This is our read, not an oracle. We weight power headroom and time-to-power heavily because they are the binding constraint for AI build-out , a market-maturity index would weight differently, and that’s fine. Drag the sliders to weight it your way and watch the grades move.
| # | Locality | Score | Data | Compare |
|---|---|---|---|---|
| 1 | 🇨🇦 Manitoba province | 80 | ||
| 2 | 🇨🇦 Newfoundland and Labrador province | 73 | ||
| 3 | 🇨🇦 Quebec province | 73 | ||
| 4 | 🇺🇸 Tennessee state | 72 | ||
| 5 | 🇺🇸 Washington state | 71 | ||
| 6 | 🇺🇸 North Carolina state | 70 | ||
| 7 | 🇺🇸 Georgia state | 69 | ||
| 8 | 🇺🇸 Alabama state | 68 | ||
| 9 | 🇨🇦 British Columbia province | 68 | ||
| 10 | 🇺🇸 Iowa state | 67 | ||
| 11 | 🇺🇸 South Carolina state | 66 | ||
| 12 | 🇨🇦 Ontario province | 66 | ||
| 13 | 🇺🇸 Minnesota state | 65 | ||
| 14 | 🇨🇦 New Brunswick province | 64 | ||
| 15 | 🇺🇸 Wisconsin state | 63 | ||
| 16 | 🇺🇸 Kentucky state | 63 | ||
| 17 | 🇺🇸 Idaho state | 63 | ||
| 18 | 🇺🇸 Missouri state | 62 | ||
| 19 | 🇺🇸 Oregon state | 62 | ||
| 20 | 🇨🇦 Saskatchewan province | 62 | ||
| 21 | 🇨🇦 Alberta province | 61 | ||
| 22 | 🇺🇸 Michigan state | 61 | ||
| 23 | 🇺🇸 Florida state | 61 | ||
| 24 | 🇺🇸 Montana state | 61 | ||
| 25 | 🇺🇸 Wyoming state | 61 | ||
| 26 | 🇺🇸 Pennsylvania state | 59 | ||
| 27 | 🇺🇸 Indiana state | 59 | ||
| 28 | 🇺🇸 Ohio state | 59 | ||
| 29 | 🇺🇸 South Dakota state | 59 | ||
| 30 | 🇺🇸 Mississippi state | 59 | ||
| 31 | 🇺🇸 Arkansas state | 59 | ||
| 32 | 🇺🇸 New Mexico state | 59 | ||
| 33 | 🇺🇸 Illinois state | 58 | ||
| 34 | 🇺🇸 North Dakota state | 58 | ||
| 35 | 🇺🇸 Louisiana state | 58 | ||
| 36 | 🇺🇸 Nebraska state | 57 | ||
| 37 | 🇺🇸 Vermont state | 56 | ||
| 38 | 🇺🇸 Kansas state | 56 | ||
| 39 | 🇺🇸 Oklahoma state | 56 | ||
| 40 | 🇺🇸 Arizona state | 56 | ||
| 41 | 🇨🇦 Nova Scotia province | 56 | ||
| 42 | 🇺🇸 Virginia state | 55 | ||
| 43 | 🇺🇸 Maine state | 55 | ||
| 44 | 🇺🇸 New York state | 54 | ||
| 45 | 🇺🇸 West Virginia state | 54 | ||
| 46 | 🇨🇦 Prince Edward Island province | 54 | ||
| 47 | 🇺🇸 Texas state | 53 | ||
| 48 | 🇺🇸 New Hampshire state | 53 | ||
| 49 | 🇺🇸 Utah state | 53 | ||
| 50 | 🇺🇸 Colorado state | 52 | ||
| 51 | 🇺🇸 Nevada state | 52 | ||
| 52 | 🇺🇸 Connecticut state | 51 | ||
| 53 | 🇺🇸 Maryland state | 51 | ||
| 54 | 🇨🇦 Yukon territory | 49 | ||
| 55 | 🇺🇸 Massachusetts state | 47 | ||
| 56 | 🇨🇦 Northwest Territories territory | 47 | ||
| 57 | 🇮🇪 Ireland country | 43 | ||
| 58 | 🇺🇸 New Jersey state | 43 | ||
| 59 | 🇺🇸 Rhode Island state | 42 | ||
| 60 | 🇺🇸 Delaware state | 42 | ||
| 61 | 🇺🇸 District of Columbia district | 39 | ||
| 62 | 🇺🇸 Alaska state | 38 | ||
| 63 | 🇺🇸 California state | 37 | ||
| 64 | 🇨🇦 Nunavut territory | 32 | ||
| 65 | 🇺🇸 Hawaii state | 23 |
Comparing 4 , tick up to 5 above. Open “Adjust weights” to re-weight.
