AI’s Transformative Potential – and the Risks of Aggressive Growth Projections

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Chris Davis:

Well, I think in the middle of last year, we published a piece that was really about a value investor lens as you look at this. And so I'll commend that to your attention in terms of when we look at categories of businesses and things like that. But what I'd say at this high 30,000 foot level is that these are sort of our working assumptions in this fast-changing space. One is that it's an economy-wide shift. There's not going to be a lot of areas to hide in. It is going to be an enormous revolution in terms of efficiency and productivity. Think of electricity and the steam engine in terms of just amplifying human labor. This is amplifying human knowledge work. Early adopters in many industries will have a huge advantage because they'll get that cost advantage and be able to gain share fairly quickly. And as I mentioned earlier, this white collar disruption and the rate of change has been accelerating.

I think it's going to create real disadvantages for passive strategies and inflexible strategies. This is a time when the ability to adapt, and I think one of the things that people in the world of private equity are going to realize is the inability to change your mind could end up being very costly. And one massive example of where it's hard to change your mind is in an index. I'd like to point out that Kodak was still in the top third of the S&P 500 when digital camera sales had already surpassed film camera sales. So millions of people knew that film was dead, but the index has to adapt slowly. So you sort of go down with the ship when there's times of disruption. And we think therefore the company specific research, valuation discipline, these are going to be increasingly accretive to investment returns. So those are sort of our assumptions.

Here are the big uncertainties that affect how you look at this as an investor. Is it going to be winner take all or is it going to be an oligopoly? Those have huge differences, obviously in social networks, in things like search algorithms, in office software. Winner take all network effect businesses have very, very different economics than ones where the leader keeps shifting and they're very low switching costs. So we are going to need to watch that very closely. Right now, it's looking like an oligopoly rather than a network effect Metcalfe Law business. Will the returns flow to the users or the providers? You think about the build out of the electric utility grid, huge value to the users, not big utility-like returns for the builders. So again, who is going to get the returns from this spending? Railroads, the returns went to the users, not the builders.

All the capital intensive builders of course went bankrupt. The unemployment implications are very dramatic, and those themselves will raise the regulatory and political responses as well as of course some of the social fears that we're seeing. What will be the returns on the capital spending and what is the systemic risk of misuse? That's obviously something that we're grappling with. And so when you layer up those uncertainties and you think about how blithely investors are making assumptions about being able to identify the winners, we see a lot of risk. And Danton, you put together some data on this that is really worth sharing.

Danton Goei:

Yeah, I think it's important that last point you're talking about the assumptions that investors are putting out there, and a lot of it is around valuation and the growth that is needed to support those very high valuations. And if you look at the historical data, it shows that the likelihood of reaching those thresholds of growth for many years in the future is just very low. So this chart here shows you two lines here. It's the percentage of S&P 500 companies that are able to maintain the blue line, a 10% sales growth, and then the red line, a 20% sales growth. And you can just see that most companies can do it for one year, but even looking out just three or four years in consecutive years, the percentage of companies that are able to achieve that falls dramatically. And then if you think that you think you can maintain that level of growth for a decade, then the percentages are extremely low, 10% for companies maintaining a 10% sales growth for 10 years.

And then at the 20% sales growth, which many companies will likely have to maintain to support their valuations, that falls down to a tiny 2%. So again, kind of cautionary tale there. And then similarly, this chart here just shows you the number of companies that can maintain a very high margin. So growth is one component that is necessary to maintain these high valuations, but the other thing is profitability. And so companies that can maintain a 50% or plus EBIT margin even for a year is just six plus percent, but then maintaining that for consecutive years falls dramatically and you get down to 1% and less than 1% going forward. So very unlikely that any company can grow very rapidly and maintain for very long, very high margins.

And that has huge implications for the valuation of these companies. And then kind of putting the cherry on the bow here of thinking about valuation here, this is one of our favorite quotes. This is Scott McNeely, the CEO of Sun Microsystems. This is a quote of his in 2002. So a couple of years after the peak of the dot-com boom in the 1990s, he's talking about how at 10 times revenues, and this is him talking about his stock, "To give you a 10-year payback, I have to pay you 100% of revenues for 10 straight years in dividends." And that assumes that his shareholders agree with that, that he has zero cost of goods sold, which is impossible for a computer company. It assumes zero expenses, which given he had 39,000 employees, also very hard, assuming that he pays no taxes and that as investors, we pay no taxes on our dividends, which he likes to, tongue-in-cheek stays highly illegal, and also that he'll have zero R&D even though he is a tech company.

And having done that, would any of you like to buy my stock at 64, which is what it peaked at in late 2000. Do you realize how ridiculous these basic assumptions are? You don't need any transparency, you don't need any footnotes. What were you thinking? And he's talking about this in 2002, so two years later, and at the end of 2002, his stock was below five, so a 90% plus drop in a couple of years. And just the basic math never made sense based on those assumptions, and he's just calling out Wall Street. Of course, he wasn't saying this in 2000, but this is after the fact. And he has a very good point that he clearly was looking at the stock market and could see that it was out of sync, out of touch with reality and the reality of the business.

Chris Davis:

But it's amazing how convinced people were in 2000 that they knew the winners. They were convinced that Cisco, AOL, Yahoo, those were the certain winners of the internet. And in the same way people are convinced that Anthropic, OpenAI are the winners now, and they may be. We are open-minded. We spend time visiting these companies. We understand and study the competitive landscape, but it just is amazing the complacency reflected in the data that Danton shared, but also just that complete ignorance of when you have these revolutionary technologies, this certainty at this stage is so misplaced.

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