This project investigates the role of Artificial Intelligence (AI) and Algorithmic Management (AM) in future-proofing long-term care (LTC). The sector faces multiple challenges: an ageing population, limited productivity gains in a labour-intensive sector, labour shortages, and the crisis of traditional modes of care provision amid rising female employment rates. We will identify key challenges and explore AI/AM’s potential to help the sector respond to long-standing and growing workforce challenges, improve its value proposition and care quality. Findings will inform industry standards, care models and best practices to inform viable and high-quality care solutions.
This comparative study compares efforts in five countries (Austria, Belgium, Sweden, Spain and the UK) to address issues affecting the sustainability of LTC. These countries represent distinct care, welfare and industrial relations regimes. A key research focus is to explore the challenges and potential of AM/AI to (i) address recruitment & retention challenges through enhancing working conditions and (ii) improve care quality with potentially better outcomes for workers, care recipients and their families.
In each country, case studies of care providers will be conducted, covering emerging patform-based services as well as more traditional long-term care services in their respective national and sectoral context. Special attention will be paid to certain dimensions of job quality relevant to AM/AI: intrinsic elements (OH&S, work intensification, surveillance, workers’ consultative rights and voice) and extrinsic elements (wages, working hours, benefits, employment conditions, skills).
ZSI contributes to all work packages in the project, conducts the fieldwork (expert interviews and case studies) in Austria, and will organise two national stakeholder workshops in Austria.
