儘管中國在推動科技企業融資方面展現出決心，並且擁有顯著低於美國的融資成本優勢，但也面臨著潛在風險。政策主導的資金湧入可能導致產能過剩和利潤壓縮，而且單靠資金並不足以彌補在頂尖技術與人才方面的差距，銀行業也依然偏好成熟企業而非高風險的新創公司。
然而，中國在人工智慧領域可能不需要像美國那樣龐大的資金規模就能達成目標。研究指出，中國企業訓練AI模型的成本遠低於全球領導者，這意味著中國可以憑藉其深厚的製造基礎、供應鏈和工程人才優勢，透過大規模的工業化與商業化來彌補純粹創新上的劣勢。
The unprecedented success of memory chip maker CXMT's initial public offering in Shanghai last month highlights China's aggressive utilization of its massive capital markets to support strategic industries like artificial intelligence. Beijing is attempting to channel the world's largest pool of household savings into stocks and bonds to close the significant tech funding gap with the US and reduce reliance on foreign advanced chips.
Although China shows determination in boosting tech financing and enjoys significantly lower funding costs compared to the US, it also faces potential risks. The policy-driven influx of capital could lead to overcapacity and margin compression, and funding alone is insufficient to overcome the shortfalls in cutting-edge technology and talent, while banks still favor mature companies over high-risk startups.
However, China may not require the same massive scale of capital as the US to achieve its goals in the artificial intelligence sector. Research indicates that the cost for Chinese companies to train AI models is a fraction of that of global leaders, suggesting that China can leverage its deep manufacturing base, supply chains, and engineering talent to offset pure innovation disadvantages through large-scale industrialization and commercialization.