Rajiv Jain Reverses Course, Bets on AI and Semiconductors
GQG Partners chairman and CIO Rajiv Jain has reversed his earlier bearish stance on artificial intelligence and shifted three of the firm’s four main funds to overweight technology and semiconductors. The move follows $15.1 billion in client outflows during the first half of 2026, which reduced assets under management from $172.4 billion to $156 billion. Rajiv Jain previously described the AI boom as a “dot-com bubble on steroids” and reduced positions in Nvidia, Alphabet, Amazon and Microsoft. GQG now argues that sustainable computing demand has a longer runway than previously expected. Lower valuations also supported the change: Nvidia’s earnings multiple fell from about 35 times in 2025 to roughly 16–17 times by mid-2026. GQG funded the technology pivot by cutting exposure to utilities and healthcare. The firm remains underweight technology in its emerging-market funds, indicating a selective focus on developed-market technology leaders and semiconductor companies rather than a broad AI trade. For traders, the reversal is a signal that institutional investors may view AI infrastructure as a more durable growth theme, although it also highlights the risks of chasing momentum after a major sector rally.
Neutral
The news is neutral for the cryptocurrency market because it does not involve a cryptocurrency, blockchain project or crypto-specific regulation. Its immediate effect is more likely to be felt in technology equities, especially semiconductors and AI infrastructure. A large asset manager moving back into AI could reinforce risk appetite and support broader growth-stock sentiment. In past periods, strong institutional demand for technology shares has sometimes benefited crypto indirectly through improved liquidity and a greater willingness to hold speculative assets. However, the $15.1 billion in GQG outflows also shows that poor relative performance can trigger rapid reallocations. If the AI trade strengthens, capital could remain concentrated in equities rather than flow into crypto. Conversely, a reversal in AI sentiment or renewed concerns about valuations could produce a wider risk-off move, pressuring both technology stocks and digital assets. Short term, traders should monitor Nasdaq performance, semiconductor earnings, real yields, liquidity and Bitcoin’s correlation with growth assets. Long term, the development supports the narrative that AI infrastructure remains a major institutional investment theme, but it provides no direct fundamental catalyst for BTC, ETH or other tokens. The most appropriate classification is therefore neutral, with potential indirect effects through global risk sentiment.