Economist: AI spending mainly relies on cash flow, and the bubble risk has been overestimated

Economist Jeffrey Cleveland recently released a report presenting an interesting perspective: in the AI investment boom, corporate spending mainly comes from internal cash flow rather than excessive borrowing, which suggests that the bubble risk may be overestimated by the market. This view offers some reference value for understanding current economic and market trends.

Funding Structure of AI Investments

Cleveland emphasizes a key distinction in the report: AI-related expenditures are primarily financed by companies' own cash flow rather than over-leverage. The importance of this viewpoint lies in:

• Investments supported by cash flow are more sustainable, and companies won't be forced to withdraw due to debt pressures
• Corporate leverage ratios are common leading indicators before economic downturns, but currently debt growth is relatively moderate
• Compared to historical periods of overexpansion, current debt levels remain within manageable ranges

This conclusion directly points to a question: if AI investments are mainly supported by companies' profitability, then the risk structure of these investments is entirely different from expansion relying on debt financing.

Reassessment of Bubble Risk

Cleveland believes that the AI craze is unlikely to turn into a bubble. The reasoning is:

Bubbles typically require several conditions—excessive leverage, frantic financing, unsustainable growth expectations. But when companies mainly invest using cash flow, these conditions are weakened. The limited nature of cash flow naturally constrains the scale of overinvestment; companies won't endlessly burn cash chasing hot trends.

This is not to say that AI investments are risk-free, but that the nature of the risks is different. Short-term risks include misjudging technological directions or changes in the competitive landscape, but systemic financial risks (such as crashes caused by excessive leverage) are relatively low.

The True Risks Facing Investors

Cleveland's most interesting point is: for investors, the real risk may not be entering too late, but exiting too early.

This reflects a psychological phenomenon—within emerging themes, investors are often more afraid of missing out (FOMO), but Cleveland believes the current situation is actually the opposite. If AI investments are indeed supported by cash flow, then the sustainability of this theme is relatively strong, and exiting too early could mean missing out on longer-term gains.

Summary

The core logic of this report is: the funding structure of AI investments (cash flow rather than debt) determines their risk profile, making bubble risk relatively controllable. Investors need to adjust their perception of risk—not fearing to enter too late, but being cautious about exiting too early. Of course, this is an economist's view based on current data; the actual situation still requires ongoing observation of indicators such as corporate leverage ratios and debt growth.