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In the third-quarter earnings season for US stocks, the real main event isn't whose PowerPoint looks prettiest, but whether AI can actually make money.
Microsoft, Google, Amazon, and other tech giants are about to report results, and the market's attention is once again fixed on their AI businesses. Over the past two years, any company with even a little connection to artificial intelligence seemed to get an automatic boost to its valuation. The problem is that GPUs cost money, data centers cost money, electricity costs money, and engineers are even more expensive. Before AI has brought in profits, capital expenditures have already come knocking.
It's like opening a milk tea shop: you spend millions on renovations, buy top-of-the-line equipment, and promise to take over the whole city. But what investors really want to know is: How many cups can you sell each day? When will you break even?
When looking at AI giants' earnings, don't just focus on how fast their cloud businesses are growing. Also look at whether orders can turn into revenue, whether profit margins are under pressure, and whether capital expenditure growth is exceeding what cash flow can support.
If revenue is growing strongly and customer demand is solid, the spending may be like building a highway. But if investment keeps increasing while commercial returns remain elusive, it's time to worry that the highway will be finished but no one will pass through the toll booths.
The AI story is certainly not over, but the stock market isn't a sci-fi movie. What ultimately determines valuations isn't how intelligent the models are, but whether the business model can make money.
After all, artificial intelligence can generate answers, but investors don't want to be left with the bill for capital expenditures.
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