Aswath Damodaran: Big Tech Has No Idea How AI Pays Off

23:08Thank you. code at midnight or strategizing your next business move, Cloud extends your thinking to tackle the problems that matter. You can delegate tasks of all sizes from tedious bug fixes to new feature ideas, then handle the other work while Cloud runs in the background. Cloud has checkpoints that let you save progress and roll back to any previous state instantly. Plus, you can set up workflows to run on a schedule such as daily reports, weekly summaries, and recurring data pools that can help your day-to-day operations. For problems worth solving, get started with Claude at Claude.ai slash markets.

23:45That's Claude.ai slash markets. And check out Claude Pro, which includes access to all of the features mentioned in today's episode. Claude.ai slash markets.

24:01Support for the show comes from BCX, the public ticker for private tech. For generations, American companies have moved the world forward through their ingenuity and determination. And for generations, everyday Americans could be a part of that journey through perhaps the greatest innovation of all, the U.S. stock market. It didn't matter whether you were a factory worker in Detroit or a farmer in Omaha. Anyone could own a piece of the great American companies. But now that's changed. Today, our most innovative companies are staying private rather than going public. The result is that everyday Americans are excluded from investing and getting left further behind while a select few reap all the benefits.

25:02Until now. at bcx.com. This is a paid sponsorship.

25:10When you need to build up your team to handle the growing chaos at work, use Indeed Sponsored Jobs. It gives your job post the boost it needs to be seen and helps reach people with the right skills, certifications, and more. Spend less time searching and more time actually interviewing candidates who check all your boxes. Listeners of this show will get a$75 sponsored job credit at indeed.com slash podcast. That's indeed.com slash podcast. Terms and conditions apply. Need a hiring hero? This is a job for Indeed-sponsored jobs.

25:44We're back with Prof G Markets. It seems as though these big tech companies were looking for a growth engine. They saw AI happen. They invested huge amounts of money into basically two companies, OpenAI and Anthropic. Then OpenAI and Anthropic turned around and sent the money back to them, buying all of the compute from the data centers that they're building. And that is now how they grow. And that's what we're seeing when the numbers explode. That, to me, signals something very unhealthy that we are. And I thought about you a lot when I was looking at these earnings, the idea of the mature company versus the young company.

26:29And it seems as though these companies are trying to sort of artificially inject this Botox into themselves to pretend that they're young again. Is that not what's kind of happening here with big tech?

26:40Aswath Damodaran:They are middle-aged companies. And I've been saying that for a while for the Mag-7. Middle age is not bad. They're in great shape. They make a lot of money. They're good middle-aged companies. But you're right. Nobody wants to be a middle-aged company, especially these companies, their history of growth. And there are two things that drove them into AI. One, of course, is greed, the fact that there's a big market and they can find growth there. But I think you can't underestimate the fear factor, the fear of being left behind, of history books saying Alphabet got into AI, but Meta was slow to join in.

27:14Aswath Damodaran:You can almost see that playing in the way they talk and the way they invest, is they don't want to be pointed to as the company that's not keeping up with everybody else. There's an element of the emperor's new clothes here, right? Which is, you know, we talk about AI, it's going to be a big market, we all buy into it, and they kind of hang out with the crowd where this is accepted wisdom. You know, the conviction that AI is going to be a huge market is deeply embedded, you know? And I think when that's deeply embedded, you don't want to be the company or the CEO of the company. And I put right to the top here, the CEO of the company that falls behind.

27:53Aswath Damodaran:And I think that's a big part of what you're seeing in this race to spending is not that there is a belief that they're going to make money, but the worry that they will be left behind in this race and be the company that didn't catch that race. I mean, we often learn the wrong lessons from looking at history. A lot of chip companies look at NVIDIA and they say, if only we'd been like NVIDIA, think of how much money we could have made in the AI chip business. And I think that the NVIDIA lesson for a lot of companies is if you bet big on a growth business and it works out, you're going to be this insanely valuable company.

