Key Takeaways
- Major investors are shifting from overvalued AI stocks to potential next winners
- Strategy mirrors successful dotcom-era approach of rotating before peak
- Focus on software, robotics, Asian tech and infrastructure plays
- Concerns about AI bubble building despite strong earnings
Major investors are deploying a dotcom-era playbook to navigate AI market risks, rotating from hyped stocks to potential next-in-line winners while avoiding direct bets against the booming sector. As Nvidia’s valuation surges past $4 trillion and U.S. stocks hit records, professionals seek gains without excessive exposure to the most exuberant AI names.
“What we are doing is what worked from 1998 to 2000,” revealed Francesco Sandrini, multi-asset head at Europe’s largest asset manager Amundi. He noted signs of irrational exuberance but expects tech enthusiasm to continue, targeting “the highest growth opportunities that so far the market had failed to spot” in software, robotics and Asian tech.
Riding the AI Wave Like Dotcom Veterans
Simon Edelsten, CIO at Goshawk Asset Management, warns: “The odds of this being a bust are very high because you’ve got companies spending trillions fighting for the same market that does not yet exist.” The former telecom IPO banker sees parallels with 1999 and favors IT consultants and Japanese robotics as secondary beneficiaries.
Historical data supports this approach. Hedge funds during the dotcom bubble outperformed by 4.5% quarterly from 1998-2000 by skillfully rotating between sectors rather than betting against the trend. “There were good profits to be made for the fleet of foot even during 2000 when the top came,” Edelsten noted.
His analogy captures the strategy: “When someone strikes gold, buy the local hardware store where the prospectors will buy all their shovels.”
Creative Risk Management in AI Investing
Investors are finding innovative ways to benefit from AI infrastructure spending without direct exposure to hyperscalers. Fidelity’s Becky Qin favors uranium plays, anticipating nuclear energy demand from power-hungry AI data centers.
Carmignac’s Kevin Thozet is taking profits on Magnificent Seven stocks and building positions in companies like Taiwan’s Gudeng Precision, which supplies delivery boxes to AI chipmakers including TSMC .
However, concerns about overcapacity loom. “In any new technological paradigm we don’t get from A to B without excesses along the way,” cautioned Pictet’s Arun Sai, who sees “the building blocks of a bubble” despite strong earnings from Microsoft, Amazon and Alphabet.
Diverging Approaches to AI Risk
Not all investors embrace the rotational strategy. Janus Henderson’s Oliver Blackbourn hedges U.S. tech with European and healthcare assets, fearing an AI crash could drag down the entire U.S. economy.
He acknowledges the timing challenge: “We’re in 1999 until the bubble pops,” noting that identifying peaks is only possible in hindsight. This divergence highlights the ongoing debate about how best to navigate what many see as an AI investment bubble with real underlying value.
