The Simple Macroeconomics of AI

Daron Acemoglu uses a task-based economic model to test claims that artificial intelligence will produce rapid, economy-wide growth. He estimates that AI may raise total factor productivity by no more than 0.66 percent over ten years, and probably by less than 0.53 percent once the analysis accounts for tasks whose context is difficult for machines to learn. The result is meaningful, but far smaller than many forecasts embedded in investment and market expectations.

The paper argues that productivity gains depend on which tasks can be performed reliably and how much economic value those tasks contain, not simply on improvements in model capability. Acemoglu also warns that automation may widen the divide between capital and labor income and finds little basis for assuming it will reduce inequality among workers. Some new AI-enabled tasks may create social costs as well as measurable output.