GRIDINT RESEARCH · DATA HUB

AI economics.

The AI economy, receipted — the tracked cuts ledger beside filed capital, small on purpose: no event enters without a receipt, and the review queue is public.

published 2026-08-27 · data cutoff 2026-08-26 · edition 1 — updated only by a new dated edition

THE REPORTThe AI Layoffs LedgerRead it →

Fifteen months of cuts, one picture.

2025-072025-102026-012026-042026-07BUBBLE AREA = HEADCOUNT · COLOR = RECEIPT CLASSAmazon−30,000Intel−26,400Oracle−21,000Dell−11,000Meta−8,000Microsoft −4,800HP−4,000CiscoIntuitAtlassian −1,600Nike −775CrowdStrike −5002025-072025-102026-012026-042026-07BUBBLE AREA = HEADCOUNT · COLOR = RECEIPT CLASSAmazon−30,000Intel−26,400Oracle−21,000Dell−11,000Meta−8,000Microsoft −4,800HP−4,000CiscoIntuitAtlassian −1,600Nike −775CrowdStrike −500
The tracked ledger as a timeline — sized by headcount, colored and filterable by receipt classFifteen layoff events, May 2025 → July 2026. Green counts appear verbatim in a filing; violet ride on filed charges with a press count; amber is press-only; pink is derived from a filed end-state and includes attrition. Click a legend chip to include or exclude its class; tap or hover any mark for its receipt.source SEC EDGAR filings + receipted press, per event · classes printed in B1 and F1 — method curated entry — a receipt or no entry · null count ≠ 0 · the filter changes what is DRAWN, never what is trackedRead the report →

Plot it on any two axes.

The shape of the records.

Records by filing form

8-K8-K: 9 of 15 (60.0%)9 · 60%10-K10-K: 3 of 15 (20.0%)3 · 20%10-Q10-Q: 1 of 15 (6.7%)1 · 7%PRESSPRESS: 1 of 15 (6.7%)1 · 7%ASXASX: 1 of 15 (6.7%)1 · 7%15 records · counted from the records at build · source the GRIDINT layoffs ledger

SOURCE · the GRIDINT layoffs ledger, hand-curated — receipted to filings · data cutoff 2026-08-26 · counted from the records

How this hub was made.

Eight events tracked to the receipt standard; the rejection queue is part of the record. Payroll-saved figures are TheCatch's estimates, labeled with method. Fragility and payoff scores elsewhere in this family are model outputs and say so. Downloads are verification extracts.

The ai economics exhibit page → · The institute's method →

Every edition, dated.

  • Edition 1 published 2026-08-27 · data cutoff 2026-08-26 · first edition

A hub changes only as a new dated edition, on the institute's word — never on a schedule. Collection continues underneath; publication is deliberate.

Verify this hub.

Verification extracts — the working records with their receipts, attribution first, pointing at the origin. We never provide data; the source is the authority, this hub is the lens.

Cite this hub

GRIDINT Research (2026). AI economics data hub, edition 1 (data cutoff 2026-08-26). https://gridint.ai/data/ai-economics
@misc{gridint_ai_economics_2026,
  title = {AI economics data hub, edition 1},
  author = {{GRIDINT Research}},
  year = {2026},
  note = {Data cutoff 2026-08-26; source: the GRIDINT layoffs ledger, hand-curated — receipted to filings},
  url = {https://gridint.ai/data/ai-economics}
}

In pandas

import pandas as pd
D = pd.read_json("https://gridint.ai/demo/ai-economics/explorer-records.json")
records = pd.DataFrame(D["rows"].tolist(), columns=["company", "heads_cut", "pct_workforce", "capex_usd_b", "filing_form", "announced"])

The first row of that extract, as it stands: ["Meta", 8000, 10, 135, "10-Q", "2026-04-17"] — the values are the receipt, whatever a column is called.

Every hub →

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