record amount of fundraising we saw in the first half of 2026. and why GenAI companies are now turning their eyes to public markets. Before we dive in, I have a few housekeeping reminders. All engagement tools are resizable and movable, so feel free to adjust them for optimal viewing on your monitor. We want this to be an interactive session. While we may not be in the same room, your participation is key to making this experience engaging. We encourage you to submit your questions throughout the presentation. To ask a question, please click the Q&A button at the bottom of your screen. Don't worry about punctuation, only we will see your questions. If you're joining us for the replay, please use the request demo link found under the related content widget to reach out to us. This widget also includes links to our thought leadership resources. You can also access our webinar replay portal to revisit the session and others on demand. This webinar features close captioning in English to activate it, simply click the CC icon and the media player. And at the conclusion of the session of Reed survey will appear. -- completing it takes less than a minute and your feedback is invaluable to us. It helps us understand what aspects of the webinar you found engaging, identify areas for improvement and gather suggestions for topics you'd like us to cover in future sessions. Now please note that the activities of S&P Global Market Intelligence are independent and separate from S&P Global Ratings, S&P Global Ratings maintains a separation of analytical and commercial activities. Thank you for joining us today. The webinar will begin with a brief presentation from my colleague, Gary Shuda, who covers capital markets and M&A in the tech space here at S&P Global Market Intelligence. -- he'll be walking us through his research into the funding we have seen thus far this year and for GenAI. After his presentation, we'll hear from Melissa Auto, Head of Visible Alpha Research at S&P Global Market Intelligence about the financial metrics that are supporting these funding trends and why these funding trends are not likely to continue. Then, we'll move straight into a panel discussion with our guest speaker, Sherri Baker, National Capital Markets leader and partner at KPMG, and we'll also be taking your questions. So without further ado, Iuri, can you get us started? Actually, before we begin, let me ask -- we're going to start off with a brief poll. How do you expect your organization's budget for AI initiatives to change over the next 12 months? Do you expect them to significantly increase, remain about the same, decrease or significantly decrease. And just take a second to answer the poll and then we will begin with our presentation. With Iuri giving us his Uber view. And just waiting for some answers to come in, usually takes about 15 seconds. Interesting. So we've got -- it looks like everybody is expecting their organization's AI budget to either increase or significantly increase and then about 1/3 or a little less than 1/3 to remain about the same. All right. Iuri, do you want to take it away?

