In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period.

SocioLens project,

Claim LD02-HQ-C10 (v1.0)

In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period.

Provenance and status

Claim type: Fact (self report)
Publication status: Eligible for publication, with qualifiers: self report
Verification state: Checked against the primary source. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: Causal aggregate employment effect; “only 2% actually cut jobs”
Limitations: Self-report; may miss forgone hiring; broad AI
Source (as cited): Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026
Source type: Working paper (recorded as “Government working paper / nationally representative firm survey”)
Institutional position: Government research
Maturity of the evidence: Rapidly maturing evidence
Recorded date: 25 September 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026 (Working paper)
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Version

This page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): FACT (SELF_REPORT) (as printed: “FACT (SELF-REPORT)”)
Publication status (coded): ELIGIBLE (SELF_REPORT) (as printed: “ELIGIBLE WITH SELF-REPORT QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): WORKING_PAPER
Maturity (coded): RAPIDLY_MATURING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD02-HQ-C10	—
2	PUBLIC-FACING CLAIM	In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period.	—
3	CLAIM TYPE	FACT (SELF-REPORT)	base_types: FACT · qualifiers: SELF_REPORT
4	RESEARCH STRAND	A/C — Exposure/adoption/use; firm labour demand	—
5	MATURITY	RAPIDLY MATURING	states: RAPIDLY_MATURING
6	SOURCE	Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026	source_ids: SRC-LD02-BONNEY-CES-26-25
7	SOURCE TYPE	Government working paper / nationally representative firm survey	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Government research	—
9	SCOPE	US firms; November 2025–January 2026	—
10	DESIGN	Business survey and regression analysis	—
11	SAMPLE / DATASET	BTOS 2026 AI supplement	—
12	MODEL / TOOL / VERSION	Broad AI use	—
13	COMPARATOR	Survey population / users vs non-users	—
14	MAIN RESULT	18% firm use, 32% employment-weighted; 23% of firms report worker task use, 41% weighted; 66% of users augment only; 2% report AI-related employment decreases	—
15	INFERENTIAL TARGET	Adoption/use prevalence and firm-reported employment response	—
16	DOES NOT LICENSE	Causal aggregate employment effect; “only 2% actually cut jobs”	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Self-report; may miss forgone hiring; broad AI	—
19	CONTRADICTORY / SUPPORTING SOURCES	Yotzov survey; administrative firm studies provide causal complements	—
20	GEOGRAPHY / LANGUAGE	US / English	—
21	DISTRIBUTIONAL LEDGER	Adoption concentrated in larger/info/professional/finance firms	—
22	R01 / FIELD-MAP LINKS	D2, L-C, R-1	—
23	WHAT WOULD CHANGE THIS CLAIM?	Later nationally representative waves materially revise prevalence/impact reports	—
24	PUBLICATION STATUS	ELIGIBLE WITH SELF-REPORT QUALIFIER	state: ELIGIBLE · qualifiers: SELF_REPORT
25	RECORDED DATE	2026-09-25	—

Field 22 references resolved against Field Map v0.2: D2 (DOMAIN); L-C (LENS); R-1 (LENS)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026” → Bonney et al. (2026), “The Microstructure of AI Diffusion” (SRC-LD02-BONNEY-CES-26-25--v1.0) — Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026; class WORKING_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, September 25). In the US Census 2026 AI supplement, 18% of firms reported using AI in a business function, while only 2% self-reported AI-related employment decreases during the reference period [Claim LD02-HQ-C10, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld02-hq-c10/v1.0/

@misc{sociolens_ld02_hq_c10_v1_0,
  author = {{SocioLens project}},
  title = {In the US Census 2026 AI supplement, 18\% of firms reported using AI in a business function, while only 2\% self-reported AI-related employment decreases during the reference period.},
  year = {2026},
  date = {2026-09-25},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld02-hq-c10/v1.0/}},
  note = {Claim LD02-HQ-C10, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 dabf70db18b229257f524dc8904b77d0534e7b25f2f2ff7a2588214e6274894e.

Frozen Drive-derived inputs

R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED (v1.0) — Drive ID 1y7Iid5SaEnjKaPZ7ZsSSVj8dASVlSF8b; revision: NOT_EXPOSED_BY_DRIVE_TEXT_EXPORT; Drive modified ; block “ENTRY 10 — LD02-HQ-C10” SHA-256 06e3e33645896d013dec4aac309be888b7237a47de2fef19cc00d0258c82a901; SocioLens — Programme Status & Authority Register v0.6 status “CURRENT.”; frozen fixture fixtures/frozen/r05-ld02-claim-ledger-v1.0-canonical.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the locked R05 canonical ledger v1.0; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 1 authorizes completion of its existing canonical claim corpus. This is the first materialized version of this logical Claim, not a research update.
CURRENT_POINTER = true — basis: SocioLens — Programme Status & Authority Register v0.6 status for "R05 — LD-02 Canonical Claim Ledger v1.0 — LOCKED": "CURRENT."
FIELD_6_SOURCE_REFERENCE = SRC-LD02-BONNEY-CES-26-25--v1.0 — basis: field 6 of ENTRY 10 — LD02-HQ-C10 cites "Bonney et al., “The Microstructure of AI Diffusion,” US Census CES-WP-26-25, April 2026"; HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5: this exact frozen field-6 citation segment selects SRC-LD02-BONNEY-CES-26-25--v1.0 under ruling 4; identity established by B1 lines 111–157 and the pinned R05 ledger fields 6/7/8.
SOURCE_PROVENANCE_PIN = SRC-LD02-BONNEY-CES-26-25--v1.0 — basis: HQ-ESC-sociolens-ld02-t6-20261011T133040Z-01 ruling 5 / Publication System Amendment v1.2 §§4,6: explicit version-pinned public provenance selection of SRC-LD02-BONNEY-CES-26-25--v1.0 for LD02-HQ-C10--v1.0. Preserve the canonical qualification and independently authorized Source metadata.