aceInstitutional context and the employment effects of artificial intelligence in European SMEs
Using novel data from the Survey on Access to Finance of Enterprises covering the last quarter of 2025 and an Inverse Probability Weighted Regression Adjustment approach, we assess the conditional treatment effects of artificial intelligence (AI) use on the likelihood of employment growth among Small and Medium-sized Enterprises across twelve EU countries, under selection on observable firm characteristics. Given the cross-sectional nature of the data and the contemporaneous measurement of AI use and employment…
SMEs using AI across twelve EU countries were more likely to report employment growth, especially small, medium, young and mature firms and those in services and trade.
AI use and employment change were measured at the same time in cross-sectional data, so the estimates are conditional associations rather than definitive causal effects.
Evidence
- Peer-reviewedTelecommunications Policy2026-10-15
How should this claim be treated?
Truvace Impact Record TRV-2026-1620, v1: “Institutional context and the employment effects of artificial intelligence in European SMEs.” Truvace, 2026-10-16. /record/TRV-2026-1620 (accessed at citation time). sha256 93296267cc4229db…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1620 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.