US GDP Directly Attributable to AI Systems, 2030
What percentage of US GDP will be directly attributable to AI systems by 2030?
model spread ±5.11%
90% interval
width ±11.30%
The three supporting readings tell you how much weight to put on p50: confidence reflects cross-model spread relative to scale, the p5—p95 band shows the 90% interval each model collectively places, models shows whether the four agree on shape.
Current distribution
US GDP Directly Attributable to AI Systems, 2030
What percentage of US GDP will be directly attributable to AI systems by 2030?
Belief trajectory
How the ensemble median and uncertainty band have moved across the polling window.
Driver decomposition
Expanded by default. Driver-level distributions explain movement in the anchor distribution.
Driver distributions explain movement in the anchor distribution. They do not mechanically generate it.
Driver matrix
Expanded by default. Compare how each model views every driver.
Compare every driver across the four-model ensemble. Use this surface to find disagreement, weak confidence, and drivers worth opening.
Per-model distributions
Each model forecasts the quintile distribution independently. The Crene aggregate is the median of each percentile across these four models.
Resolution
Resolved against BEA satellite accounts for AI economic contribution, or if unavailable, the consensus of McKinsey Global Institute, Stanford HAI, and Brookings estimates of AI direct contribution to US GDP.