Rajiv Jain shifts stance, embraces AI investments after skepticism

Rajiv Jain shifts stance, embraces AI investments after skepticism

The GQG Partners chief who called AI a 'dot-com bubble on steroids' is now overweight tech after $15.1 billion in outflows forced a rethink

Roughly a year after calling the artificial intelligence boom the “dot-com bubble on steroids,” Rajiv Jain has done what fund managers rarely do in public: admitted the market was right and he was wrong.

The chairman and CIO of GQG Partners revealed during the firm’s half-year results call in August 2026 that three of its four main funds have shifted to an overweight position in technology and semiconductors. That’s a full 180 from 2025, when Jain was aggressively dumping Nvidia, Alphabet, and Amazon while trimming Microsoft.

The cost of being early (or just wrong)

The firm bled $15.1 billion in outflows during the first half of 2026. Funds under management dropped from $172.4 billion to $156 billion.

The core problem was straightforward. Jain bet against the most powerful momentum trade in a generation. While GQG was underweight tech, the sector kept posting robust growth. Clients noticed, and they voted with their feet.

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What changed his mind

Jain’s original skepticism wasn’t unreasonable. In 2025, AI spending by hyperscalers was accelerating while revenue generation from AI products remained murky. The gap between capital expenditure and actual monetization looked, to a value-oriented investor, like a classic setup for disappointment.

Two things appear to have shifted the calculus. First, valuations compressed. Nvidia’s earnings multiple fell from around 35x in 2025 to approximately 16-17x by mid-2026. Second, GQG’s management cited revised assessments of sustainable compute demand, concluding that the AI infrastructure buildout has a longer runway than Jain initially believed.

To finance the tech pivot, GQG cut back substantially on utilities and healthcare holdings, which had failed to meet performance expectations.

Analysts on the call were reportedly surprised by the speed of the reversal. Management responded that the decision was backed by detailed bottom-up research rather than a panic reaction to outflows.

The contrarian’s dilemma

GQG isn’t a small shop. At $156 billion in assets, it’s one of the larger active managers globally. When a firm of this size pivots its sector positioning this dramatically, it sends a signal that reverberates beyond its own portfolio.

The semiconductor angle is particularly notable. GQG’s overweight position in semis suggests the firm believes the picks-and-shovels layer of the AI stack has durable economics. With Nvidia’s multiple compressing to the mid-teens, the valuation argument for chipmakers looks materially different than it did 18 months ago.

One wrinkle worth watching: GQG remains underweight technology in its emerging market funds, citing index composition differences. That selective approach suggests this isn’t a blanket “buy everything with a GPU” trade but rather a more targeted bet on developed-market tech leaders.

Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.
Rajiv Jain shifts stance, embraces AI investments after skepticism
Rajiv Jain shifts stance, embraces AI investments after skepticism

The GQG Partners chief who called AI a 'dot-com bubble on steroids' is now overweight tech after $15.1 billion in outflows forced a rethink

Roughly a year after calling the artificial intelligence boom the “dot-com bubble on steroids,” Rajiv Jain has done what fund managers rarely do in public: admitted the market was right and he was wrong.

The chairman and CIO of GQG Partners revealed during the firm’s half-year results call in August 2026 that three of its four main funds have shifted to an overweight position in technology and semiconductors. That’s a full 180 from 2025, when Jain was aggressively dumping Nvidia, Alphabet, and Amazon while trimming Microsoft.

The cost of being early (or just wrong)

The firm bled $15.1 billion in outflows during the first half of 2026. Funds under management dropped from $172.4 billion to $156 billion.

The core problem was straightforward. Jain bet against the most powerful momentum trade in a generation. While GQG was underweight tech, the sector kept posting robust growth. Clients noticed, and they voted with their feet.

Advertisement

What changed his mind

Jain’s original skepticism wasn’t unreasonable. In 2025, AI spending by hyperscalers was accelerating while revenue generation from AI products remained murky. The gap between capital expenditure and actual monetization looked, to a value-oriented investor, like a classic setup for disappointment.

Two things appear to have shifted the calculus. First, valuations compressed. Nvidia’s earnings multiple fell from around 35x in 2025 to approximately 16-17x by mid-2026. Second, GQG’s management cited revised assessments of sustainable compute demand, concluding that the AI infrastructure buildout has a longer runway than Jain initially believed.

To finance the tech pivot, GQG cut back substantially on utilities and healthcare holdings, which had failed to meet performance expectations.

Analysts on the call were reportedly surprised by the speed of the reversal. Management responded that the decision was backed by detailed bottom-up research rather than a panic reaction to outflows.

The contrarian’s dilemma

GQG isn’t a small shop. At $156 billion in assets, it’s one of the larger active managers globally. When a firm of this size pivots its sector positioning this dramatically, it sends a signal that reverberates beyond its own portfolio.

The semiconductor angle is particularly notable. GQG’s overweight position in semis suggests the firm believes the picks-and-shovels layer of the AI stack has durable economics. With Nvidia’s multiple compressing to the mid-teens, the valuation argument for chipmakers looks materially different than it did 18 months ago.

One wrinkle worth watching: GQG remains underweight technology in its emerging market funds, citing index composition differences. That selective approach suggests this isn’t a blanket “buy everything with a GPU” trade but rather a more targeted bet on developed-market tech leaders.

Disclosure: This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our Editorial Policy.