In Central and Eastern Europe, family-owned companies, which follow the structure of small and medium-sized enterprises (SMEs), are increasingly relying on foreign workers to address structural labour shortages; however, they generally lack the necessary HR infrastructure to support the integration of a multicultural workforce. This study examines how HR workflows augmented with artificial intelligence (AI) shape the integration of a multicultural workforce at a resource-constrained, SME-structured, family-owned company. It also examines the division of tasks, competencies, and organizational conditions that characterize these processes from the employer’s perspective. We employed an exploratory, single-case qualitative research design that combined five semi-structured interviews with the analysis of 12 company documents; we applied reflexive thematic analysis to both data sources. Three main themes emerged. First, the organization established a deliberate division of labour in which artificial intelligence handles high-volume, language-intensive tasks across six operational areas, while human actors retain control over decisions that require judgment and are culturally sensitive, thereby creating a complementary collaboration and decision-making architecture between artificial intelligence and humans. Second, HR staff and managers have developed hybrid competencies that combine proficiency in artificial intelligence with intercultural judgment. Third, transparent decision-making authority, the establishment of a consistent complementary framework, and relationship management practices have enabled repeatable, cost-effective integration workflows at the SME level. The results show that affordable, platform-based artificial intelligence tools can narrow the resource and capability gap between small and medium-sized enterprises and large corporations in the area of multicultural integration, provided that human decision-making authority is preserved and clearly delineated. Limitations of this study include its scope, which is limited to a single case; the small sample size; and its focus exclusively on the employer side. Future research should incorporate employee perspectives and adopt comparative, multi-case designs with quantitative integration performance indicators.
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Lamper et al. (2026) studied this question.
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