Who Pays for AI?

A public ledger of AI’s resource costs

Who actually pays for the AI buildout?

AI data centers need power, chips, equipment, workers and money. This site tracks where that demand is creating measurable competition and where AI is simply getting the blame. Every grade comes with sources and a check date.

Explore 10 resource ledgersSee how grades are assigned

Crowding Index

How the score works

January 2024 = 100

The Crowding Index measures how prices and availability in AI-exposed input markets have changed relative to comparable markets with less direct AI demand, using January 2024 as a baseline of 100.

See the basket and calculation rules β†’
Storage-device PPI65.056
+30.4% since Jan 2024 Β· not seasonally adjusted
Transformer PPI365.306
+5.9% since first current-series observation, Oct 2024
Semiconductor PPI29.695
βˆ’6.3% since Jan 2024 Β· aggregate series, not memory-specific
Transformer lead time1–2+ yr

DOE’s 2024 distribution-transformer range; large units can reach 3–4 years.

Equipment ledger β†’
HBM capacity trade3:1

Micron’s reported HBM-to-DDR5 production trade ratio.

Memory ledger β†’
Gas turbine orders100 GW

GE Vernova backlog plus slot reservations at Q1 2026.

Turbine ledger β†’

Latest resource grades

Markets with the clearest signal

All 10 markets β†’
SemiconductorsAI-driven

Memory (DRAM & HBM)

3:1HBM-to-DDR5 capacity trade ratio reported by Micron

AI memory demand is squeezing the same production capacity used for ordinary DRAM.

See the evidence β†’
SemiconductorsAI-contributing

Storage (NAND & SSDs)

+30.4%BLS storage-device PPI, Jan 2024 to Jun 2026

Storage prices rose 30.4%; available data does not isolate AI’s share.

See the evidence β†’
Grid equipmentAI-contributing

Transformers & Switchgear

1–2+ yrdistribution-transformer lead time in 2024

Data centers are adding demand to a transformer shortage that started earlier.

See the evidence β†’
Generation equipmentAI-contributing

Gas Turbines

100 GWGE Vernova backlog plus slot reservations, Q1 2026

Data centers occupy turbine slots within a broader power-construction boom.

See the evidence β†’

Claim report cards

A page for each recurring claim

All report cards β†’
AI-drivenβ€œAI is driving the return of U.S. electricity-demand growth.”Supported at the national demand levelContestedβ€œAI raised my household electricity bill.”The effect is utility-specificScapegoatedβ€œAI caused the transformer shortage.”Overstated: AI adds demand to an older shortage with several causes

How a grade is made

The same four checks for every grade

  1. 1
    Write down the claim

    Use the wording people actually repeat.

  2. 2
    Trace how it would happen

    Identify the market, the other buyers and the supply limit.

  3. 3
    Check the best sources

    Start with public data, agency work and company filings.

  4. 4
    Review it by hand

    Tools draft updates. The editor approves every publication.

Public changelog

Every meaningful revision gets a date.

Grade changes, source replacements and revised figures all go into one public record, including corrections that do not change the overall conclusion.

Read the changelog β†’

Research updates

Follow every release.

The Changes page records every data update, editorial revision, grade change and correction in chronological order.

Follow releases β†’

About this project

AI growth consumes real resources.

AI architect David Veksler maintains this project. Software flags new data and drafts updates. David reviews every publication. The site discloses his affiliations and the capital-markets conflict. It has no ads, sponsors or affiliate links. About & disclosures β†’