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This essay appears in the Oct. 17, 2026 edition of the Fortune 500 Digest<\/strong> newsletter, which rounds up the headlines driving the week\u2019s most important business news and coverage of Fortune 500 companies. Subscribe to receive it in your inbox every Saturday morning.<\/em><\/p>\n The AI buildout is in full swing, and it\u2019s incredibly expensive.<\/p>\n Between Amazon, Alphabet, Microsoft, and Meta, over $720 billion of capital expenditures is projected to be spent this year, most of it on AI infrastructure, according to analyst estimates compiled by Bloomberg. Alphabet President and Chief Investment Officer Ruth Porat confirmed to me this week at the Fortune Most Powerful Women Summit that Alphabet intends to spend \u201csignificantly more\u201d in 2027.\u00a0<\/p>\n This year, Alphabet said it expects capital expenditures of $195 billion to $205 billion. That\u2019s more than double the $91.4 billion it spent in 2025. When asked whether spending on the buildout has peaked across the industry, Porat said it is still in its early phases relative to the eventual economic value Alphabet thinks AI can drive. \u201cWe do see this as an opportunity that extends for quite some time,\u201d she said.<\/p>\n Increasingly, debt is fueling the AI buildout too. Private credit funds such as Blue Owl, Apollo, and KKR are a growing source: Outstanding private loans to AI-related companies have climbed to more than $200 billion by some estimates. Often, they\u2019re lending to special purpose vehicles and smaller \u201cneocloud\u201d operators rather than to deep-pocketed Big Tech players. Even Alphabet posted negative free cash flow in Q2 for the first time since its 2004 IPO to help fund AI. Its long-term debt was about $98 billion at the end of June, up more than four times the year prior.<\/p>\n Alphabet can afford such costly long-term AI bets\u2014and arguably the bigger risk for it would be not making them. But many less well-capitalized players are vulnerable, and recent shifts may be making them more so.<\/p>\n One of the biggest: Open-weight models, particularly from China, are increasingly taking business and usage from closed models like Anthropic, OpenAI, and Google\u2019s Gemini. New financial figures from Anthropic this week also suggest its growth may have flattened. <\/p>\n This trend led Jefferies\u2019 global head of equity strategy, Chris Wood, to declare that the most likely long-term outcome of the AI boom is massive capital destruction in the U.S., according to Bloomberg. Wood argued that cheaper Chinese open-source models threaten to commoditize large language models, eroding the economics behind America\u2019s AI spending, and that China \u201chas become a technological peer to the U.S. in AI.\u201d<\/p>\n When I recently spoke with one of China\u2019s leading open-weight model developers, Moonshot AI, I learned that 70% of its usage comes from outside China.<\/p>\n I asked Porat directly about Wood\u2019s thesis that much of the money pouring into the U.S. AI race could be destroyed.<\/p>\n \u201cIt\u2019s illogical to say we\u2019re in a capacity-constrained position because there\u2019s such strong demand for the insight in the ability to improve business and government, and yet you can\u2019t drive a return on it,\u201d Porat replied. She also noted that when it comes to the trend toward open-weight models versus closed, she feels AI companies that add differentiated value will find customers paying for their services regardless.<\/p>\n Porat has had a front-row seat to previous bubbles, first as head of Morgan Stanley\u2019s technology banking team during the dot-com era, and later during the 2008 financial crisis, when she helped advise then U.S. Treasury Secretary Hank Paulson. She went on to become Morgan Stanley\u2019s CFO in 2010.<\/p>\n Her takeaway from those periods is that companies using AI to build truly differentiated experiences will win.<\/p>\n \u201cOne of the key lessons from the financial crisis was that you should identify your greatest source of vulnerability early and fortify against it, because you can\u2019t address it in the moment. For banks, it was liquidity. Without liquidity, you couldn\u2019t run a trading operation. Without liquidity, you shut down,\u201d Porat said.\u00a0<\/p>\n \u201cI\u2019ve been asked that question frequently since: What is the greatest source of vulnerability today? I think for all of us across industry, one of the most important elements is innovation in your business. If anyone is connecting with your customers in ways you are not, because they are using AI and you are not, you\u2019re at a competitive disadvantage.\u201d<\/p>\n Yes, she\u2019s talking her book here, and the \u201cjust add more AI\u201d view doesn\u2019t negate the potential systemic economic risk of overbuilding. But it\u2019s also true that AI is not going away and the need for companies to adapt is only going to increase.\u00a0<\/p>\n At Alphabet, Porat indicated that the company will keep investing heavily in AI because of its conviction in the long-term economic upside.<\/p>\n \u201cYou must invest for long term growth,\u201d Porat said. \u201cBy the time you need it, it\u2019s too late to say, OK, now we\u2019re going to start.\u201d <\/p>\n For more, check out my full conversation with Google CIO and President Ruth Porat here.<\/p>\n<\/div>\n\n