The Zhitong Finance App learned that CICC released a research report saying that the operating cash flow of leading US AI companies is close to capital expenditure, and the market is paying close attention to the sustainability of their high-investment models. CICC believes that as an emerging industry, AI technology breakthroughs and commercial revenue are naturally highly uncertain, and it is necessary to understand the sustainability of its capital expenditure from multiple perspectives. As a result, CICC broke away from the traditional profit forecasting framework and deconstructed the core funding sources of US AI's high capital expenditure from capital allocation logic.
CICC's main views are as follows:
On the capital supply side, the long-term trend of financialization in the US continues, that is, the expansion of “marshmallow” liquidity, which some scholars have likened. At the macro level, the general liquidity of the US continues to rise compared to GDP; at the micro level, it is reflected in the endless emergence of new financial products, revitalizing existing assets, activating idle capital, and transfusing blood into some industries with high potential returns.
On the capital demand side, the US AI industry has the dual attributes of technology and real estate, opening up both equity and debt financing channels. Its hard-core technology attributes are adapted to equity financing, and are a benchmark for VC and equity financialization models during the US stock technology network revolution period driven by the loosening of pensions in the 90s; its high fixed asset-like real estate characteristics mean that debt financing can be carried out through asset collateral. Although its fixed assets cannot completely target real estate, the debt financing logic of US real estate financialization after 2000 relied on derivatives to revitalize stocks and expand credit is of reference significance.
Currently, the financialization of AI in the US is still in its early stages. The financing cash flow of leading AI companies has just been corrected. The cost of combined debt financing is still significantly lower than equity financing. The industry's new financing is mainly based on debt, and large-scale equity financing has yet to be initiated. In retrading history, the US stock market bubble and the bursting of the real estate bubble all simultaneously experienced three major phenomena: high leverage, deterioration in fundamentals, and systematic tightening of liquidity. Judging from these indicators, there are currently no systemic risks in the US AI industry.
But America's short-term liquidity risk cannot be ignored. The trend of the US economy, the game between the market and the Federal Reserve, compounded by the uncertainty in oil prices brought about by the US-Iran geopolitical conflict, there is a possibility that US liquidity will tighten beyond expectations. If this happens, the global market will also be affected, and market concerns about the sustainability of AI companies' capital expenditure may also heat up.