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Berkshire Hathaway<\/a> CEO Greg Abel discussed with CNBC’s Becky Quick on Wednesday the conglomerate’s massive investment in Google parent Alphabet<\/a>, calling the tech giant a “significant player” in artificial intelligence.<\/p>\n Abel said Berkshire has clear view of the impacts that AI is having across its portfolio of companies, and that Google’s position relative to the emerging technology is strong.<\/p>\n “We have a lot of visibility from within our companies as to how we’re using AI, what type of benefits it’s delivering, so that brought incremental interest, and then we saw Google as a significant player,” he told Quick.<\/p>\n Berkshire took a $10 billion stake in Google 15 months ago at a 6.5% discount, Abel said.<\/p>\n “They hadn’t set the size, but recommended that we consider 10 billion. And Warren and I discussed the size. We discussed the size of discount, and I’d recommended 6.5% discount, and we were comfortable with that,” Abel said. “Then ultimately consummated the transaction.”<\/p>\n Berkshire added a total of $17 billion of Alphabet shares in the second quarter, making it the third-largest holding in\u00a0Berkshire Hathaway’s equity portfolio<\/a>, according to the company’s\u00a0Q2 portfolio snapshot<\/a>\u00a0filed with the Securities and Exchange Commission in August.<\/p>\n Stock Chart IconStock chart icon GOOGL year to date<\/p>\n As of the company’s last filing, Berkshire owns around 106 million of Alphabet’s Class A and Class C shares, currently worth about $36.6 billion. Alphabet purchases were the largest addition to Berkshire’s portfolio of the quarter, but Berkshire also bet big on\u00a0Delta Air Lines<\/a>, increasing that position by 44%, or roughly $1.6 billion.<\/p>\n Google is one of the five so-called hyperscalers executing huge capital expenditures to expand their computing power to run AI, along with Microsoft<\/a>, Meta<\/a>, Amazon<\/a> and Oracle<\/a>. Global hyperscaler capex for 2026 is estimated to be around $1 trillion, according to investment bank Goldman Sachs, but there is significant variance within estimates.<\/p>\n “Estimates indicate that the commonly cited forecast for hyperscaler capex of $794 billion likely understates the total amount of global AI capex by around $200 billion. At the same time, the $794 billion figure likely overstates the amount of US investment in AI by $200 billion,” Goldman Sachs researchers wrote in an August analysis.<\/p>\n The question for investors is to what extent these huge investments will pay off and over what time frame.<\/p>\n AI computing workloads are generally split up into the two categories of algorithmic training based on large datasets and inference, or query response.<\/p>\n “A prolonged training-dominant phase extends the ROI timeline as CapEx and R&D continue to be deployed in advance of broad monetization,” Goldman Sachs researchers wrote in May<\/a>.<\/p>\n![\"hide](\"https:\/\/static-redesign.cnbcfm.com\/dist\/a54b41835a8b60db28c2.svg\")
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