Institutional 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…

By the Truvace deskOctober 16, 20262 min read1 sourcePeer-reviewedTRV-2026-1620· cite & verify

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In brief

Researchers analysed late-2025 survey data on small and medium-sized enterprises in twelve EU countries. Using a weighting and regression adjustment method, they compared firms that use AI with similar firms that do not, looking at whether headcount grew or shrank.

The results suggest AI adoption may go together with job creation rather than job loss in many SMEs, but gains are uneven across firm size, age, sector and national setting. Because the data are a single cross-section, the findings show associations and cannot prove that AI caused the hiring.

Main points

AI use was linked to a higher probability of employment growth, with no significant link to the likelihood of employment decline.
Positive effects were concentrated among small and medium firms and among young and mature firms; micro and old firms showed no significant effects.
Services and trade showed positive growth associations, while construction was the only sector tied to a significantly higher chance of employment decline.
The link was stronger where innovation performance and governance quality were higher, and weaker where employment protection was stricter and political centralisation greater.

The gain

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.

The rundown

The study used novel data from the Survey on Access to Finance of Enterprises for the last quarter of 2025, covering twelve EU countries. It applied an Inverse Probability Weighted Regression Adjustment approach, which assumes selection on observable firm characteristics.

The main finding held across alternative estimators and leave-one-country-out specifications. Effects differed strongly by firm characteristics, with micro and old firms showing no significant effect.

Institutional context mattered: countries with stronger innovation and governance saw larger associations, while stricter employment protection and greater centralisation weakened them. The authors conclude that AI integration and institutional conditions may be important for employment-enhancing digital transformation.