We Asked Jeremy Grantham Why AI Won’t Boost Profits — and What It Will Do Instead

Why It Matters

Understanding AI’s limited effect on profit margins helps investors avoid overpaying for hype and focus on valuation, while policymakers gauge the broader economic implications of growing tech monopolies.

Key Takeaways

• AI becomes a baseline cost, not a profit driver.
• Concentrated tech giants will capture most AI-driven gains.
• Historical mean reversion suggests early AI adopters enjoy temporary margins.
• Increased monopoly risk may slow overall GDP growth.
• Investors should focus on valuation cycles, not hype.

Summary

The interview centers on Jeremy Grantham’s assessment that artificial intelligence will not lift aggregate corporate profit margins; instead, it will become another routine expense for businesses. Grantham argues that the shift from a monopoly‑free era to a fiercely competitive landscape means AI will be widely adopted, eroding any temporary advantage.

He highlights that early adopters may enjoy fleeting margin expansion, but as the technology diffuses, profit margins revert to historical norms. The discussion ties this pattern to mean‑reversion across asset classes and firms, noting that the “Mag 7” tech giants are already operating as near‑monopolies, allowing them to set prices and capture outsized returns while the broader economy sees slower GDP growth.

Grantham cites past cycles—such as the mini‑computer boom—to illustrate how new tools initially boost returns before becoming a cost of doing business. He warns that AI’s complexity fuels divergent predictions, yet the fundamental economic impact mirrors previous innovations: a short‑lived profit surge followed by normalization.

For investors, the takeaway is to treat AI hype with skepticism, prioritize valuation discipline, and anticipate that any productivity gains will be broadly shared, limiting upside for most companies while reinforcing concentration at the top.

Original Description

Jeremy Grantham joins Excess Returns to discuss The Making of a Permabear, mean reversion, market bubbles, AI, the Magnificent 7, and the long-term lessons investors can take from his career at GMO. We cover why he rejects the simple “permabear” label, how he thinks about valuation and bubbles, why AI may be both transformative and dangerous for investors, and why long-term thinking is so hard but so essential.

The Making of a Permabear: The Perils of Long-term Investing in a Short-term World

https://amzn.to/3RqutdW

GMO

https://www.gmo.com/americas/

Topics covered:

* Why Jeremy Grantham thinks the “permabear” label misses the point

* The difference between being generally bearish and making a true “abandon ship” call

* Mean reversion, valuation cycles, and why history still matters for investors

* Why monopoly power helped reshape U.S. profit margins and market concentration

* How AI could turn today’s monopoly winners into brutal competitors

* Why new technology often becomes a cost of doing business rather than a permanent profit boost

* How Grantham defines bubbles using two-sigma market events

* Lessons from Japan, the dot-com bubble, the housing bubble, and the 2021 speculative peak

* Why institutional investors struggle to stick with value strategies during bubbles

* The role of purpose, climate risk, toxicity, and long-term thinking in Grantham’s later career

* The one lesson Grantham would teach ordinary investors about pessimism, realism, and time horizons

Timestamps:

00:00 Jeremy Grantham on unpleasant news and long-term investing

04:18 Reinvesting when terrified in 2009

08:43 Why Grantham told investors to abandon ship in 2008

10:28 Mean reversion and why history matters

14:00 Monopoly power, the Mag 7, and rising market concentration

17:14 Why AI is important but impossible to forecast

20:21 AI as a cost of doing business

21:24 From monopoly profits to brutal AI competition

24:05 How investors should think about valuation mean reversion

27:00 Why high returns on capital should eventually attract competition

29:47 How Grantham defines a market bubble

33:00 Japan’s extreme bubble and GMO’s zero weight decision

34:19 The dot-com bubble and the pain of being early

38:00 Grantham’s bubble warning signal in 2021

41:35 Whether today’s market is showing classic bubble behavior

43:00 QuantumScape, meme stocks, and speculative excess

46:35 How ChatGPT interrupted the 2022 bear market

49:12 Investor behavior and the cost of underperforming in a bubble

55:00 Purpose, philanthropy, climate risk, and useful work

01:01:03 The one lesson Grantham would teach average investors