28:36Aswath Damodaran:But that's betting. That's not investing. You can't run a company betting on the odds that you have right now. And collectively, that's why I think they're going to, collectively, I think they're overinvesting. I don't even think there's a question. The question is whether there'll be one big win and lots of big losers or how big the losers will be or how this business will shake out. With the worry that somebody outside the space who didn't invest like they did could be a late entrant into space. But because, you know, it's like, you know, every time I take the train from San Diego to L.A., I curse the fact that U.S.

29:15Aswath Damodaran:railroads were built 100 years before everybody else because they were built for trains that could go only 25 miles an hour. And by the time you got around to putting faster speed, you couldn't take. My worry is you're building AR architecture and you might find out three years from now that you've been building for the wrong kind of product and service. And that's the charitable view you can take of Apple is they have the money to spend if they wanted to. And maybe they'd rather wait for this turmoil to clear up and people to find that end game before they jump in with tens of billions. But I think, I mean, uneasy is the word I would use.

29:56Aswath Damodaran:Worried might be, you know, might be the follow up to that, but I'm uneasy about the way they're spending money. And as somebody who owns five of the max seven, I don't own NVIDIA anymore or Tesla anymore. I see the intra-company both investing and financing. That's the other side of this, right? In addition to the intra-company operations, there's intra-company financing with NVIDIA often financing customers who buy from them. And intra-company investing, something that when I first started valuing companies, I I used to be happy to be able to value US companies because crossholdings were not common here.

30:35Aswath Damodaran:I hated valuing family group companies in Asia because to value one company, I had to value four companies. I worry about the fact that to value any of these companies in the near future, I'll have to value three companies. To value Microsoft, I'll have to value OpenAI because of the big position it has. So the intra-company investing, financing, and operations creates noise in the process. noise is just a fancy word for it. We don't know what's going on under the surface because of the intercompany stuff. On this point, when we look at the net income for Amazon and Google, both of which exploded, almost tripled in Amazon's case, 85 % of its net income, Amazon's, was attributable to its paper gains, its unrealized gains in their stake in Anthropic and OpenAI.

31:25And for Google, looking at their stakes in SpaceX and Anthropic, that number was 87%. So their earnings have been massively inflated by these gains in these AI startups, which they haven't even actually realized. So we don't even know if those valuations are fair or even make sense. We don't know how they were valued either. And this is something I pointed out on Twitter recently. As a result, their PE multiples have been massively skewed. They've come way, way down, somewhere below 20 times earnings because their earnings have exploded. And I worry that that means that the metric has been compromised by AI because it looks cheap, but you're not getting the full story.

32:07We made like our own little adjustment where we kind of stripped out the AI startup gains and you pointed out that actually we need to be including their value in the numerator. Could you talk a little bit about how we can actually value these companies now that they're so in bed with the AI frontier labs.

32:25Aswath Damodaran:When I talk about pricing metrics in class, PE, EV to EBITDA, EV to sales, I mean, the whole, there are dozens of multiples. One of the first rules I start with is a consistency rule, which is what's in your numerator should be what's in your denominator. So let me give you an example, you know, enterprise value to EBITDA, widely used in capital intensive businesses. What's In the numerator is the market value of equity and that net of cash. And people say, why do we net cash out? Because the income from cash is not part of EBITDA. And then I point to a danger with EBITDA when you have crossholdings.

33:01Aswath Damodaran:When you have crossholdings, here's the problem. If you have minority holdings in other companies, your market value reflects those holdings. Because the market knows you own 30 % of this very valuable company. So what happens is your market cap inflates, your enterprise value is higher, but your EBITDA does not include the earnings from that crossholding because it's viewed as non-operating. It shows up below the EBITDA line. So I say, even with enterprise value to EBITDA, you should be netting out the value of the crossholdings because otherwise you think these companies are more expensive than they are because the EV is inflated by including them, but the EBITDA does include it.

33:44Aswath Damodaran:And people say, that's a pain in the neck. And I say, welcome to reality. A lot of the reason people like to use multiples, it's the shortcut, right? You're not asking the in-depth questions you need to ask to value companies. I need a shortcut. And that shortcut historically has been the PE ratio. But for 20 years, I've argued the PE ratio is the most dangerous of all multiples to use because it's this mess, right? There's a numerator that's just the market value of equity, and a denominator includes everything. It includes interest income from cash. What if you're making a huge interest income from cash and you're including it, and that's part of your denominator?

