AI Economics

Report · Growth & productivity · Labor & work · Economic measurement · Economic structure

Forecasting the Economic Effects of AI

Ezra Karger, Otto Kuusela, Jason Abaluck, Kevin Bryan, Basil Halperin, Todd Jones, Connacher Murphy, Phil Trammell, Matt Reynolds, Dan Mayland, Ria Viswanathan, Ananaya Mittal, Rebecca Ceppas de Castro, Josh Rosenberg, and Philip E. Tetlock

· Revised 20 May 2026

GDP-growth forecasts from economists, AI experts, superforecasters, and the public under different AI scenarios.
Source visual: Forecasting Research Institute

Summary

A structured survey compares forecasts from economists, AI-industry experts, AI-policy experts, superforecasters, and the public. Central group medians put annual GDP growth near 2.5%; under a rapid-automation scenario, forecasts rise to roughly 4% while labor-force participation falls from 62% to 55% by 2050 and wealth becomes more concentrated.

Why it matters

The report makes disagreement about AI's economic effects measurable instead of presenting one forecast. Matt Clancy's interpretation of related FRI work suggests that persistent gaps reflect different assumptions about generalization, diffusion, and bottlenecks rather than missing facts alone.

What to keep in mind

These are elicited beliefs, not observed outcomes. Expert selection, nonresponse, scenario framing, and different prior models of technological change can all shape the results; deliberation need not make those models converge.

Sources