Kevin Warsh, Chairman of the U.S. Federal Reserve, stated in a speech at Jackson Hole that artificial intelligence could become a new factor of production, leading to lower costs for businesses and consumers if productivity experiences a sustained leap.

Warsh noted that capital is continuously flowing into AI infrastructure, with the pace of innovation exhibiting characteristics of 'super Moore's Law'; users of large language models acquire model capabilities by purchasing tokens, with annualized token sales from two leading labs exceeding $100 billion, a growth of over 500% compared to a year ago.

He suggested that the current value of AI may primarily flow to holders of scarce assets, including AI labs, chip manufacturers, energy suppliers, and cloud service providers; however, the long-term key variable is whether productivity gains can be transferred to business clients and consumers.

Warsh specifically pointed out that the pricing paths of cutting-edge models and older models may diverge: access to high-performance models can maintain a high premium, while the token prices of older models may eventually drop to near marginal costs, resulting in ongoing technological deflation.

In the short term, AI does not solely push prices down. The construction of large-scale data centers is driving up costs for construction and storage chips, and AI capital expenditures have become a significant part of the growth in U.S. investment in equipment and intangible assets; Federal Reserve data shows that related investments are driving a quarterly growth rate of about 9% in such capital expenditures, with over half of the growth attributable to AI construction.

Warsh emphasized that research on AI productivity will not alter current monetary policy decisions. The U.S. PCE inflation rate over the past 12 months was 3.7% and 4.1% over the past 6 months, both above the Fed's 2% target; 54% of the goods and services in the PCE basket saw price increases exceeding 3% in the past 12 months, thus the Fed's current priority remains to reduce inflation.

In market mechanisms, funds are concentrating on buying scarce supply segments such as AI labs, chips, cloud computing, electricity, and data centers, flowing into infrastructure through corporate capital expenditures and credit expansion; if token prices continue to decline with model maturity, application companies and end users will benefit, while supply chain companies reliant on high-priced computing power, storage, and construction orders will face pressure on profit margins and pricing power. The market is simultaneously trading two opposing main lines: long-term AI deflation expectations favor productivity assets, while short-term investment demand and inflation stickiness support higher interest rate expectations.

Source: Public Information