34:26Aswath Damodaran:You're mixing up a business with a cash holding, and in this case, a cross-holding, and you're trying to come up with a consolidated multiple. So the lesson I think that you get by looking at the Google and the alphabet is don't trust net income. Net income is a deadly number at these companies because of the mess that goes into it. Climb the income statement. Look at the operating margins. Look at the interest expense. And because in a sense, you worry about things like financial expenses and other income. But separate the two. The operating income is going to tell you what the operating business of these companies are doing.

35:02Aswath Damodaran:that the rest of the stuff is telling you what the other investments are. Now, I'm surprised to see the marking up. I mean, because on the Amazon income statement, it says gain from sale of asset as opposed to the marking up component. The reason I'm surprised is when you hold an investment for trading, you have to show the marking up or marking down. SoftBank is a classic the example. When you hold an investment as a strategic investment, as an investment that's going to be part of your business in the long term, you generally don't do that. You hold that original value and any income you show will be the actual income or loss from that holding.

35:44Aswath Damodaran:That's what happened with Microsoft. So I am confused about what the accounting is. And if the accounting is they're holding at these companies as trading investments, that's a very revealing statement. Because you told me this investment in open AI was because you wanted to build the AI business in the long term, not because you wanted to make money like a venture capitalist by buying open AI at a low price and selling at a high price. So again, it goes back to this, once you create crossholdings, you create these follow-up questions. What's the motive? Why are you doing it? And I think that's what I mean about transparency.

36:20Aswath Damodaran:Tell me what the end game here is. What is it that you're hoping to get from an anthropic investment or an open AI investment? And frame it in terms of that end business, that this will give you an advantage on that AI product and service business. I'm willing to listen. But don't tell me you're doing it because you want to make money, because you're not a trader. You shouldn't be doing this if your objective is to just make money on another player in the AI space. But if all of Wall Street were as rigorous as you, then maybe we'd be okay. But I think the trouble is that people like shortcuts.

36:53People don't want to do all of the homework that you're describing. So they just look at the numbers. They go, oh, it's okay. The revenue exploded. The net income is up.

37:01Aswath Damodaran:I don't think it's rigor particularly that keeps it apart. It's the fact that you're required as an analyst to react in real time. I'm glad that I'm not there at 4.30 after an earnings call where somebody says, what do you think about that earnings call? I mean, I need a little time to digest what's in that statement. I need to look at the footnotes. I need to see the breakdown. But I think we live in a world where instantaneous reaction is required of us. It's part of your job. So I cut them some slack on what they're doing, but I faith that eventually markets kind of figure it out. And I think that that's going to be the end game is, Now, I did strip out the Google and the Amazon earnings from the effect on earnings.

37:50Aswath Damodaran:And they're pretty good quarters, even without it. And I think it made more sense for them to say, this is what we did without RA. And that's what I meant about separating what's happening with AI from everything else, is I don't think markets would punish them if they did that. I think markets would actually reward them for transparency. I mean, it's one of the reasons I think Jeff Bezos was cut so much slack by the market for so long at Amazon because he was open about what he was doing. He said, look, I'm building, I mean, I call it the field of dream story, which is if we build it, they will come.

38:26Aswath Damodaran:He was open about the fact that Amazon in its early years was building revenues, that margins would look terrible, that they'd give away shipping for free because they had an end game. He brought people into the endgame. And it's that belief that allowed Amazon to do what it did. So that's why I said if there's one company in this mix that should have experience having gone through this before, it's Amazon. So I'm going to get my cues on whether Amazon starts to become transparent earlier than the rest, because I would expect them to. So there has never been this level of capex in emerging technology that didn't ultimately result in a fairly serious correction, if not a crash.

39:11Whether it's the railroads, the electric grid, you know, the highways, whatever, the steel in the ground, infrastructure in 99, whatever, you know, there's always a correction. And also, to be fair, the technology and many of the companies survive that correction and go on to be big winners. But the thing that gave me the sense that we might be closer to that correction moment than further is when Meta or when Zuckerberg announced they're trying to sell their compute. And the same with Musk. And my sense is that, I mean, if you look at it at the beginning of the year, the narrative was around compute scarcity.

