ppetite to think about safe and ethical use cases for AI within Children’s Social Care (CSC) practice. Aims This pilot aimed to create two proof-of-concept tools: one that provides a search function for previously unsearchable unstructured data and difficult to search structured data; and a second tool that creates auto-generated ecomaps showing the networks around children from information held within a CSC case management system. In the short term, it is expected that implementation of these tools would reduce the amount of time social workers spend looking for information, reduce their administrative workload and help them understand networks better. In the medium term, the tool hopes to improve outcomes for children through better understanding of the networks around children and families, increase the number of people within children’s networks, increase the percentage of time social workers can spend with children and families and increase the wellbeing of social workers. The longer-term impacts of this tool could lead to the modernisation of how case management is perceived as well as influencing the wider approach to technology enabled social care and the dissemination of the tool to other areas of the council such as Adult Social Care and to other Local Authorities or organisations. Methodology This innovation work has used co-production principles and Agile methodologies such as MoSCoW analysis for requirements. A detailed benefits plan was developed with baselines identified to measure success. The evaluation has assessed the following evidence:  Case study workshops with individual social worker teams  Surveyed 981 Children and Young People’s Services (CYPS) colleagues - 218 responses  Initial user feedback from CYPS locality events - 211 responses  Cont