This episode of Excess Returns features GMO’s Tom Hancock on how to think about AI as an investment opportunity and what truly defines “quality” in today’s market. The conversation breaks down the AI value chain, challenges common assumptions about where value will accrue, and ties it all back to building durable portfolios in a rapidly changing technological landscape.

Tom walks through his “Hype vs High Conviction” framework, explaining why identifying the right layer of the AI ecosystem may matter more than simply betting on the theme itself, and why balance sheets, durability, and capital allocation remain critical even in the most exciting growth environments.

Hype vs High Convictionhttps://www.gmo.com/americas/research-library/hype-vs-high-conviction_insights/

Topics Covered:

Why AI may be the most important investment decision today
The four-layer AI stack: applications, LLMs, hyperscalers, and infrastructure
Why investors confuse secular trends with investable opportunities
Following the money through the AI value chain
The hidden risks of investing lower in the stack
Why today’s tech leaders differ from the dot-com era
Growth vs maintenance capex and what it means for AI economics
Why software may be more resilient than markets think
How GMO defines “quality” and why it matters in volatile markets
Portfolio construction: where GMO is investing (and avoiding) in AI

Timestamps:
00:00 Intro and framing the AI investment debate
00:00:55 Tom Hancock background and focus on quality investing
00:02:00 What investors are getting wrong about AI
00:03:23 Breaking down the four layers of the AI ecosystem
00:06:45 Applications vs infrastructure: where value may accrue
00:08:45 Why predicting AI winners is still difficult
00:11:00 Following the cash flows through the AI stack
00:13:00 Why AI funding is more stable than past tech bubbles
00:16:00 Big Tech strategy differences and capital allocation decisions
00:17:34 Are today’s tech companies higher quality than in 1999?
00:19:00 Growth vs maintenance capex and implications for Nvidia and others
00:22:00 Depreciation, chip lifecycles, and hidden risks in capex assumptions
00:24:00 Capital intensity vs quality: when heavy investment is a feature
00:27:00 Why incumbents may benefit most from AI
00:28:30 Risks in the LLM layer and potential commoditization
00:30:10 Software disruption fears: overdone or justified?
00:34:06 Defining “quality” in investing
00:36:00 Balance sheets vs return on capital
00:38:32 Why GMO sold Oracle and the risks of leverage
00:40:18 What happens if AI spending slows down
00:41:35 Where the biggest risks are in the AI stack
00:44:26 Where GMO is positioned vs the S&P 500
00:48:00 How new ideas enter a quality portfolio
00:51:00 Sell discipline and portfolio turnover
00:53:00 International vs US quality investing

The Risk at the End of the Whip | GMO’s Tom Hancock on Finding Conviction Amid the AI Hype

Excess Returns