Thanks, Sarah, and great to see -- great to see really see that spending is growing. So yes, I'm going to -- we have a dense presentation and like to go through it quickly, and then I'll hand it over to my colleague, Melissa. So here is a quick rundown of the entire value chain of basically how we see it and what we consider to be in AI company from chip makers to the application layer and broadly, we have AI applications, which include foundation models and user application and then AI infrastructure, which includes the chip makers, cloud infrastructure, like neo cloud and the software tools to build, implement, test, secure AI and so on. So if we are going to the next slide. So we can see funding for GenAI companies has already shattered last year's record Q1 was the strongest ever with more than around $40 billion raised from private markets. And Q2 was the second best-ever quarter and these numbers, they are largely due to a massive concentration of funding into top-tier foundation model providers like those provided by openAI and atopic. But we believe this is very likely to be the peak in transaction value for GenAI in private markets, at least for a period because we think a lot of these companies -- a lot of these companies have already put to test private markets in terms of how much they can raise and now are increasingly seeking to move their fundraising activity to public markets, which we're going to discuss in more details in the panel. And why we believe that also, if we are looking at the GenAI infrastructure, infrastructure, which, just as a reminder, includes the chipmakers, includes cloud infrastructure, the neo clouds and software tools like data bricks, those provided by data bricks, for example, snowflake, so if you're looking at general infrastructure, a good chunk of this company, especially the larger ones have already moved to public markets in recent years. And this includes companies like Corwive, Cerebro systems more recently, another chip maker, Grok, was acquired by NVIDIA. And from our numbers, we can see fundraising has been relatively strong for the infrastructure, but it's probably -- I wouldn't be surprised if it goes down this year. And this is primarily because a few of the companies that can raise big private rounds have already moved to public markets. If we're moving to our next slide, we do this research where we exclude foundation model providers because they sort of skew the numbers upwards and just look at the GenAI companies that they don't own a frontier financial model. They use a third party where they have their own, which is fine-tuned or that make their own but is more specialized. And we see -- so for GenAI, excluding foundation models, we see a sequential increase in funding but an annual decline. So annually, this -- we see a decline. And we think some of these declines can be attributed to factors like the largest foundation models have increasingly moved into different verticals like enterprise, legal, coding and so on. And this does make some VC investors avoid or at least as funding for AI companies that are not a the fontier, looking in this environment, when a foundation model like we saw with Entropic launch in cohort, they could just come and crush it by attacking these specific verticals like coding and legal. And -- as a result, we think investors are looking elsewhere, we're pausing a little bit, looking more into what there is in the infrastructure layer. And on the other hand, I think also a lot of the capital is being stucked by -- in private markets by top foundation model players. They are growing at a speed that has never seen before, never seen before speeding public -- in a private market. And as a result, I think investors are sort of pausing, but they're not thinking to stop their investing activities in non-front foundation models, but they're definitely looking for a pause and trying to understand where this is leading before putting more money to work. And if we are going further down into the GenAI application layer, we divide it by sort of the use case, audio code, image, multimodel, synthetic data, text video. We can see text and code remains 1 of the top funded verticals, synthetic data a little bit more. But the most interesting that we see is audio actually. And we -- audio has seen an increase basically -- has been seeing sequential increase over the past 4 quarters. And it is becoming a use case that is more and more important. And if we're going to the last slide, and we've seen -- I want to talk a little bit about the token Maxine trend and we saw news that some of the companies burn through their entire annual AI budgets in just a few months. So we looked at the data from the fintech company ramp, they have about 70,000 business customers, which most of them are so-called AI peels, they are investing a lot in AI. And the data shows that the token Maxine trend is essentially limited to a few power users rather than being broad-based. So this shows -- this chart shows that the average company still spends just $11 per month per user on AI tools, which basically this equates to a Netflix subscription. And this does show the potential for growth and for AI demand to continue to grow exponentially from these levels. So with this, I finish my presentation, and I will hand over to Melissa.

