In a survey of nearly 750 corporate executives, the authors find positive labour-productivity gains from AI, reflecting revenue-based total factor productivity and expected to strengthen in 2026, but report a productivity paradox: executives perceive larger gains than are measured, which the authors attribute to a delay in revenue realizations.

SocioLens project,

Claim LD03-SL-C05 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with a qualifier
Verification state: Checked against the abstract of the primary source only. 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: Economy-wide productivity; a causal estimate
Limitations: Checked against the official abstract only, read on the NBER page on 15 October 2026; how 'measured' gains are defined and the survey vehicle were not read in full text
Source (as cited): Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026
Source type: Working paper (recorded as “Academic working paper”)
Institutional position: Mixed
Maturity of the evidence: Emerging 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

Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026 (Working paper)
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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 (QUALIFIED) (as printed: “ELIGIBLE WITH QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (ABSTRACT_ONLY)
Source type (coded): WORKING_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD03-SL-C05	—
2	PUBLIC-FACING CLAIM	In a survey of nearly 750 corporate executives, the authors find positive labour-productivity gains from AI, reflecting revenue-based total factor productivity and expected to strengthen in 2026, but report a productivity paradox: executives perceive larger gains than are measured, which the authors attribute to a delay in revenue realizations.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	B — Firm and executive outcomes	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026	source_ids: SRC-SL-BASLANDZE-ET-AL-NBER-34984
7	SOURCE TYPE	Academic working paper	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Mixed	—
9	SCOPE	Firms surveyed through their executives (country not stated in the abstract)	—
10	DESIGN	Executive survey	—
11	SAMPLE / DATASET	Nearly 750 corporate executives	—
12	MODEL / TOOL / VERSION	AI in general	—
13	COMPARATOR	Measured productivity gains, as the authors define them	—
14	MAIN RESULT	Perceived productivity gains exceed measured gains; gains reflect revenue-based total factor productivity rather than capital deepening; labour-productivity gains expected to strengthen in 2026; little evidence of near-term aggregate employment declines	—
15	INFERENTIAL TARGET	The gap between perceived and measured firm-level productivity gains	—
16	DOES NOT LICENSE	Economy-wide productivity; a causal estimate	—
17	VERIFICATION STATE	CONTENT VERIFIED ABSTRACT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: ABSTRACT_ONLY · verified_by: UNKNOWN
18	LIMITATIONS	Checked against the official abstract only, read on the NBER page on 15 October 2026; how 'measured' gains are defined and the survey vehicle were not read in full text	—
19	CONTRADICTORY / SUPPORTING SOURCES	Consistent with executives elsewhere reporting little realized impact; matches the absorption-lag reading	—
20	GEOGRAPHY / LANGUAGE	Not checked / English	—
21	DISTRIBUTIONAL LEDGER	Larger firms anticipate workforce reductions; smaller firms expect modest gains	—
22	R01 / FIELD-MAP LINKS	LD-03, D2	—
23	WHAT WOULD CHANGE THIS CLAIM?	Full-text reading of how measured gains are built, or later revenue data closing the gap	—
24	PUBLICATION STATUS	ELIGIBLE WITH QUALIFIER	state: ELIGIBLE · qualifiers: QUALIFIED
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)

“Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026” → Baslandze et al. (2026), “Artificial Intelligence…” (SRC-SL-BASLANDZE-ET-AL-NBER-34984--v1.0) — Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 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 a survey of nearly 750 corporate executives, the authors find positive labour-productivity gains from AI, reflecting revenue-based total factor productivity and expected to strengthen in 2026, but report a productivity paradox: executives perceive larger gains than are measured, which the authors attribute to a delay in revenue realizations [Claim LD03-SL-C05, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld03-sl-c05/v1.0/

@misc{sociolens_ld03_sl_c05_v1_0,
  author = {{SocioLens project}},
  title = {In a survey of nearly 750 corporate executives, the authors find positive labour-productivity gains from AI, reflecting revenue-based total factor productivity and expected to strengthen in 2026, but report a productivity paradox: executives perceive larger gains than are measured, which the authors attribute to a delay in revenue realizations.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld03-sl-c05/v1.0/}},
  note = {Claim LD03-SL-C05, 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 ac6d87dcdbc8b9c68ff4d45b75e2274426a16097e43791439fc541d098f41c33.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD03-SL-C05 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 05 — LD03-SL-C05” SHA-256 fff12cea3c0b1ac9337f3eb1e4ed050454959614c70d1a698bfba4f770dabee2; fixture fixtures/authored/claims/LD03-SL-C05--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-C05 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-C05 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-BASLANDZE-ET-AL-NBER-34984--v1.0 — basis: field 6 of ENTRY 05 — LD03-SL-C05 cites "Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-BASLANDZE-ET-AL-NBER-34984--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Baslandze, Edwards, Graham et al., “Artificial Intelligence, Productivity, and the Workforce: Evidence from Corporate Executives,” NBER Working Paper 34984, March 2026".