US GDP Directly Attributable to AI Systems, 2030
What percentage of US GDP will be directly attributable to AI systems by 2030?
spread ±0.44%
90% interval
width ±9.10%
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.
Latest distribution
Belief trajectory
Cross-model percentile distribution over time. Outer band p5—p95, inner band p25—p75, line p50. Repolled daily at 06:35 server time.
Per-model distributions
Each model forecasts the quintile distribution independently. The Crene aggregate is the median of each percentile across these four models.
TODAY=2.0%; BAND=+150% to +400% (structural AI growth, not mature sector); P50_LOGIC=Sustained capex, productivity gains, and enterprise adoption drive ~2.7× expansion to 5.4% by 2030;
TODAY=3.0; BAND=[2.0, 20.0]; P50_LOGIC=[I expect a moderate growth in AI contribution due to current adoption rates and projected advancements in 2026, interpreting a clear trend upward.] TAILS=[Extreme growth scenarios could emerge from rapid technological breakthroughs or significant shifts in policy supporting AI, while downturns may occur due to regulatory hurdles or economic crises.]
TODAY=2.5; BAND=80% to 240%; P50_LOGIC=Projecting moderate but significant AI integration driving growth in its direct GDP contribution; TAILS=Slower adoption or a significant AI investment bust would drive lower extremes, while rapid breakthroughs and widespread deployment would drive higher extremes.
TODAY=2.4; BAND=±40% cumulative; P50_LOGIC=2.4*(1+1.95) from 2026-2030 AI spend ramp. TAILS=Extremes driven by capex cycle boom vs regulatory stall or recession.
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.