Princeton economist Markus Brunnermeier told central bankers at Jackson Hole that AI trading agents could understand and exploit monetary policy faster than officials can respond. His paper described a possible Federal Reserve with two press conferences, one offering an anchoring narrative to people and another supplying training data to machines. He also warned that central banks might become deliberately less predictable to stop automated traders from gaming policy signals. The argument appeared at the Kansas City Fed's annual symposium, where financial innovation was the stated subject. Brunnermeier called the imbalance “asymmetric understanding,” a condition in which markets equipped with advanced agents may read the central bank better than the bank reads them.

An interest-rate statement already moves bond and currency prices within moments of publication. An agent can parse each word, compare it with years of data and place trades while reporters are still forming questions. Transparency then reaches the public at unequal speeds. Dividing communication into a human narrative and a machine-readable feed would formalize two audiences for the same public decision. The feed would become market infrastructure, shaped for institutions able to train systems on it, while households encounter the decision later through mortgages, savings and pension values. Any such arrangement would require a public release time, an open data format, equal-access rules and a record of which automated trades were placed before the human conference ended.