39:54And now both Musk and Zuckerberg are trying to spin it as look at the premium we're getting for the infrastructure we built. And what I see in that is that the AI demand curve has been vastly overestimated. And now you have essentially hundreds of billions, if not trillions of dollars in CapEx, all going to only two sources of demand creation, open AI and anthropic. It feels like we have all of a sudden pivoted from a supply crisis to potentially a demand crisis. Your thoughts?

40:25Aswath Damodaran:When I was looking at the SpaceX prospectors and I noticed that they were making more money by leasing out their data centers to others, in this case, Anthropic. than they were making. No, I thought it was actually seriously at odds with the AI story they were telling in the prospectus of this huge market, 28 trillion. And I think in the aggregate, what you're pointing to is the fact that you're making more money by selling into the AI architecture space. And I include LLMs in this. Then from talking about AI product and services is very revealing. It tells me that you're not as confident as you claim to be, that there's going to be this huge, if you were really confident that there was going to be a huge market, you wouldn't want to lease the space out to who could be potential competitors in that market.

41:15Aswath Damodaran:So the fact that you're doing it, I think is a sign that at least for the near term, you don't have as much faith as you claim to have that AI is going to be as big as it is going to be. I take that as one data point. And then I take the fact that the amount of tokens being consumed from Chinese LLMs or AI infrastructure companies has, the data I've said, it's gone from 8 % share in January of 25 to somewhere above 50 % now. It feels as if the cracks are really beginning to emerge in the whole narrative here and that China is potentially engaging in AI dumping, trying to do to our market what they tried to do to our steel market 30 or 40 years ago.

42:01and doing in kind of 20 weeks to Silicon Valley what Japan did to Detroit over 20 years. Am I overstating the threat of these inexpensive LLMs out of China?

42:14Aswath Damodaran:No, I think China is just ahead of the game in seeing that the AI product and service market, this mythical market we keep talking about, is going to bifurcate. There's going to be a premium component of the market, primarily business products and services, which is high margin. And there's going to be a big component of the market, which is going to be a low margin, big scale market. And China is clearly putting its stakes and saying that market we're going to go after because we're equipped to go after it. So I think China in many ways is taking a look at that endgame playing out. And I think the real question is in that endgame.

42:51Aswath Damodaran:So let's play it out. Let's suppose the endgame, the AI product and service market turns out to be looked. Let's play along with the AI optimists. Let's say it's$6 billion,$8 billion,$9 billion, even$10 billion. That by itself doesn't create valuable companies because you haven't told me much about the business models that will be used to generate money in that market. If 90 % of that market is low margin, large scale, you could be a$10 trillion market. But the companies in that market are not going to make much money on those trillions of dollars because your margins are going to be single digit margins.

43:26Aswath Damodaran:Now, one of the most revealing components of the Anthropic success story was how much it costs Anthropic to deliver the products and services that they charge$6 ,000 an hour for. This isn't software where the unit economics are amazing. The unit economics are struggling in a business that's still evolving. I think the question, though, is what's the catalyst that's going to create a major correction? This might be one of those things where you get multiple catalysts and corrections along the way, rather than a big time, you know, like the dot-com bus. Unlike the dot-com bus, something that happens, staggered pain.

44:11Aswath Damodaran:I'm not sure which is worse, to get the pain in one go and clean up and move on. Or a staggered pain where individual companies get into trouble and markets go through these cycles of correction and hope. where you come back a little bit, then you have a correction again. But I don't see an individual catalyst that's big enough for a moment where people say, oh my God, the AI market is not going to be as lucrative as we thought it was. Because it seems like every time you get something that has the potential to do it, there's still money on the sidelines that jumps in and says, we need to be in AI because everybody else needs to be in AI.

44:51Aswath Damodaran:Now, I think that, you know, last week after the blow up with situation, when you had all that selling of forced selling, the next day you wake up and there's a 10 % jump in all of the stocks. Clearly money coming in saying, we've never been in AI. We need to be there because everybody else is there. I think I know whether this is being accentuated by social media and the awareness of other people make money. I don't know. But that factor still seems to be strong enough to overcome the catalyst effect. But at some point in time, the catalyst effects are going to overwhelm that momentum effect.

