What if AI datacenter buildout adds 10 Bcf/d to US gas demand?
Hyperscaler AI-datacenter load drives a structural +10 Bcf/d increase in US power-sector gas burn by decade's end, tightening the domestic balance and lifting the long-dated Henry Hub curve.
Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 1–3 years horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…
What it would mean
If this plays out, it is a mixed shock. Hyperscaler AI-datacenter load drives a structural +10 Bcf/d increase in US power-sector gas burn by decade's end, tightening the domestic balance and lifting the long-dated Henry Hub curve. The trigger decomposes into signed root‑shocks — Natural gas ▲ · AI capex ▲ · Industrial demand ▲ · Inflation expectations ▲ — which propagate through our causal graph to the markets below.