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)

Research opportunities this claim motivates

What this claim leaves open for research. Each is a hypothesis about a gap, not a finding.

Is there a generative-AI productivity J-curve inside firms?Executives perceive larger productivity gains from AI than their firms' data show and attribute the difference to a delay in revenue.

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)
Read the original

Version

This is the current version, v1.0. Earlier versions stay available, and their records never change.

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".