45:33We'll be right back. And for even more markets content, sign up for our newsletter at profgmarkets.com.

46:11That's Indeed.com slash podcast. Terms and conditions apply. Need a hiring hero? This is a job for Indeed-sponsored jobs.

46:40Sponsors set up required compatibility and availability varies 18+. Hear that? That's now Crispy and McCrispy Strips meeting creamy Caesar sauce. Sounds extra crispy. Caesar sauce at McDonald's for a limited time.

47:04We're back with ProfG Markets. Do you think that Open Air, you mentioned the unit economics, Anthropik charging all of this money, but then they spend way more money delivering that product. Do you think that OpenAI and Anthropik ever figure out the unit economics? Like, I'm just going along with, I guess they will, but I don't know why I should believe that.

47:25Aswath Damodaran:The way AI is set up right now, I don't think there's going to be that much give on the unit economics in the near term, right? You still have to build, I mean, the physical infrastructure seem so expensive, unless you can figure out a way to build data centers at one-tenth the cost, right? This is not the kind of investment where scaling up is going to help you that much. You have to figure out how, you know, so none of the elements are easily going to bend to economies of scale argument. Maybe I don't know enough about AI. Maybe they have some secret sauce that's going to allow them to do this.

48:02Aswath Damodaran:But I don't see it. I think every time I open Google and AI helps me out there, it seems like a marginal cost is being created somewhere along the way that I'm not seeing. And that marginal cost is not decreasing because tens of millions of people are using Google at the same time because each surge seems to provide an additional cost. So as I said, I am not enough of an expert in AI to see where these economies of scale will come from. But I don't see them yet. I don't see anything in the architecture that bends easily to scale where you can say the costs are going to decrease just because they get bigger.

48:41I don't see it either. And I feel as though we're just being told to trust that it's going to work out and trust that the unit economics will make sense eventually. But if they don't, the whole thing collapses.

48:54Aswath Damodaran:On the premium side, it starts to shrink. Maybe not collapse, but shrink. McKinsey might be willing to pay$9 ,000 or$90 ,000 and$500 ,000 for an AI agent. There would be premium products where you can charge a premium price even over the high cost, but it'll mean that that end market is going to be more premium product. The economies of scale argument might work better in that lower margin market where you don't need NVIDIA chips. You don't need expensive data centers. And the reason I say that is I see a lot of stuff that I saw 10 years ago that was labeled as machine learning or look at this macro we built for Excel.

49:38Aswath Damodaran:I see the same stuff today marketed as AI. And my question is, why do you need any of this AI? You don't need data centers. You don't need NVIDIA chips, you could do this with the traditional computing power and without the access to data. That's the part of AI that I think is going to be the scalable part. We have low margins, but the scale takes care of it. So it's not that the AI product and service market will not exist, but it'll become almost primarily a mass market, low margin business. And that's why the architecture you're building might not be right for that. It might be too much for the premium part of the business where you need these high-end chips and data centers to feed those products.

50:24We're describing a lot of AI anxiety. And as you can tell, I'm pretty anxious about this myself. How much of this anxiety, in your view, is priced in right now? I get the sense that it's somewhat priced in, certainly priced in in the case of Meta, in my view, perhaps not the others. What do you make of these valuations? Do you think that the markets are telling us that they see what we're saying?

50:50Aswath Damodaran:They seem to see it, and then they seem to forget it, right? You take the meta example, right? Over the last week, it's made up about 70 % of what it lost in the previous six months. So it's not like the lessons are sticking because, you know, all you seem to need is some other distraction along the way. And that's why for the moment, at least, the catalysts are not working because they have a temporary effect. One company gets hurt, but you're not seeing it ripple into the other companies. It seems to be company specific and time specific. So I think that collectively, I think anxiety kind of ebbs and flows, but it doesn't seem to be at a level where it permeates into permanent pricing changes yet.

