# AI Campus Colocation: Sources & Citations | SAVRN
Source: https://savrn.com/sources/colocation
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[All research sources](https://savrn.com/sources)

Sources & Citations

# AI Campus Colocation

6 primary sources 3 categories We publish the receipts

A

## Industry survey & capex

Uptime · McKinsey

Uptime Institute Global Data Center Survey 2024 — canonical industry baseline on operator practice, rack density, and PUE for the colocation comparison.

Uptime Institute Global Data Center Survey 2024 [View source](https://www.uptimeinstitute.com/resources/asset/global-data-center-survey-results-2024)

McKinsey analysis of data center capex forecasting — used as the projection baseline for AI infrastructure capital deployment.

McKinsey — Technology, Media & Telecommunications practice [View source](https://www.mckinsey.com/industries/technology-media-and-telecommunications)

B

## Power demand forecasts

Goldman · IEA

Goldman Sachs Research on AI-driven data center power demand growth.

Goldman Sachs Research [View source](https://www.goldmansachs.com/insights)

International Energy Agency tracking of grid-tied data center builds and global electricity demand from AI.

International Energy Agency [View source](https://www.iea.org/)

C

## Federal grid data

LBNL · DOE

LBNL queued capacity tracker — U.S. interconnection queue size and wait times that anchor the colocation deployment-speed comparison.

LBNL — Queued Up interconnection queue tracker [View source](https://emp.lbl.gov/queues)

U.S. Department of Energy publications and program data on grid modernization, large-load policy, and data center electricity demand.

U.S. Department of Energy [View source](https://www.energy.gov)

These are the primary sources behind our research. Have a better one, or spot an error? [Tell us](https://savrn.com/contact?topic=sources) — we’ll correct it.