Prominent US Stock Market Influencer: AI Investment Craze Needs to Beware of Four Major Risks, Low PE Does Not Signify Stable Structure

June 3rd: US stock market KOL Herman Jin (@ShanghaoJin) published a post yesterday breaking down four key risks tied to the ongoing AI investment frenzy, per Jin’s analysis. He outlined four critical areas of concern: At the micro-company level, seemingly flawless operating scenarios can easily foster overconfidence; ample liquidity is currently available, but central banks have limited tools to control it effectively; disruptions to the semiconductor supply chain could spiral out of control, pushing capital expenditure costs sharply higher; and slowing revenue growth for AI models from players like Anthropic and OpenAI may shake hyperscalers’ (Microsoft, Google, Amazon, Meta, etc.) expectations around capital spending. Jin emphasized that demand risks at the AI model end—specifically for firms such as Anthropic and OpenAI—are the most worthy of attention and the most straightforward indicator to track. While today’s AI bull market appears to have low price-to-earnings (PE) ratios and minimal froth, the reality is that model revenue must maintain rapid, high-speed growth to justify the massive capital expenditures hyperscalers are pouring in. If model revenue growth slows, “de-intelligence” sets in, or computing power bottlenecks cause token quality or efficiency issues, the market’s confidence in the sustainability of these capital expenditure returns will be severely compromised. Once that expectation is shaken, it will directly pierce the lifeblood of this bull market, turning the current low-PE froth from a “strong positive feedback loop” into panic selling. At the same time, all valuations that had held firm amid prior negative news and were propped up by investor confidence will face a one-time valuation reset.