The US investment in AI seems to be surging
The US investment in AI seems to be surging,
But apart from the well-known large science and technology enterprises, the investment expenditure of the local government and other enterprises is actually relatively limited. According to Harvard University economist Jason Furman, the current capital expenditure on AI in the United States is about 1% of GDP, significantly lower than the historical investment frenzy, such as railway expansion in the 1980s (the related CAPEX accounted for about 6% of GDP), electrification reform in the 1920s (3 percent), Science Networks and Broadband Investment in the 2000s (5 percent). From this perspective, if AI is truly a once-in-a-century innovation, the current US investment might be "inadequate" rather than "over-due".
Furthermore, the US's past investments in railways, electricity, and broadband have been mainly effective domestically; by contrast, the AI programs currently owned by US companies and data centers located in the US have a greater potential for growth, theoretically, to reach and serve users around the world.
As the latest research report from JPMorgan Chase points out, if compared to the railway revolution in the 19th century and the power revolution in the 20th century, the investment cycle of this AI revolution will last at least 20 to 30 years, and it is just starting. The bank estimates that as a "super cycle," the total investment of the US from 2026 to 2030 will reach $5 trillion, with the GDP ratio rising to about 3%.
Overall, from the perspective of valuation, application, cash flow, investment volume, etc., the current AI frenzy can be called "hot", while there may be signs of excessive excitement in some areas (which has led to a sharp decline in the stock market), but it may not necessarily be said that a large-scale "bubble" has been formed. From a longer-term perspective, the AI cycle may still be in its infancy and may not be comparable to the same amount as the dot-com "crazy period" in 2000. It is believed that it is still too early to talk about "bubble bursting".
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