Episode summary
The AI Investment Boom: When Will It Pay Off?
Exchanges (Goldman Sachs)
· · Hosts: Alison Nathan, George Lee · Guests: Jim Covello
Summary
Jim Covello says the AI buildout has moved further away from clear economic returns over the last two years, even as the technology itself has improved and consumer adoption has been strong. He argues that most users are still on free products, so the real test is enterprise deployment, where companies are spending heavily before the economics are proven. In his view, the biggest economic winners so far have been semiconductor companies, while customers higher up the chain are still struggling to show profit from the spend.
George Lee agrees the payoff hurdle is high, but is more optimistic that AI can create net new economic activity rather than just displace existing profit pools. He points to faster model revenue growth than the Cloud era and says enterprise adoption is taking time because AI is novel, probabilistic, and requires new control and orchestration layers. Both speakers see coding as the clearest current use case, while broader enterprise returns remain uncertain.
Covello also highlights a gap between C-suite expectations and worker experience, saying surveys show less productivity gain than promised. He argues that if enterprises do not make or save money from AI, the market will eventually have to question the scale of capex and the concentration of returns in semis.
Key takeaways
- Jim Covello says AI economics have gotten worse, not better, because spending has risen faster than demonstrable enterprise returns.
- George Lee says the payoff from AI may come from creating new economic activity, but the hill to climb is still very high.
- Covello argues that semiconductor companies have captured most of the economic value so far, unlike prior tech cycles where customers eventually benefited too.
- Both speakers see coding as the strongest current AI use case, while other enterprise domains remain harder to prove.
- Covello says third-party surveys show a persistent gap between C-suite expectations and line-worker productivity gains.
Notable quotes
“at some point you got to make money. You make investments in a business so that you can generate returns and make money”
“And we've gotten further away from that over the last couple years instead of closer to it”
“all of the value, all of the economic value has continued to accrue to the semiconductor companies”
“you have to move beyond the traditional notion of disruption of existing profit pools”
How the episode opens
Look, at some point you got to make money. You make investments in a business so that you can generate returns and make money. And we've gotten further away from that over the last couple years instead of closer to it.
That doesn't mean it's never going to happen. It just means the stakes are higher. Welcome to another episode of Goldman Sachs Exchanges.
I'm Allison Nathan and I'm here with George Lee, co-head of the Goldman Sachs Global Institute. Together we're co-hosting a series of episodes exploring the rise of AI and everything it could mean for companies, investors, and economies. George, great to see you again.
Great to be here. And this should be fun, George, because today we are talking to someone who at least in the past several years has really disagreed a fair amount, I think, or taken a different view than you on AI. Our guest is Jim Covello, head of global equity research here at Goldman Sachs.
And again, you've had many debates with Jim about this topic. Well, first of all, it's great to have Jim here. He is both a great friend and a great thinker.
And while we differ on some matters related to AI, actually there's much we agree on. And it's been very fun to have this dialogue over multiple years. Yeah, for sure.
So, welcome Jim. Yeah, no, it's great to be here. Thank you.
And I agree. Geroge is everything that makes Goldman Sachs great to me. And it's been incredible going on this journey with you.
And here we are again. Here we are again. Exactly.
So, Jim, as we mentioned, a couple of years ago you came out with what I would characterize as a pretty skeptical, somewhat out of consensus view of generative AI.
From the episode’s captions: roughly the first two minutes, lightly cleaned. Keep watching on YouTube →
Topics
- ai investment boom
- ai economics
- semiconductor demand
- hyperscalers spending
- enterprise roi
Companies and tickers mentioned
- GS
- Goldman Sachs
Watch the episode
Watch “The AI Investment Boom: When Will It Pay Off?” on YouTube
Summary, takeaways and quote selection by Octagon. Quotes are short excerpts; the full conversation is in the episode.
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