3 reasons why Google's Gemini could be the big bogeyman of the AI trade

• New research lays out the threats Google's Gemini poses to the AI trade.
• Tom Essaye, founder and president of the Sevens Report, is worried about Gemini taking market share from ChatGPT.
• He argues overall that Gemini changed how investors view spending on AI from hyperscalers.

While Anthropic's Claude AI has snatched headlines recently for disrupting the software industry, one researcher says there's perhaps an even bigger bogeyman lurking in tech.

Tom Essaye, founder and president of the Sevens Report, says Google's Gemini threatens major potential disruptions to how investors currently see major AI firms.

In a note to clients on Tuesday, Essaye highlighted three risks posed by Gemini, in particular its November update.

The first is that it could take market share from OpenAI's ChatGPT. That, in turn, could hurt OpenAi's ability to deliver on the $1 trillion in spending it has promised to firms like Nvidia, he said.

Second, the fact that Google used its own chips to build Gemini could undermine the importance of large semiconductor providers.

"The reason that Nvidia, Broadcom, Taiwan Semi and others have exploded in recent years was because of insatiable demand for their semiconductor chips, as they are necessary to build out LLMs," Essaye wrote. "Google making their own chips implies demand for chips from NVDA, AVGO and TSMC may be less than expected. That means less earnings growth and a lower multiple for semiconductor stocks."

That leads to the third point: since Gemini is so effective and was cheaper to produce than other leading chatbots, investors are holding spending levels from hyperscalers to a higher degree of scrutiny, Essaye said.

"If Google can make Gemini as good as ChatGPT on its own chips, then others likely can as well. The fear is that AI becomes commoditized, making trillions of dollars in AI infrastructure investment foolish," Essaye wrote.

"Put plainly, Gemini broke the idea that all money spent on AI was 'good' money that would result in earnings growth," he continued. "Instead, it ushered in scrutiny to AI capex spending and that altered the paradigm AI/tech stocks existed in. Practically, that means it's no longer the case that the company that spends the most on AI infrastructure 'wins' and we can see that in the market reaction to the collapse of mega-cap free cash flow."