Thanks, Iuri. It's great to hear all the different things happening on the VC side. Good morning, everyone. Thanks for having me today. Can we go to the next slide. So 1 of the things that I wanted to kick off with from my present part of the presentation was to just highlight in the public markets, what has been happening in terms of CapEx spending? And it is absolutely staggering to look at these numbers. If we look at the major tech companies, so Alphabet, Microsoft, Amazon, Meta, and Apple. Back in 2019, they were all kind of similar parameters for CapEx in total about $80 billion. And then let's just fast forward to this year, we're looking at close to $700 billion. And next year, based on visible African census, that number is projected to go to $850 billion. And so when we put those together, between this year and next year, the major hyperscalers are expected to spend $1.5 trillion, very substantial amount of money coming into the market to be spent. And normally, the next question that I get asked is, are we in a bubble and where is that going? And why isn't Apple participating? So let's go to the next slide and take a look at this. If we look at the balance sheet of these hyperscalers, they are very strong. So Google, Microsoft, Amazon, and Meta. You can see very clearly, as we look out to 2026, 2027 all of the debt-to-equity ratios for those companies are expected to be well below 1, which is, I think, a fairly is a decent rule of thumb around health of the balance sheet. Whereas we do look at Apple and Oracle, for example, these are much higher. And Oracle, I think by definition, is the level -- very clearly that Oracle's debt-to-equity ratio is expected to be over 3%. So I think one of the questions I'd like to go back to that initial question around the bubble. The reality is that the hyperscalers have a lot of cash that they can spend and have had a lot of cash that they can spend. So if they start to leverage up their businesses, the amount of capacity is very significant. This could -- like imagine if Amazon or Alphabet took their debt-to-equity ratio up to the same levels as Oracle. I mean this would be very significant. So that's actually how I'm looking at it and how I'm watching it. And I'm also using a total debt, which is incorporating different facets of their liabilities on their balance sheet, not just simply long-term debt. but to really look and see where the leverage may come from. So let's go to the next slide. One area that we are seeing all of this money being spent is around Memory. Memory was essentially left for dead. It's an area that is very important to the applications, as Iuri alluded to, as an application leverages AI and gets to know you, it remembers you. And in order to do that, it requires memory and quite a lot of it. And so that has taken the expectations for Memory absolutely through the roof. And I mean, these were doing very little in revenues. And you can see very clearly a Samsung, SK Hynix and Micron, all seeing their expectations for the next couple of years really skyrocketing. And that is really driven by price increases due to this enormous demand coming from the hyperscalers. And there is really not much that's going to slow that down. It's really very much intact. We don't see anything that would say that we're going to stop buying Memory. I think the question is, how it's managed, how it's navigated and how much new supply will come on to the market over the next couple of years. So I mean, this is 1 area that we're watching very closely, and it's continuing to defy gravity. Can we go to the next slide, please? Another area that is worth highlighting around this are power consumption trends. This is a study that was done by Columbia Business School, Colombia showed how the major 4 hyperscalers are really using a lot of power in the U.S. for their data centers. It went from fairly low levels back in 2018 to now it's about 5% of total U.S. annual consumption. And it's -- they're projecting it to go closer to 20% by 2030. So I think there's different views around this. I've seen other studies that are looking at more like 14%, 15%. But the reality is that it's probably somewhere in that range, given the amount of investment that's coming in. So what does that mean when we say there's more power consumption that's coming through. Let's go to the next slide. This is, I think, really where it gets interesting. So in order to facilitate all of this fantastic growth and infrastructure and to ensure that the compute happens, it requires a lot of electricity in order to pipe that electricity into the data center, it requires a lot of copper. Copper is the backbone of the data center. It delivers the power and the grid connections. It's -- there's no way that a data center can deliver enhanced compute power for AI without copper wiring. And I think there is a potential here for it to drive significant volume. I mean silver as well. Silver also has high-performance uses. -- around its chip packaging, connectors and switches within the actual rack and within the data center itself. But I think copper here from a volume standpoint and where we are in terms of timing and how energy is such a critical focus is an area that we're watching very closely. So let's go to the next slide and take a look at copper pricing. And here, just taking a look at Anglo American, hopper expectations have been on the rise this year. And I wonder if there's more revisions that are coming into the pipeline as we look out to 2027, 2028, I think -- the Street is probably trying to get their head around what the direction of travel is going to be how sales volume and production are going to shake out as these new data centers come online. And I think you can see it pretty clearly from 2025 to 2026, 2026 to 2027, and it will be interesting to see what ratchets it up further. And where we could continue to see maybe outsized expectations starting to hit. And then if you could go to the next slide, I'm going to move it forward and pass it over to Shari, our guest speaker to take us into a broader look at how the capital markets are experiencing this.

Yes. Thanks so much. And yes, Shari, we wanted to start with you and get a sense for -- your mentioned that a lot of -- a lot of the GenAI companies are eying IPOs later this year. The SpaceX IPO obviously generated a lot of hype and Anthropic has started setting up meetings with Wall Street bankers, ahead of a possible October IPO. We've got openAI in the wings. How are you thinking about these mega IPOs and what they say about the health of the IPO market?

