Episode summary
We Asked a $30 Billion Manager Where AI Profits Will Actually Go
Excess Returns
· · Guests: Tom Hancock
Summary
Tom Hancock argues that AI is a real investment opportunity, but the biggest mistake is treating the whole theme as one trade. He lays out a four-layer AI stack—applications, LLMs, hyperscalers, and infrastructure—and says investors need to ask where revenue, durability, and bargaining power actually sit in the chain. The key point is that revenues are only as durable as the spend from the layer above, so the lower you go, the more dependent you are on someone else’s capex and the less visibility you have into demand.
He says the current boom is meaningfully different from the dot-com era because it is being funded largely by cash-rich strategic buyers like Microsoft and Alphabet rather than debt. That makes it more stable, but not risk-free: spending could slow, some firms may not need their own LLMs, and the market could overestimate how much value accrues to model builders. Hancock is especially cautious on the LLM layer and more constructive on hyperscalers and infrastructure where he sees stronger durability and better balance-sheet support.
More broadly, he defines quality as profitable growth supported by strong balance sheets, durable competitive advantages, and the ability to survive bad times. He says GMO has been willing to own some software names again after the AI selloff, but sold Oracle because its debt load and customer concentration made the business less comfortable to underwrite as a quality holding.
Key takeaways
- Hancock thinks AI should be analyzed by layer, because the economics differ sharply between applications, LLMs, hyperscalers, and infrastructure.
- He says the current AI buildout is safer than the dot-com era because it is funded mainly by Microsoft, Alphabet, and other cash-rich strategics rather than heavy debt.
- He is most cautious on the LLM layer, where he sees too much competition and a real risk of commoditization.
- He prefers businesses with durable revenue, strong balance sheets, and the ability to keep investing through downturns.
- He says Oracle no longer fit GMO’s quality standard because debt and customer concentration made the revenue stream less secure.
- He expects hyperscalers and semiconductor infrastructure to capture more durable value than many application or model-layer names.
Notable quotes
“conflating the idea of here's a big secular trend that's going to grow and it's going to change our lives with exactly which companies”
“The revenues are only as durable as the spend from the person above them who is buying their products”
“Nvidia's revenues are OpenAI's capex and Open AI has the capex to spend because they're getting money from Microsoft”
How the episode opens
I think what investors tend to have trouble with is conflating the idea of here's a big secular trend that's going to grow and it's going to change our lives with exactly which companies that are riding that wave have the differentiated business models. The revenues are only as durable as the spend from the person above them who is buying their products. And as you do get further down the this the layers, you do lose visibility in what's going on above you.
Nvidia's revenues are OpenAI's capex and Open AI has the capex to spend because they're getting money from Microsoft and also from just because they're spending in advance of that revenue. Bad times can happen to anyone. Things happen in the world and a lot of being quality is just being able to keep going through those tough patches.
Tom, welcome to Excess Returns.
Hi, thanks for having me.
You're head of focused equity and a quality portfolio manager at GMO. You spent most of your career there. Um, and your focus is on building concentrated portfolios that consist of highquality businesses.
So, a lot of the conversation today is going to be around this topic of quality investing, what it means, how you define it at GMO. But I thought where we'd start with you is on a topic that is kind of critical to today's market. It's represented in a lot of investors portfolios and even in market cap weighted indices and that's how to think about AI as a investment opportunity.
You recently published a paper titled hype versus high conviction. You could people can download this on GMO's site uh arguing that you know AI may be one of the most important decisions facing equity investors today. So we want to kind of work through that paper with you which was excellent and then I think at the end we'll you know really try to tie back to how you define quality what makes for a durable business in your view and how you construct portfolios that consist of those types of companies.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai value chain
- quality investing
- hype vs high conviction
- ai capex and economics
- portfolio construction
Companies and tickers mentioned
- NVDA
- ORCL
- GMO
- Nvidia
- Oracle
- S&P 500
Watch the episode
Watch “We Asked a $30 Billion Manager Where AI Profits Will Actually Go” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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