The rapid expansion of AI is transforming labour markets and welfare institutions. The automation of routine and complex tasks is eliminating certain professions and increasing demand for high-skilled roles, deepening the polarization of the workforce. This, combined with the Industry 4.0, is shrinking middle-skilled jobs and expanding platform-based precarious jobs. This threatens the sustainability of traditional employment-based, contributory social insurance regimes and increases the pressures on welfare states.

Drawing on comparative political economy and social policy literatures, this paper examines the capacity of welfare states to cope with this change through three key dynamics: Primarily, labour market transformations challenge the sustainability of traditional social insurance programs. Secondly, while AI offers new governance opportunities, such as guidance in welfare analysis, personalized public services, efficient audits, and efficiency in healthcare systems, it also raise ethical and privacy concerns. Third, the unequal distribution of AI globally has the potential to exacerbate existing international inequalities, particularly in the South. Furthermore, the risk of AI shrinking the premium base threatens the intergenerational solidarity that underpins Bismarkian welfare regimes.

To address these challanges, the study highlights the need for welfare states to develop a diverse typology of adaptation strategies, ranging from defensive measures (i.e.,universal basic income, AI taxation) to proactive investments (lifelong learning, digital inclusion). Ultimately, the study concludes that while AI poses a disruptive threat, if integrated into inclusive sustainable policy designs, it can act as a catalyst for the renewal of welfare institutions and address the debates on the decline of the welfare state.