Yes. Thanks for the question, Sarah, and thank you all for having me today. So I think 1 thing that's really important to understand is these mega IPOs, they are important signals, but I don't think the perfect proxies for the entire market. They do act as market bellwethers, right? And they are providing very valuable data points. So think investor appetite, valuation discipline, and risk tolerance. And so companies like SpaceX and leading AI firms, they do attract outsized attention, but their scale and their market position make them unique. So I think it's important for companies to view them as indicators of sentiment rather than direct templates for the broader IPO market. And in terms of the health of the market, we're definitely seeing a healthy market, but it is still extremely selective. So there's clearly been a recovery in IPO activity, but it's still nothing like what we saw in 2021. Investors are really rewarding quality, profitability pathways and really operational maturity rather than just simply growth at any cost. And so I think the thing that companies in this space need to remember is, there is extremely strong demand, but it's concentrated around AI, digital infrastructure, certain health care sectors and fintech with other areas are seeing secular growth drivers. So I guess what I would say is that mega IPOs are definitely telling us the market is open, but it's not open for everyone because investors are being highly selective. And so they're rewarding companies that can combine scale, strong fundamentals and really a compelling long-term growth story.

Interesting. And just to follow up on that. Some of these GenAI companies have been raising huge sums -- just huge sums as private companies as they make this switch to publicly traded companies. Do you foresee any new challenges as they become accountable to shareholders or changes that they have to make?

Yes, definitely. I mean I would say the level of scrutiny changes overnight once you go from private to public. And so private companies, they generally have much greater flexibility in how they communicate performance and strategy. But once they're public, management teams are often facing quarter-by-quarter accountability from the shareholders, the analysts, the regulators, the media, right? There are so many stakeholders that are going to be focused on them. And it really just requires a much higher level of operational rigor. So if you think about expectations around forecasting and execution, they become much more demanding. There's definitely going to be heightened pressure for AI companies to prove the ROI. I think governance becomes a very strategic differentiator and honestly, maintaining growth while they're public is probably going to be 1 of the more difficult asks, right, of a newly public company compared to when it was private. And I would say what they need to remember is going public is not the finish line. It's really the beginning of the new level of accountability. And so the ones that are going to be successful are the ones that can care their innovation and growth with strong governance, transparency and frankly, consistent execution.

Interesting, right. So kind of stability as opposed to bursts of innovation are interesting. Iuri, what are the risks to growth and innovation in the global economy? Has over investment in AI left little fundraising for other software equipment or biotech markets.

Yes. Thanks, Sarah. I'm not sure if the question is -- so I would say -- I would not say there is little funding left for other endeavors, I think, there is always money to fund something. I would say the willingness to fund software. I'm not sure -- I'm not an expert on biotech. I don't know much what's happening in biotech, maybe shares more in the IPO market, I think it's becoming pretty exciting there. But I would say the willingness to fund software and also, for example, fintech and other areas that are non-AI is very low now. This is happening in private markets, but private markets often take cues from public markets. And we've seen that a lot of the software -- software companies in public markets are not creating at valuations that would make private investors salivate for -- take -- to eventually take this company's public. maybe a lot of the software companies in public markets, they can be a good value investment -- a value investment, but certainly not a growth investor -- certainly at a growth investment for VCs for venture capitalists, which they're looking for -- mostly for new technologies that can grow -- that can grow a lot. So if you look at public markets, there is definitely a rotation that has taken place. Money has been moving into AI names, the infrastructure and I think Melissa can talk more about this in Memory, that is for sure. And software has suffered than -- my view is that probably it will continue to suffer because there is this -- it's not only the low growth that we've published some articles that showcasing or from the data from Capital IQ that growth, while it has not suffered in software, it's not accelerating. So it stays sort of locked into 10%, 13% range. And that's definitely for a lot of growth investors, that's definitely not something that you want fund, you don't want to fund now like a 10%, 13%, you want to fund something that can grow like 50%, 60%. So you have -- and -- the low growth, you also have, in addition to low growth, you also have this narrative that it's going to be disrupted by AI. And unfortunately, you don't have the growth rate kind of disputing that fact, at least for now, you don't have it sort of proving it that AI is disruptive but you also don't have it that it's confirming that it's not a disruptive force. So we have this double whammy hitting these areas. And I'm not sure all of the result for disruption system software like Microsoft, SAP, Salesforce. These are hard to rip out from your system. So they basically become embedded in their system, it's very hard to rip them out. So probably we're going to build on top of them rather than taking them out completely. And -- so -- and in private markets, the blood bath in software that has happened in public markets. In private markets, it's the same thing and probably even worse. -- in VC, we see investments, they're looking at, they want to fund the future. And as you can see, there are very few people thinking software is the future now. And a lot of money is being found within to AI hardware and space tech.

