Microsoft Is Cited by Both Sides: Testimony for an AI Bubble—or a Rebuttal?
On the same day, Microsoft became the name both sides of the AI debate cited.
On one side, the U.S. Treasury Secretary publicly dismissed the AI-bubble thesis, naming Microsoft, Google, and Meta as drivers of significant revenue growth.
On the other, the Bank of England’s governor warned that asset prices “at some point may undergo a correction,” and noted that these companies are pouring in hundreds of billions of dollars—historically, the leaders often are not the final winners.
Money is also speaking: according to market news, last month the seven major-related ETFs saw the largest single-month inflow on record. Over a ten-year horizon, Microsoft returned about 912%, outperforming the S&P, but far behind Nvidia.
My own judgment leans toward this: the market treats Microsoft as a proxy for whether “AI can deliver,” but its revenue structure, the return cycle of its capital expenditures, and the pure compute-driven narrative are not the same thing.
Anthropic spent $100 million to train 10,000 enterprise-deployment engineers, while Microsoft is effectively “growing” 6,000 people of its own—same bet on talent, but entirely different paths.
If the returns on AI capital expenditures start being questioned quarter by quarter, will Microsoft be the first to be held accountable—or the last?
What remains to be verified is: how much of this ETF inflow is allocation-driven versus momentum-driven (chasing gains).
On the same day, Microsoft became the name both sides of the AI debate cited.
On one side, the U.S. Treasury Secretary publicly dismissed the AI-bubble thesis, naming Microsoft, Google, and Meta as drivers of significant revenue growth.
On the other, the Bank of England’s governor warned that asset prices “at some point may undergo a correction,” and noted that these companies are pouring in hundreds of billions of dollars—historically, the leaders often are not the final winners.
Money is also speaking: according to market news, last month the seven major-related ETFs saw the largest single-month inflow on record. Over a ten-year horizon, Microsoft returned about 912%, outperforming the S&P, but far behind Nvidia.
My own judgment leans toward this: the market treats Microsoft as a proxy for whether “AI can deliver,” but its revenue structure, the return cycle of its capital expenditures, and the pure compute-driven narrative are not the same thing.
Anthropic spent $100 million to train 10,000 enterprise-deployment engineers, while Microsoft is effectively “growing” 6,000 people of its own—same bet on talent, but entirely different paths.
If the returns on AI capital expenditures start being questioned quarter by quarter, will Microsoft be the first to be held accountable—or the last?
What remains to be verified is: how much of this ETF inflow is allocation-driven versus momentum-driven (chasing gains).