| Factor | 🇨🇦 Alberta | 🇺🇸 Virginia | 🇺🇸 Texas | 🇮🇪 Ireland |
|---|---|---|---|---|
Power availability & time-to-power 18% weight | 251,200 MW cap, fully allocated; ~19.6 GW queued | 25PJM queue ~70 GW; NoVA large-AI energization ~4–7 yr; Dominion ~40 GW requested | 50ERCOT paused Batch Zero large-load interconnection Aug 2026 (audit due Dec 10); ~474 GW requested (~90% DCs) | 0Dublin moratorium to ~2028; on-site gen required |
Power price 14% weight | 100~US$0.044/kWh wholesale | 509.31¢/kWh industrial | 756.58¢/kWh industrial | 0~19–25 €¢/kWh (~US$0.21+) |
Clean power / carbon intensity 8% weight | 50335 gCO₂/kWh | 50~300–330 gCO₂/kWh (est.) | 50~335–390 gCO₂/kWh | 50~280 gCO₂/kWh |
Water availability 8% weight | 50Med–High in the south | 75Low–Medium (Potomac) | 25High–Extremely High (C/W TX) | 100Low (high rainfall) |
Cooling climate (free-cooling) 10% weight | 100~40–90 CDD (Calgary) | 50~900–1,200 CDD | 0~2,000–2,800 CDD (Dallas) | 100~0–50 CDD (Dublin) |
Natural-disaster risk 6% weight | 75Low (hail, wildfire, flood) | 75Low–moderate (inland) | 25High (hurricane, tornado, freeze) | 100Very low |
Land availability & cost 7% weight | 75Abundant, cheap | 50Scarce/pricey in NoVA | 100Abundant, cheap | 25Scarce/expensive; planning limits |
Construction, material & labour cost 7% weight | 50Mid-range N. American | 25High-cost metro | 75Low-to-moderate | 25Among priciest in Europe |
Skilled-labour availability 6% weight | 50Strong trades; thin DC-ops | 100World's densest DC-ops | 75Large + growing | 75Deep DC-ops; tight build labour |
Fibre / network connectivity 4% weight | 50Regional (YYCIX); not a hub | 100~70% of global traffic (Ashburn) | 75Dallas top-5 US market | 100Major EU hub (INEX), subsea landings |
Policy, incentives & political climate 12% weight | 50Stable, market-friendly; connection cap | 75Sales-tax exemption; rising NIMBY | 50Tax exemption; Aug-2026 audit pause + SB6 | 25Stable but restricting DCs |
| Score (out of 100) | 61 | 55 | 53 | 43 |
How we score it
Each locality is scored 0–100 on 11 factors, grouped into power, environment, build & inputs, connectivity and governance. Every factor is scored against fixed, documented thresholds (so scores don’t wobble when we add a new place), then combined by weight into a composite and an A–F grade. Every value shows its source and year , hit “Show every source” above.
Method follows the OECD’s approach to composite indicators; the closest industry comparison is Cushman & Wakefield’s data-centre market index. We differ deliberately: we care about development suitability for new AI campuses, not existing market size, so we up-weight power and climate. Full factor definitions, weights and sources live on the methodology page (coming). Found a better source or a stale number? Tell us.