Right. So it's not -- the way to think about it is not that AI as kind of stopping up all of the money available. It's more that it's providing the different options for that selectivity that Shari mentioned where investors are choosing what you're betting on growth.

Yes, exactly.

Perfect. We had another question come in from the audience. Iuri, I think you would be able to answer it based on some of your discussions with investment bankers, but -- we had a question about these companies require -- the audience ever is mentioning the hyperscalers. These companies require subcontractors to put in the investment, but they don't have the same credit quality of the hyperscalers. How do these hyperscalers expect the downstream supply chain to fund these projects?

Yes, a very good question. And I think I'm not an expert in that, but basically based from my discussions with a lot of the investment bankers, especially in the data centers space. So even if you are downstream and we don't have like any quality or credit quality, if you have a contract that is coming from the hyperscalers who is coming from someone that has good credit quality and they say, Look, we are going to be our client, and you can show that to the bank or to the lender, then you can borrow money to finance that project. You are basically a good credit. But if you don't have a hyperscaler as a customer or your -- potential customers are not good credit, then this becomes a little bit more difficult downstream. And I would say the financeability of project -- of these projects in downstream of AI and subcontracting very much depends on who your clients are, whether our clients are good credit and they can vouch for you with the actual contracts that they say, if you deliver this, you're going to get this amount.

Shari, many AI and high-growth companies have been able to stay private longer than ever before. What are the factors that ultimately push a company to transition from private capital to public markets?

Yes, -- that's a great question, Sara. And I think what we're seeing is that access to capital is not really the primary reason for going public because as we just heard, right, today's leading private companies, they have access to unprecedented levels of private funding, whether it's from venture capital, private equity, sovereign wealth funds, right, and crossover investors. So what I'm seeing is that the decision to go public, it's more driven by strategic considerations really more so than just raising cash. And so I think companies are asking whether the public markets are going to help them accelerate growth, enhance their credibility, right, and to provide them to maybe broader access to capital over the long term. So I think what's really important is the scale and maturity of these companies. Certainly, that's going to require potentially a different capital structure, right? So even in today's environment, there does come a point where a company needs, whether it's liquidity or currency or just that visibility that the public markets can provide. And so we definitely see IPOs creating these opportunities for companies and frankly, many large state companies, private companies are choosing to go public because it's really like the next logical phase of their growth. And so I think the thing to maybe keep in mind is that the question isn't really can the company stay private longer because I think it often can given the funding that's available to them. But really, the real question that they're asking themselves is when do the benefits of going public start to outweigh the flexibility that they have as they remain private. And I think those are the ones that we're seeing, starting to get ready like well long before they need to make that decision because they're taking advantage of the optionality that the private markets give them today while evaluating the benefits of entering into the public markets.

Right. And we are seeing the SEC try and push through some changes that would lower the reporting burdens or make it easier to raise money once you're a publicly traded company without having to wait that first year period and kind of make it easier for companies to go public and encourage that -- make IPOs great again like -- great. Well, Melissa, I think you are on the line. We can't see you right now, but I think we can hear you. How should public market investors evaluate GenAI companies with significant capital needs, especially when private valuations remain high.