AI Data-Center Electricity Demand & the Grid
Global data-center power consumption, the AI share of incremental demand, capacity-market price spikes, US grid shortfall, and per-site draw.
Historical + IEA scenario range, terawatt-hours per year.
View data & sources →AI vs non-AI data-center power capacity, gigawatts (McKinsey base case).
View data & sources →$ per MW-day by delivery year — the killer chart for the grid story.
View data & sources →Projected peak demand vs available capacity, gigawatts.
View data & sources →Average draw, megawatts — frontier sites now rival mid-sized urban load.
View data & sources →Data table
| year | series | source_ref | value_basis | twh_historic | twh_scenario | ai_gw | non_ai_gw | delivery_year | clearing_price_usd_per_mw_day | demand_gw | capacity_gw | entity | draw_mw |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2024 | global_consumption | iea-electricity | IEA Energy & AI: ~415 TWh in 2024 (~1.5% of global electricity); corroborated by S&P Global | 415 | |||||||||
| 2030 | global_consumption | iea-electricity | IEA base case ~945 TWh by 2030 (S&P Global: roughly doubles) | 945 | |||||||||
| 2035 | global_consumption | iea-electricity | IEA base case ~1,200 TWh by 2035 | 1200 | |||||||||
| 2025 | ai_share | mckinsey-aipower | McKinsey “AI power”: AI workload power ~44 GW in 2025; total DC capacity ~103 GW (JLL) ⇒ non-AI ~59 GW (deduction) | 44 | 59 | ||||||||
| 2028 | ai_share | mckinsey-aipower | Interpolated along McKinsey base-case trajectory (AI 44→156 GW; total ~103→219 GW, 2025→2030) — labeled estimate | 100 | 75 |
12 more rows + CSV download
The full 17-row dataset, one-click CSV export, and the AI-ready context file are free with an account. Prefer to verify it yourself? The full methodology and sources are published below.
Methodology & sources
Last updated: Jul 17, 2026Methodology
Source-backed values are seeded for all five charts: global data-center electricity consumption (IEA Energy & AI, historic vs base-case scenario, corroborated by S&P Global), the AI vs non-AI share of data-center power capacity (McKinsey base case, corroborated by JLL), the PJM capacity-market clearing price by delivery year (PJM Base Residual Auction reports, corroborated by Utility Dive), the US data-center demand-vs-supply gap to 2028 (Morgan Stanley; Deloitte), and per-site power draw vs a city. Every numeric point carries a sources[].ref and a value_basis. The 2028 available-capacity figure is derived from Morgan Stanley’s ~45 GW shortfall estimate against ~100 GW demand (labeled in the value_basis). ESTIMATE: the AI-share chart uses McKinsey’s published AI-vs-total capacity trajectory (AI ~44 GW in 2025 → ~156 GW of ~219 GW total by 2030); the 2028 point is interpolated along that trajectory and the non-AI slice is a deduction (total − AI). It is a published-estimate split, not a measured per-year megawatt count. Re-verified 2026-06-17.
Sources
- US EIA Open Data ↗ Public domain
- IEA — Energy and AI / Electricity ↗ Open access — attribution
- S&P Global — data-center power demand ↗ Public report
- Morgan Stanley Research — data-center power ↗ Public report
- Deloitte — data-center power demand insights ↗ Public report
- Utility Dive — PJM capacity prices ↗ Public report
- Ember Climate — global electricity ↗ CC BY 4.0
- Our World in Data — Energy ↗ CC BY 4.0
- JLL — Global Data Center Market Outlook ↗ Public report
Comparisons are informative, not definitive. See each source for definitions and limits.
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