Published by Global Banking & Finance Review®
Posted on October 24, 2025
5 min readLast updated: January 21, 2026
Add as preferred source on GoogleInvestors are using 1990s strategies to navigate AI market risks, shifting from hyped stocks to potential winners while managing risks effectively.
By Naomi Rovnick
LONDON (Reuters) -Major investors, spooked by AI exuberance yet wary of betting against it, are shifting from hyped-up stocks into potential next-in-line winners, reviving a strategy from the 1990s dotcom era that helped some sidestep the crash.
As U.S. stocks have hit successive records and AI chipmaker Nvidia's valuation has surged beyond $4 trillion, professional investors have been trying to find ways to make money from the bull market while avoiding excessive risk.
Some are looking back to the 1990s internet boom, which spread from startups to telecoms and tech, and where hedge funds rode the wave by flipping out of highly-valued stocks before they peaked and picking others that had room to rise.
"What we are doing is what worked from 1998 to 2000," said Francesco Sandrini, multi-asset head and Italy CIO at Europe’s largest asset manager Amundi.
He highlighted signs of irrational exuberance on Wall Street, such as frenzied trading in risky options pegged to the share prices of big AI stocks. But he said he expected the new tech enthusiasm to continue and hoped to bank gains via bets on reasonably valued assets that might rally next.
Sandrini said this involved trying to find "the highest growth opportunities that so far the market had failed to spot", with moves into software groups, robotics and Asian tech.
Other investors also expected to edge out of Wall Street's Magnificent Seven stocks after shares in Nvidia more than tripled in two years, but want to keep their diversification within the AI sphere.
ASSET MANAGERS NEED TO BE NIMBLE TO RIDE THE WAVE
"The odds of this (AI boom) being a bust are very high because you've got companies spending trillions and all fighting for the same market that does not yet exist," said Goshawk Asset Management CIO Simon Edelsten, who worked on telecom IPOs at stockbroker Dresdner Kleinwort Benson in London in 1999.
He expected the next phase of AI fever to spread from Nvidia and others like Microsoft and Alphabet into related sectors.
Timing the phases of a bubble has historically been a way to play it without the risk of trying to call the peak too early.
A study by economists Markus Brunnermeir and Stefan Nagel showed that hedge funds mostly did not bet against the dotcom bubble, but rode it skillfully enough to beat the market by about 4.5% per quarter from 1998-2000 and avoid the worst of the downturn.
They shed high-priced internet stocks in time to recycle profits into others before they caught the attention of less sophisticated investors.
"There were good profits to be made for the fleet of foot even during 2000 when the top came," Edelsten at Goshawk said, adding the current market environment was similar to 1999.
He favoured IT consultants and Japanese robotics groups that can potentially pick up revenues from AI heavyweights, in what he said was the typical chronology of a market gold rush.
"When someone strikes gold, (you) buy the local hardware store where the prospectors will buy all their shovels."
INVESTORS TRY TO STAY IN AI WITHOUT EXCESSIVE RISK
Investors are also attempting to benefit from the trillions of dollars so-called hyperscalers such as Amazon, Microsoft and Alphabet are committing to AI data centres and advanced chips without taking on more direct exposure to these companies.
Fidelity International multi-asset manager Becky Qin said uranium was her favoured new AI trade because power-hungry AI data centres could gobble up nuclear energy.
Kevin Thozet, investment committee member at asset manager Carmignac, was taking profits on Magnificent Seven stocks and building up a position in Taiwan's Gudeng Precision, which makes delivery boxes for AI chipmakers including TSMC.
Asset managers are also concerned that the rush to build data centres could result in overcapacity, as in the fiber-optic cable boom in the telecoms industry.
"In any new technological paradigm we don't get from A to B without excesses along the way," said Pictet Asset Management senior multi-asset strategist Arun Sai.
Even though top AI stocks like Microsoft, Amazon, and Alphabet are being powered by strong earnings, he still sees "the building blocks of a bubble" and favours Chinese stocks as a hedge if rapid AI advancements in China sap Wall Street's AI enthusiasm.
Some investors, though, do not favour this relative value approach to AI investing as a way to mitigate future losses.
Oliver Blackbourn, portfolio manager at Janus Henderson, said he was hedging his U.S. tech positions with European and healthcare assets lest an AI stock crash takes the U.S. economy down with it.
He said it was impossible to forecast how long the AI craze would roll on because calling the peak was usually only possible with hindsight.
"We're in 1999 until the bubble pops."
(Reporting by Naomi Rovnick; editing by Dhara Ranasinghe and Jane Merriman)
Artificial intelligence (AI) refers to the simulation of human intelligence in machines programmed to think and learn. It encompasses various technologies, including machine learning and natural language processing, to perform tasks that typically require human intelligence.
An investment portfolio is a collection of financial assets such as stocks, bonds, and cash equivalents held by an individual or institution. It is designed to achieve specific investment goals while managing risk.
Hedging is an investment strategy used to reduce the risk of adverse price movements in an asset. It often involves taking an offsetting position in a related security or derivative to protect against potential losses.
Financial markets are platforms where buyers and sellers engage in the trade of financial assets, such as stocks, bonds, currencies, and derivatives. They facilitate the allocation of resources and risk management in the economy.
Innovation in finance refers to the introduction of new ideas, products, or processes that improve financial services and products. This can include advancements in technology, new financial instruments, or improved customer service methods.
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