In May 2026, 45% of US workers used generative AI for work, but adoption was widespread and shallow: within most occupations and tasks fewer than half of workers used it, no task exceeded 70% adoption, and mean weekly hours among work users had stayed flat since late 2024.

SocioLens project,

Claim LD03-SL-C03 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: working paper
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: Productivity or output effects; firm-level adoption
Limitations: Self-reported use; 'shallow' refers to the share of workers adopting within an occupation or task, not to hours of use
Source (as cited): Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026
Source type: Working paper (recorded as “Academic working paper”)
Institutional position: Government research
Maturity of the evidence: Rapidly maturing evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 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): ESTIMATE (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (WORKING_PAPER) (as printed: “ELIGIBLE WITH WORKING-PAPER 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	LD03-SL-C03	—
2	PUBLIC-FACING CLAIM	In May 2026, 45% of US workers used generative AI for work, but adoption was widespread and shallow: within most occupations and tasks fewer than half of workers used it, no task exceeded 70% adoption, and mean weekly hours among work users had stayed flat since late 2024.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	A — Adoption and depth of use	—
5	MATURITY	RAPIDLY MATURING	states: RAPIDLY_MATURING
6	SOURCE	Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026	source_ids: SRC-SL-BICK-BLANDIN-DEMING-SCHUMACHER-STLFED-WP-2026-017
7	SOURCE TYPE	Academic working paper	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Government research	—
9	SCOPE	US adults aged 18–64; task module August 2025 to May 2026	—
10	DESIGN	Nationally representative survey with a task module	—
11	SAMPLE / DATASET	Real-Time Population Survey respondents	—
12	MODEL / TOOL / VERSION	Generative AI in general	—
13	COMPARATOR	Workers in the same occupation or task who do not use it	—
14	MAIN RESULT	45% of workers use generative AI for work (62% of adults use it at all); four in five detailed occupations have adoption above 20% but only one in six above 70%; no task exceeds 70%; mean weekly hours of work use flat	—
15	INFERENTIAL TARGET	How widely and how deeply generative AI is used across US jobs and tasks	—
16	DOES NOT LICENSE	Productivity or output effects; firm-level adoption	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Self-reported use; 'shallow' refers to the share of workers adopting within an occupation or task, not to hours of use	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with other Real-Time Population Survey measures of work use cited in LD-02	—
20	GEOGRAPHY / LANGUAGE	US / English	—
21	DISTRIBUTIONAL LEDGER	Uneven adoption among workers doing the same job	—
22	R01 / FIELD-MAP LINKS	LD-03, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Later waves showing within-occupation adoption converging or weekly hours rising	—
24	PUBLICATION STATUS	ELIGIBLE WITH WORKING-PAPER QUALIFIER	state: ELIGIBLE · qualifiers: WORKING_PAPER
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-03 (LIVING_DEBATE); D2 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026” → Bick et al. (2026), “What Work Does Generative AI Do?” (SRC-SL-BICK-BLANDIN-DEMING-SCHUMACHER-STLFED-WP-2026-017--v1.0) — Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026; class WORKING_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Organizational absorption: Why micro gains do not become macro outcomes (v0.1) LD-03

Cite this page

SocioLens project. (2026, October 15). In May 2026, 45% of US workers used generative AI for work, but adoption was widespread and shallow: within most occupations and tasks fewer than half of workers used it, no task exceeded 70% adoption, and mean weekly hours among work users had stayed flat since late 2024 [Claim LD03-SL-C03, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld03-sl-c03/v1.0/

@misc{sociolens_ld03_sl_c03_v1_0,
  author = {{SocioLens project}},
  title = {In May 2026, 45\% of US workers used generative AI for work, but adoption was widespread and shallow: within most occupations and tasks fewer than half of workers used it, no task exceeded 70\% adoption, and mean weekly hours among work users had stayed flat since late 2024.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld03-sl-c03/v1.0/}},
  note = {Claim LD03-SL-C03, 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 2db2f2719030f338834702804999aea9c2d070c53ded90a652d4ef6c5b9431ee.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD03-SL-C03 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts. Block “ENTRY 03 — LD03-SL-C03” SHA-256 1bdc69617297c08eb7a01a000419af09920b17e6a458c8b9f2f38ad31e27d192; fixture fixtures/authored/claims/LD03-SL-C03--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD03-SL-C03 v1.0); the first version of a new Claim of the LD-03 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD03-SL-C03 v1.0" (Project Lead (Claude, AI), 2026-10-15); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 15 October 2026 to build the LD-03 debate; a new Claim, first version, written from the project's LD-03 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-BICK-BLANDIN-DEMING-SCHUMACHER-STLFED-WP-2026-017--v1.0 — basis: field 6 of ENTRY 03 — LD03-SL-C03 cites "Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-BICK-BLANDIN-DEMING-SCHUMACHER-STLFED-WP-2026-017--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Bick, Blandin, Deming & Schumacher, “What Work Does Generative AI Do?,” Federal Reserve Bank of St. Louis Working Paper 2026-017A, August 2026".