AI in the Labor Market in Europe : Risk and Opportunity through a Quantitative Analysis

Sammanfattning

Abstract This thesis investigates whether artificial intelligence (AI) adoption in Europe leads to job displacement or labor market transformation. During global debates on the socioeconomic implications of AI, the research poses a central question: Does AI adoption in Europe primarily reduce employment or transform it, and how do sectoral structures and policy frameworks shape this outcome? Drawing from both theoretical foundations and empirical modeling, the study examines how different economic sectors and national governance approaches mediate the labor market effects of AI integration. The empirical analysis draws on panel data simulations and case studies reflecting sectoral and national-level AI adoption trends across selected EU countries between 2015 and 2024. A difference-in-differences (DID) case study, adapted from Duong and Pham Thi (2022), provides further depth. Sectoral data on AI adoption is sourced from Eurostat and the World Economic Forum’s Future of Jobs Reports. These findings support the growing scholarly consensus that technological change is not deterministic but mediated by policy, institutions, and societal choices (Acemoglu & Restrepo, 2020; Brynjolfsson & McAfee, “The second machine age” 2014). The thesis positions the EU as a normative leader capable of guiding AI toward inclusive and ethical governance, and frames AI as a proxy for broader automation trends in contemporary labor markets. Policy recommendations include linking AI funding to mandatory reskilling programs, ensuring algorithmic transparency in employment, and addressing regional disparities in digital readiness. By combining empirical evidence with policy-oriented analysis, this thesis aims to offer useful insights for understanding how AI adoption might affect employment in Europe and how it can be guided toward more inclusive outcomes.