51:38Aswath Damodaran:And I think maybe that reflects the fact that those who are anxious are in the wrong. So I'm always open to the possibility that maybe we're missing a really big story. Maybe Leo was right about this being the ultimate winner. It's going to happen in 2027. And I'm always going to leave that door open because I've learned that you can't ignore somebody just because you disagree with them. I have to be willing to listen. So I try my best to read as much as I can from the AI optimist. I'm looking for a story that explains economies of scale. But so far, the story still seems to be focused on fuzzy end games and how great an AI agent has worked in an individual business.

52:22Aswath Damodaran:I'm not seeing the aggregate numbers from any of these stories that lead me to say, OK, there's something here that I should be taking a closer look at. So it's going to be a race between whether those stories come into play or whether the the skepticism builds up to a point where people stop believing. So are you comfortable with current valuations of big tech? Microsoft, Amazon, Google, Meta will leave Apple aside because they're not getting into AI. Are you comfortable with them, these valuations, or are they too volatile to even have an opinion? I can live with them, and it's because of my framing.

52:56Aswath Damodaran:I frame them based on what I paid for them. I paid for them a long time. I know this sounds irrational, but if we keep comparing the price to something, that I could have got it for six months ago, a year ago. So I'm willing to accept 20 % right down in those investments and accept it as part of the long-term costs and benefits. Now, the reason I do it is, if I think there's a shakeout in the AI space, these companies will be impacted. But the lesser companies in the space are, I mean, none of these companies have net debt ratios that are beyond the single digits. Their debt is completely manageable.

53:33Aswath Damodaran:And I did net-to-debt EBITDA for all of these companies, one and a half times EBITDA. So basically, next year, they stopped investing in AI. A year and a half of EBITDA from their regular businesses would pay off the debt. So debt is not my concern of these companies. But there are a whole host of lesser companies where debt is a much bigger component. There, an AI meltdown in the story will be catastrophic. Now, just as Amazon got hurt after the dot-com bus, but it's the best thing that happened to them because it wiped out all of their dot-com competition, in many ways, the Mag-7 might be, you know, this is a very sinister view of this whole thing.

54:14Aswath Damodaran:Maybe they're wishing for an AI correction. They'll be punished, but the rest of their competition will be decimated. Now, and remember, OpenAI and Anthropic can't survive on their cash flows either. So maybe if you were looking for a story with villains that knew more than they did, maybe this is the end game for them. Is there hoping for an AI shakeout where they can come in and pick up the pieces at bargain basement prices? Because they're going to survive. I mean, I don't have worries about failure rates for these companies. I just worry about their prudence in what they're doing in terms of AI investing.

54:53There's been a lot of concern around – you have$1.4 billion in disclosed debt, but the debt you don't see is now bigger than the debt you can see. So, for example, Meta is carrying$420 billion of off-book versus$140 billion on-book. But I don't entirely know if that's a feature, not a bug. Are these companies taking advantage of their credibility in the marketplace to offload from their shareholders some risk? Or is this just an accounting trick to create opacity around the actual amount of debt they have?

55:32Aswath Damodaran:Now, I'd be interested to see what the recourse on that debt is. If you're lending money on a data center that Meta is a player in, and the debt has recourse only against that data center's revenues and assets, then you're not going, I mean, in a sense, as a Meta shareholder, it's clearly not something I want to see happen, but it's not something that's going to impact me. No, I would be, you know, again, I want to go back and look at the accounting rules as to what happens when you take debt that's off balance sheet debt, where there is recourse against the parent company and whether you can get away not revealing that as part of your debt.

56:18Aswath Damodaran:and maybe there's this iceberg of debt that you're not seeing underneath. That could be, no. But I think that even, I mean, let's bring the recourse debt in then and let's see. I mean, I'd like to see full disclosure of that debt that's not on the balance sheet because even then I would wager it's three times. We're not talking about heavily levered companies in the sense of companies that are, you know, that are going to be dragged down by the failure of AI. But I might be wrong on that. Maybe I need to do more of my homework digging through that debt. But that would require some bending, perhaps even breaking of accounting rules to be able to get away with it.

57:05Aswath Damodaran:So I'll do another read of the footnotes to see if there's something in there. But at least for me, the worry with the MAG-7 is not so much the debt, but the investment paying off, whether there's enough for a return. The worry with lesser AI is whether they can make it to the other side. And their worst case scenario is that AI turns out to be an incredibly big market, but they don't make it there. They fail because the debt comes due and they have to sell themselves to one of these other companies at a fraction of what they should be charging. And that's a very real possibility in this space.

