Artificial Intelligence and Labor Productivity in Construction: A Comparative Systems Analysis Across European Economies
Claudiu George Bocean, Adriana Scrioșteanu, Sorina Gîrboveanu, Marius Mitrache, Mirela Sîrbu, Ionuț-Cosmin Băloi, Adrian Florin Budică-Iacob, Maria Magdalena Criveanu · Systems · 10 Jul 2026
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Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding goes against the claim (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Abstract
The rapid expansion of artificial intelligence (AI) is revolutionizing economic systems by reshaping production, labor organization, and productivity patterns. In the construction industry, which remains highly labor-intensive, project-based, and structurally heterogeneous across European countries, AI can support productivity, planning, safety monitoring, cost estimation, and decision-making. However, its implementation also poses specific challenges, including fragmented workflows, heterogeneous construction sites, limited digital skills, poor data interoperability, high adoption costs, resistance to organizational change, and temporary adjustment costs that may delay the visibility of productivity gains. In this paper, we evaluate the effect of Artificial Intelligence (AI) on labor productivity in the construction sector of European Union countries, taking into account labor input and sector output, and search for structural trends from a systems perspective. AI adoption is defined as the share of construction businesses that use at least one AI technology. Productivity is estimated per worker and per hour using a dataset of EU countries from 2023 to 2024. The effects of AI adoption, labor input, and output on productivity are evaluated using multivariate log-linear regressions in SPSS. Hierarchical and K-means clustering reveal groups of countries with comparable digital and labor performance. The results demonstrate that construction output is the key driver of labor productivity. In contrast, AI adoption shows a small, negative association with productivity, consistent with short-term adjustment costs in the early stages of digital transformation. Cluster analysis reveals diverse country profiles in AI use, productivity, and labor intensity. Overall, the findings underscore the need for a gradual approach to managing digital change in construction, supported by complementary organizational and skills-based measures.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
- Published
- 2026 (3 months ago)
- Citations
- 0 (OpenAlex)
0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison.
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