The arrival of ChatGPT in late 2022 set off a wave of optimism about artificial intelligence and its potential to transform the economy. Yet actual productivity numbers seem to reflect a more modest impact so far. Since the debut of ChatGPT, total factor productivity (TFP) growth—a measure of how efficiently an economy converts labor and capital into output—has averaged just 1.11% annually (when adjusted for utilization), below the historical average of 1.23%, according to data from the Federal Reserve Bank of San Francisco. Over the past four quarters, this slowed to just 0.32% by the fourth quarter of 2025. This gap between AI enthusiasm and measured productivity raises an important question: Even if the productivity gains haven’t arrived yet, how does the expectation of such gains affect the macroeconomy? We use the St. Louis Fed dynamic stochastic general equilibrium (DSGE) model to examine this question, analyzing what economists call a “TFP news shock”—a situation in which households and firms become convinced that a productivity boom is coming, even though it hasn’t happened yet. As our findings show, the short answer is yes: AI optimism can raise inflation, and the monetary policy response matters considerably for the extent of that increase.