57:41Aswath Damodaran:And if it does happen, there's going to be serious side costs for the rest of us, because debt going down is always going to create side costs. Have you looked at OpenAI and Anthropics? What very little we know of their financials, and would you ever value those companies? I will, because I valued SpaceX with, you know, let's face it, 80 % of SpaceX value, at least the numbers, the story was about XAI. So it's an XAI story embedded in a space launch company. So when the prospectus comes out, I plan to value them ahead of the IPA. And it'll be interesting to see as you move from SpaceX, whether some of the shine has come off the story because of what's happened at SpaceX, where people are saying, you know, maybe the Anthropic IPO is not going to be a trillion.

58:34Aswath Damodaran:Maybe it'll be$800 billion. Maybe OpenAI is not going to get the price it wanted. So I have a feeling that they're revisiting the story because what they did with XAI was too sloppy. It really didn't stick. And they need to get there, you know. And I think there you're going to look for more specifics because, you know, just telling me you're a great LLM or you have amazing agents, AI agents doesn't do it for me. You need to show evidence that this is actually sticking at a business level, that you're making money. There, I need to see the unit economics and evidence that there are economies of scale you can point to.

59:11Aswath Damodaran:This is what it cost us two years ago, a year ago, this year. Because that's how you back up an economies of scale story. Just don't give me the words, show me the numbers. Would you ever value OpenAI without the full story? Would you ever undertake that? Because it seems as though, and you pointed this out in our exchange on Twitter, like we need to put the value in the numerator, but that kind of means valuing open AI. In order to value big tech correctly, I need to value open AI, but how can I value open AI? Because I know nothing about it. Would you ever try to do it anyway? Absolutely. I mean, in a sense, you have no choice but to tell the full story.

59:52Aswath Damodaran:The question is, is it a story you're entirely making up based on clues you're getting elsewhere, which is what I did with XAI. There was no story in the prospectus. There were just numbers thrown out of thin air. There was no story from the management of what they planned to do. So I had to write the whole story. That's always going to create more uncertainty. So it's not a question of whether you can tell a full story, but what's the basis for the story you're telling? And the case of OpenAI, unless they fill in the blanks, I am coming up with a story based on my limited understanding of AI.

1:00:31Aswath Damodaran:So I'll give you an economy of scale story that's not very strong. And I might say your costs are not, you might disagree with it. But part of the reason I think it's critical that investors flesh out their full story is then companies are forced to respond, right? So if open AI feels that they have true economies of scale and the story being pushed into the valuation is there are no economies of scale. The costs are not going to go down. Then show me the data that you have that tells me that I'm wrong. Because as long as we let these companies get away with these diffused, total addressable markets, trust me, and you don't even tell a story, use a pricing metric and say it's okay because there's a big market out there, there's no incentive on the part of companies to tell the fuller story.

1:01:22Aswath Damodaran:So I think I will try to tell a full story, but I'll be open about the fact that much of the story is my story based on little strands that I pulled out of different places, some from the company, some from people who know AI a lot better than me. But I'll always tell a full story and people will take issue with me saying, your story is wrong. And I say, absolutely, I know it's wrong, But what's the counter? Where is the counter narrative? You can tell me a narrative is wrong, but you have to beat it with a counter narrative. And that's good because it extracts the counter narratives from not just the company, but from other investors who disagree with me.

1:02:00But it seems as though there is almost no price discovery in the Frontier Lab world at all, except for, and this is how we'll end, SpaceX, where as soon as it went public, It went up and then it came crashing way down, cut in half within a couple of months, maybe less than a couple of months. Let's just get your reactions to SpaceX, what happened there.

1:02:27Aswath Damodaran:And I think in many ways, it shows you the power of hype, the power of momentum and how social media is added to that momentum factor, which is, I mean, this is the ultimate social media experiment because you think of Grok and X and basically you've got this and social media is like riding the tiger. It's great when you're on the back of the tiger, but sooner or later you're going to slip up and end up being its meal. So I think it shows you both the upside and the downside of social media driving prices. But I think as more numbers come out of the company is the earnings, much as we take issue with the earnings we're seeing from the Mag 7.

