The aim of the project is to create an AI-hub that promotes the smart use of SOTE data in Central Finland. Regional AI-Hubs in Central Finland and North Savo interact with each other, which aims to promote the creation of larger and more diverse datasets. This will enable the development of more accurate and reliable AI models and the generation of new data to prevent, treat and optimise the cost impact of diseases. In order to achieve the results, AI HUB in Central Finland works closely with regional actors (central hospitals, biobanks, various SOTE operators, companies). The aim is to produce new information on how different SOTE actors can make AI-supported solutions at provincial, municipal and individual level and develop computational decision support models that allow assessment of the effectiveness of customer group interventions and decisions. Key roles are the identification of customers’ risks and customer segmentation, the identification of treatment episodes for different customer groups, the creation of different intervention scenarios, and the operational and financial evaluation of the different decision options. It will also explore how AI-based technologies can enhance the analysis of clinical data and biobank data, how these data can be complemented by other open or self-collected data, and their potential in the development of AI applications. The project will focus on promising application areas identified on the basis of a previous study in the region, such as enhancing treatment processes, cancer treatment, and prevention of osteoarthritis. The project will activate companies in the region to utilise artificial intelligence and computational methods in their own business processes and products in the field of social services. The starting point for the planning of the project has been the needs of the regional social services organiser, business field and business. The project will result in new computational decision support models, information on the potential of clinical data and biobank data in the development of AI methods, new operating models for the exploitation of different data sources and, where possible, open databases for the benefit of companies and researchers.