­European countries. Search terms included a variety of keywords, such as‘automation’,‘AI’,‘robotics’,‘women’, ‘gender’,‘discrimination’,‘workplace’,‘skills’,‘transition’, ‘EU’, and‘equality’; these represent only a subset of the many terms used, reflecting the interdisciplinary and ­intersectional focus of the study. Studies examining ­labour market dynamics primarily in non-EU contexts were excluded from the review. The review process followed a two-stage screening ap­proach. First, titles and abstracts were reviewed for rele­vance against the inclusion criteria. Second, a full-text review was conducted on shortlisted studies to confirm their alignment with the research questions. An Excel spreadsheet was used systematically to document the details of each included study, recording information such as publication type, authors, year, title, journal, keywords and abstracts. Key themes and concepts were extracted from the se­lected literature and organised into analytical categories. Although the primary focus was on literature explicitly addressing women and automation, the review also in­corporated studies that, while not solely focused on women, contributed valuable insights into the gendered dimensions of automation and labour market dynamics. In total, an initial pool of 1,020 sources was identified. Following the screening process, 600 studies were re ­viewed, and ultimately 65 studies were included in the final analysis. The findings are presented in a narrative synthesis, mapping the main concepts, sectors and geo­graphical regions covered in the literature. This compre­hensive approach allowed for a detailed exploration of how the topic has been conceptualised and addressed across the scholarly and grey literature, providing a ro­bust foundation for identifying critical gaps and future research directions. Overview of the key research areas An examination of the collected sources reveals that ­job displacement remains a central concern. There has been considerable research into the potential scale of workforce disruption, nationally and internationally. Nevertheless, gender-focused analyses are relatively scarce, and the findings that have been obtained are ­often inconclusive. This is partly because of a tendency to overgeneralise global trends without accounting suf­ficiently for the specific complexities of the European market. Automation does not occur in isolation but is shaped by institutional contexts, including gender equal­ity in employment and education within the European Union, as well as the influence of welfare regimes and industrial relations systems. The evidence base is further constrained by its limited and inconsistent coverage across technological domains, sectors and industries. Many studies overlook regional variations, such as ­rural–urban disparities and firm-level differences, which are crucial for capturing the full impact of automation on workers, both men and women. To address these gaps, incorporating an intersectional approach is essen­tial to understand women’s diverse experiences across EU Member States and sectors. Particularly valuable in this respect are mixed-method designs that integrate qualitative case studies for a nuanced, context-specific understanding of women’s experiences. Analysis of the collected research papers has identified four key themes concerning automation technologies and their potential impact on women’s participation in the labour market. The first concerns workers’ adaptability in the context ­of workplace automation. However, an exclusive focus on individual capabilities, with gender treated merely as one socio-demographic category among others, is insuf­ficient to capture the complexity of different sectors, as well as the differences between EU Member States. The institutional context is central in shaping labour market outcomes and must be incorporated into any analysis. ­In particular, welfare regimes and industrial relations systems shape gender regimes both at the European lev­el and within individual EU Member States. Their influ­ence is crucial when evaluating the implications of tech­nological change for women’s employment trajectories. The second examines gender employment and wage gaps in the face of technological change. While emerg­ing technologies reshape work and wages, research of­ten focuses on STEM and manufacturing, overlooking the service and care sectors, which are female-dominat­ed. Empirical studies largely address industrial robots, neglecting other types of technologies, including AI in health care, education and administration. Addressing these gaps is ­essential to ensure that technological pro­gress supports rather than undermines gender equality in the labour market. The third topic is the relationship between automation technologies and occupational safety and health(OSH), paying particular attention to how women experience ­new risks. The health impacts of automation are rarely analysed through a gender lens, despite evidence that women and men face distinct physical and psychological hazards because of differences in job roles, societal re­sponsibilities and expectations. Gender bias in robotics and data-intensive technologies can exacerbate these risks, whether through physical design, such as equipment tailored to average male dimensions, or through algorith­mic design based on unbalanced historical datasets. The fourth examines the implications for an ageing work­force in the context of technological change. The demographic shift in Europe is leading to significant economic challenges, but no comprehensive framework exists to address the dual pressures of extended working Overview of the key research areas 7