Detecting subtle patterns in data will help America preserve its hard-won competitive edge.
The release of Chinese artificial-intelligence company DeepSeek’s R1 model in January 2025 renewed debate over the technological rivalry between the U.S. and China. Less widely noted is that DeepSeek began as a spinoff from a quantitative trading firm’s application of early AI techniques to financial markets. That connection highlights the immense promise of AI applications to the financial industry. It should remind us that in this domain, the U.S. has an unparalleled competitive advantage because of the depth of its capital markets, the talent that trades in those markets, and the technology they run on. So how do we use that advantage to drive the next wave of AI developments?
As in other industries, AI is already streamlining antiquated and inefficient workflows in finance, for example through tools that extract terms from dense financial agreements and develop code. But those gains, though useful, are incremental. The more consequential applications of AI in finance involve improving the core functions of markets themselves: pricing assets, measuring risk, detecting shifts in the economy, and managing volatility. These are areas where AI’s ability to detect subtle patterns in large volumes of data can be transformative.