Care homes and home-care agencies in the UK, Sweden and Finland are increasingly using AI platforms to schedule staff, match workers with clients, and automate payroll—but no one has systematically studied whether these tools improve or degrade job quality. The CareQuAI project will open that “black box” by comparing how algorithmic management works across three countries, conducting case studies inside care organisations, and involving care workers themselves in designing fairer digital tools. This matters because long-term care for older people is in crisis across Europe: chronic staff shortages, high turnover, and poor working conditions are all linked to worse care for patients. The platform economy in domestic services has nearly doubled in size since 2016, yet the evidence on whether AI helps or harms is contradictory. Some platforms offer higher wages through optimised scheduling; others erode labour protections, introduce algorithmic bias, or risk data breaches. If successful, CareQuAI will produce practical guidelines for policymakers, care providers, and unions on how to design AI platforms that support decent work—fair pay, predictable hours, and worker voice. That could improve recruitment and retention in a sector where staff turnover directly affects the quality of care that older people receive.
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CareQuAI will open “the black box” of AI-driven platform care services, through cross-national comparison, organisational case studies, stakeholder involvement and the participation of care workers in the development of equal and inclusive platform care digital-technologies. AI-driven platform care are identified as online services that use ‘algorithmic management’ to predict workflow needs, match supply (workers’ availability and capacity) and demand (people seeking care), and automated administrative functions. This project explores the technological affordances, opportunities and social consequences of platform care in three European countries: the UK, Sweden and Finland. As in Europe, the long term care (LTC) for older people delivered in these countries is considered to be ‘in crisis’ (United Nations, 2018). Demographic changes, a shortage of institutional and community services, high costs and poor quality of care have reinforced the challenge of providing affordable LTC, and the covid-19 pandemic has further deteriorated the working conditions and exacerbated labour force shortages. Imperatively, job quality and levels of staff turnover are also shown to be interrelated with quality of care (Allan & Vadean, 2023; Burns et al 2016) and an important focus for change recognised by labour trade unions and policy-building organisations. In this crisis context the size of the EU platform economy in the domestic and home services sector has increased from EUR 0.8 to 1.5 billion between 2016-2020 (European Care Strategy, 2022). AI-driven platforms are increasingly employed by care companies, care workers, and service users and their family members, and are presented as offering solutions to the interlinked challenges of workforce shortages and job quality. Platform work has been presented as offering higher wages than conventional employment (De Groen et al. 2018) through optimised scheduling and decreased manual administration. Yet platform work also challenges existing rights and obligations related to labour law, social protection and health and safety as empirical research evidences heightened risks for workers and the informalisation of work (Macdonald, 2021). Other challenges relate to the forms of AI used to enable matching of care worker to people seeking care using machine learning, which has shown to be problematic due to algorithmic bias in big data sets (Norori et al. 2021). Large language models that generate coherent text and speech by using prompts as a mechanism for inferring the context, are expected to become part of any AI-driven platform in the future. However, they are also found to contribute to risk for private data breach and increasing inequalities: e.g., by perpetuating gender stereotypes and social biases (Weildinger et al. 2022). Given the increased use in AI by care providers, a clear, evidence-based understanding of the risks and opportunities that platform services offer for LTC are essential. Informed by the International Labour Organisation’s ‘Decent Work Framework’, CareQuAI will examine the potential of AI-driven platforms to generate good quality jobs and will produce solution-focused guidelines and recommendations responding to issues of equality and inclusion. CareQuAI has three objectives: to analyse cross-national differences in how AI-driven platform care is provided; to produce cross-national guidelines on equal and inclusive AI-driven platform work in LTC; to contribute to policy, practice and frameworks that support decent work via AI-driven care platforms. The outcomes will produce both novel insights and practical-solution focused recommendations for equal and inclusive platform care, improved job quality and worker rights – critical factors which underlie effective recruitment and retention.
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