The Impact of New Technologies on Migrant Employment in the EU

This spotlight analyses the impact of new technologies on the employment of migrant and native workers in the EU. First, the level of labour migration in selected EU member states (including Austria) and how it has developed in recent years is presented. It then summarises how new technologies are affecting domestic and migrant labour while focusing on the influence of innovations and robotisation.

Technological Advancements and Migrant Employment: An EU Perspective

The impact of technological advancement, such as robotisation and digitalisation, on migrant employment will almost certainly reshape the labour market dynamics within the European Union (EU). The transformation brought about by these novel technologies has been profound, particularly in industries like manufacturing, where the potential substitution of workers and migrant workers, in particular, by robots could lead migrants to seek an alternative. Analysing such a scenario requires a deeper knowledge of the specific migrant jobs affected by these technologies, which is investigated in detail in Ghodsi et al. (2024).

Migrants are often employed in specific tasks that may be particularly vulnerable to automation or necessitate digital skills. Identifying the migrant jobs linked to technological adoption offers insights into the potential risks and opportunities for this segment of the workforce in an economy increasingly characterised by automation and digitalisation. This is particularly important for the EU labour market, as the share of migrant workers in the EU has increased from less than 9% in 2005 to about 14% in 2019 (see Figure 1 below), according to the EU Labour Force Survey (EU-LFS).

The Role Of Migrant Workers In Selected EU Countries

Figure 2 reveals significant variations in the shares of migrant worker across EU countries, with Luxembourg leading at 52%. This is significantly higher than Austria (19%) and Sweden (18%), while Slovakia, Czechia and Lithuania had the lowest shares, which ranged from 1% to 4%. Austria thereby has the second-largest share of migrant workers in the EU in terms of total workforce. Luxembourg, uniquely, had more EU than non-EU migrant workers, largely due to its attractive location, high wages and the presence of EU institutions, all of which naturally make it a prime destination for skilled workers. In contrast, the Baltic states and Slovakia have the lowest shares of EU migrant workers, at less than 1%. Non-EU migrant workers predominated in Sweden, Germany, Spain and Austria, with shares of up to 13%, with the reasons often having to do with geographical and historical connections with non-EU countries.

The distribution of migrant workers across occupations and countries from 2015 to 2019 shows heterogeneous employment patterns. As documented in Figure 3, migrant workers were predominantly found in service and sales occupations (ISCO 5), with shares ranging from above 30% in countries such as Greece and Spain to just over 10% in Lithuania and Slovenia. The lowest employment level of migrant workers was in skilled agricultural, forestry and fishery sectors (ISCO 6). A significant number also held high-skill professional roles (ISCO 2), especially in Luxembourg, which had the highest proportion (46%), as well as in Lithuania and Denmark (both 28%).

In terms of overall employment, as Figure 4 shows, migrants were mostly employed in lower-skilled roles, such as service and sales positions (ISCO 5) and elementary occupations (ISCO 9). While having migrants make up 75% of the total workforce for the latter category, Luxembourg also had an unusually high percentage (83%) of migrant workers in high-skill managerial positions (ISCO 1), vastly outstripping other nations.

As Figure 5 and Figure 6 show, migrant distribution also varied by the migrants’ education levels. While most countries showed a prevalence of migrants with medium education levels, Italy, Greece and Spain had higher proportions of low-educated migrants, which has to do with these countries’ geographical proximity to countries with lower average education levels. In contrast, Luxembourg had a notably high percentage (55%) of highly educated migrants, which suggests a mismatch, as this exceeds the proportion in high-skill occupations, which in turn indicates potential overeducation.

The Dual Impact of the Technological Revolution on Native and Migrant Workers

Given these differences in employment patterns, the technological revolution is expected to impact employment opportunities for both native and migrant workers in different ways. Analysing this relationship allows for an assessment of potential labour market outcomes and the identification of disparities, thereby informing policy decisions aimed at mitigating negative impacts while fostering inclusive growth. This is important, as the integration of migrant workers into the labour market and society at large is closely linked with their employment prospects. Thus, understanding how technological adoption affects migrant employment patterns is crucial for addressing challenges related to social integration, economic well-being and societal cohesion. In this respect, the findings in Ghodsi et al. (2024) can be summarised as follows:

First, innovations boost migrant employment. The study reveals that technological innovations, quantified by the number of granted patents, tend to increase both the absolute number and the proportion of migrant workers within the workforce. This indicates a positive correlation between novel technologies and migrant employment opportunities.

Second, robots replace jobs, but less so for migrants. While robot adoption does lead to job displacement, the impact is more pronounced for native workers than for migrant workers. This results in a relative increase in the share of migrant workers, suggesting that migrant jobs and tasks may be less vulnerable to automation-related displacements.

Third, digitalisation shows mixed effects. The adoption of digital assets shows heterogeneous effects on migrant employment; while some digital technologies positively influencing migrant employment, others do not have any significant impact.

The research highlights the diverse effects of technological change on migrant employment, providing crucial insights for policies aiming to foster economic inclusivity and social cohesion. To support skill development, it is imperative for policy makers to promote lifelong learning and skills enhancement among both native and migrant workers, thereby enhancing their ability to adapt to technological shifts. Support needs to be directed towards groups most vulnerable to the impacts of automation and digitalisation, particularly in the most affected sectors and occupations. Re-training and up-skilling are also needed to help both native and migrant workers to adopt new technologies.


Mahdi Ghodsi is an economist at the Vienna Institute of International Economic Studies, a lecturer at the Vienna University of Economics and Business, and Senior Fellow and Head of the Economy Unit at the Center for Middle East and Global Order.

Robert Stehrer is Scientific Director at the Vienna Institute of International Economic Studies.

The interactive graphics were created by Alireza Sabouniha. He is research assistant at wiiw and recently completed his master’s degree in Economics at the WU (Vienna University of Economics and Business).