CICC: American AI in the "Cotton Candy" Era

CICC released a research report stating that the operating cash flow of leading American AI companies has approached their capital expenditure, and the market is highly focused on the sustainability of their high-investment model. CICC believes that as an emerging industry, AI technological breakthroughs and commercialization revenue naturally carry significant uncertainty, and the sustainability of capital expenditure needs to be understood from multiple perspectives. Therefore, CICC steps outside the traditional earnings forecast framework and, from the logic of capital allocation, breaks down the core sources of funding for high capital expenditure in American AI. CICC's main viewpoints are as follows: On the funding supply side, the long-term financialization trend in the United States continues, namely the "cotton candy" style liquidity expansion that some scholars have analogized. At the macro level, this is reflected in the continued rise of broad liquidity in the United States relative to GDP; at the micro level, it is reflected in the endless emergence of new financial products, revitalizing existing assets and activating idle funds, providing blood transfusions to certain industries with potentially higher returns. On the funding demand side, the American AI industry possesses dual attributes of technology and real estate-like characteristics, opening up both equity and debt financing channels. Its hardcore technological attributes are suited to equity financing, comparable to the VC and equity financialization model during the U.S. internet stock revolution in the 1990s driven by pension deregulation; its real estate-like characteristics of high fixed assets mean it can carry out debt financing through asset collateralization. Although its fixed assets cannot be fully equated with real estate, the debt financing logic after 2000 in which U.S. real estate financialization relied on derivatives to revitalize existing assets and expand credit is of reference significance. The current financialization of American AI is still in its early stages. The financing cash flow of leading AI companies has just turned positive, and given that debt financing costs are still significantly lower than equity financing, new industry financing is mainly debt-based, with large-scale equity financing not yet initiated. Looking back at history, the bursting of the U.S. internet stock bubble and the real estate bubble both coincided with three major phenomena: high leverage, deteriorating fundamentals, and systemic tightening of liquidity. Judging from these indicators, the American AI industry currently faces no systemic risk. However, short-term liquidity risk in the United States should not be overlooked. The trajectory of the U.S. economy, the game between the market and the Federal Reserve, combined with oil price uncertainty brought by U.S.-Iran geopolitical conflicts, means there is a possibility of liquidity tightening in the United States beyond expectations. If this occurs, global markets will also be affected, and market concerns about the sustainability of AI companies' capital expenditure may also intensify accordingly.