1:03:13Aswath Damodaran:Now, we extract information from it that is useful in kind of finessing our story. So once you go public, that is something that these companies will face is now, in addition to telling the story, you've got numbers that come out and either your story is consistent with your own numbers or people are going to look at the inconsistency. So, no, I think that there are more tests coming, and I think for SpaceX and these other companies as they go public, it'll be an experiment worth watching. It'll show up in the market press. I'm fascinated with 1999 because I think it was the year Ed was born. That's true.

1:03:50But also, we remember that, Aswath. And I understand, you know, things are different this time, you know, in quotes. But it just feels eerily reminiscent. First, the B2C guys took a hit. It feels like OpenAI is under real fire around its business model right now. And then everyone said, okay, no problem. We'll go to B2B. Everyone piled into Anthropic, which had greater share in the enterprise market. Then when that didn't live up to its expectations, they started going after the infrastructure guys. It feels like we are midway through the exact same cycle with the dominoes beginning to fall. This feels more similar than not to me to the 99 and then ultimately the 2000 implosion.

1:04:38Where do you see the parallels or not from 99?

1:04:42Aswath Damodaran:No two corrections ever work out the same way. So, I mean, part of me doesn't want to see a correction because of what it'll do to every portfolio in the U.S. But part of me just, you know, from a market observer standpoint, I am interested and I'm much more aware now than I was in 2001 of the catalyst that created. Because in 2001, if you remember, it wasn't a single catalyst. It was just a collection of small things happening. Now, as you said, not even dominoes falling, but trees falling in the forest. And eventually, you wake up and say, oh my God, half the forest is gone. So I'm keeping tabs as I can, whether it's on the investor's side, we see a meltdown of a hedge fund shutting down because it made too much of a bet in AI.

1:05:34Aswath Damodaran:Or on the company's side, where you see companies stepping back from the brink and saying, we screwed up, we're going to write off that. Now, we still haven't seen a major AI CapEx write-off from a company yet, because that'd be the ultimate admission of, hey, guys, we screwed up. We've admitted we screwed up and we're not going to do this anymore. Whether that'll happen after the correction or before the correction or whether it'll trigger the correction. So I keep my eyes on accounting revisions and restructuring charges and look at what's being written off, because that might start to give us an indication of how this correction will play out.

1:06:20Aswath Damodaran is the Kirshner Family Chair in Finance Education and Professor of Finance at NYU's Stern School of Business, where he teaches corporate finance and valuation. You can read his research on his blog, Musings on Markets. Aswath, thank you so much for joining us today. And to our live audience, thank you for tuning in. We will see you next time. Thanks, Aswath. Thank you. This episode was produced by Claire Miller and Alison Weiss and engineered by Benjamin Spencer. Our video editor is Jorge Carty. Our research team is Dan Chalon, Kristen O'Donoghue and Mia Silverio. Jake McPherson is our social producer.

1:06:57Drew Burrows is our technical director, and Catherine Dillon is our executive producer. Thank you for listening to Prof G Markets from Prof G Media. If you liked what you heard, give us a follow and join us for a fresh take on markets on Monday.

1:07:28Reunion As the world turns And the dark lights In love, love, love

1:07:52Close your eyes, exhale,

1:07:56Aswath Damodaran:Feel your body relax and let go of whatever you're carrying today. Well, I'm letting go of the worry that I wouldn't get my new contacts in time for this class. I got them delivered free from 1-800-CONTACTS. Oh my gosh, they're so fast. And breathe. Oh, sorry. I almost couldn't breathe when I saw the discount they gave me on my first order. Oh, sorry. Namaste. Visit 1-800-CONTACTS.com today to save on your first order. 1-800-CONTACTS. summer's full of reasons to look your best Tecovis has everything you need to show up in style their western boots are handcrafted in over 200 steps by hand with premium calhide and exotic leathers stop by your local Tecovis store for the full experience free drinks, boot shines, and complimentary boot branding to make your pair truly yours their team is there to help you find exactly what fits your summer and of course, you can always stop by Tecovis.com Tecovis, forever west