Coatue Management makes the bull case for AI

Continuing my series on artificial intelligence ("AI") from last Friday and Monday...

Philippe Laffont, founder of Coatue Management, has been very bullish (and very right) on tech for more than a decade – and, in particular, AI in recent years. As a result, Coatue has grown to become one of the largest hedge funds in the world.

In light of this track record, I always carefully evaluate the presentations that Coatue makes public – the most recent of which, a Public Markets Update, was released on October 16. In it, Coatue makes the bull case for AI.

But first, to its credit, it lays out the bear case point by point...

First, the leading AI companies are too big:

Capital expenditures ("capex") are higher than during the dot-com boom and are projected to grow even more:

Corporate AI adoption is slowing down:

Data-center growth, while still high, is declining from its 2023 high:

And, lastly, there's confusion around AI revenues, as the leaders all seem to be funding one another:

In summary, here's Coatue's "scorecard" for AI's bear case:

Now, let's look at Coatue's rebuttal for the bear case and its bull case for AI...

It notes that there have been plenty of long-term investment cycles that weren't bubbles:

Coatue argues that AI has had massive adoption so far, yet it's still early in its journey compared with historical tech innovations:

And though capex is growing, it's being funded with operating cash flow:

As for valuation, Coatue argues that price-to-earnings (P/E) multiples are nowhere near dot-com levels, despite being expanded:

Looking at today's seven largest tech stocks, Coatue notes that their valuations are lower than the top seven in 1999:

Coatue then uses Microsoft as an example of potential cost savings due to AI. According to the slide below, if the top 50 tech companies reduced their headcount by 6%, they would save a combined $75 billion of annual labor costs:

Coatue projects that in the next five to 10 years, AI companies will grow revenues to $1.9 trillion and earnings before interest and taxes ("EBIT") to $850 billion. This would generate a 20% return on invested capital ("ROIC"):

In summary, here's the updated scorecard with AI's bull case:

Thank you to Coatue for the insightful presentation!

I'll repeat my conclusion from Monday: I'm not sure if all this AI spending is a wasteful bubble, but I'll continue to keep track of news and developments in the space. If I come to a definitive conclusion, I'll let my readers know.

In the meantime, I'm hedging my bets.

Best regards,

Whitney

P.S. I welcome your feedback – send me an e-mail by clicking here.