Public changelog
Every revision gets a date
Grade changes, source swaps, and corrections — including ones that don’t change the conclusion — go into one public record.
Read the changelog →Source-linked, independently graded research
Who pays for AI?
It depends on the market. AI demand is the main documented cause of higher memory prices, one cause among several for storage, transformer, gas-turbine and electricity pressure, unmeasured for water, construction, labor and capital, and wrongly blamed for the grid interconnection queue. Data centers are projected to use 11.8% of U.S. electricity by 2030.
| Value | Measures | Source | Grade |
|---|---|---|---|
| 11.8% | of U.S. electricity projected for data centers in 2030, LBNL reference case | Lawrence Berkeley National Laboratory (2026) · U.S. Energy Information Administration (2026) | AI-driven |
| 1–2+ yr | typical distribution-transformer lead time in 2024, per DOE | U.S. Department of Energy (2026) | AI-contributing |
| 3:1 | HBM-to-DDR5 production capacity trade ratio reported by Micron | Micron Technology (2025) · Micron Technology (2026) | AI-driven |
| 100 GW | GE Vernova gas-turbine backlog plus slot reservations, Q1 2026 | GE Vernova (2026) | AI-contributing |
Claim report cards
Which AI cost claims are true?
True“AI is driving the return of U.S. electricity-demand growth.”AI data centers are the largest single driver of new U.S. electricity demand.→Unproven“AI raised my household electricity bill.”No published analysis puts an AI-attributable dollar figure on a household bill.→False“AI caused the transformer shortage.”The transformer shortage began years before the AI buildout.→
Prices in the markets AI buys from are rising about 10% faster than in comparable markets it doesn’t.
Crowding Index
How much are prices in AI-exposed markets rising?
The index compares AI-exposed input markets to a matched core-PPI control, baselined at 100 in January 2024.
See the score, basket and calculation rules →Note the outlier: semiconductors broadly are cheaper than in January 2024. The squeeze is specific — memory, storage, and grid equipment — not “chips” in general.
Latest resource grades
What is AI actually making more expensive?
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 →SemiconductorsAI-contributing
Storage (NAND & SSDs)
+30.4%BLS storage-device PPI, Jan 2024 to Jun 2026
Storage prices rose 30.4% in 30 months while AI and the server refresh cycle drew on the same NAND capacity.
See the evidence →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 →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 →How a grade is made
The same four checks for every grade
- 1Write down the claim
Use the wording people actually repeat.
- 2Trace how it would happen
Identify the market, the other buyers and the supply limit.
- 3Check the best sources
Start with public data, agency work and company filings.
- 4Review it by hand
Tools draft updates. The editor approves every publication.
About this project
Pro-growth, and honest about the bill.
David Veksler is a working AI architect who thinks the buildout is worth it — which is exactly why the accounting should be straight. Software flags new data and drafts updates; David reviews every publication. No ads, sponsors, or affiliate links. Affiliations and the capital-markets conflict are disclosed. About & disclosures →