10163116Artificial Intelligence Identification of NeurodivergenceActiveFeasibility StudiesInnovate UKNeurodivergence, including autism, ADHD, and dyslexia, affects one in five people and is increasingly recognised as a key determinant of long-term mental health. Without timely identification and support, neurodivergent children are at significantly higher risk of developing anxiety, depression, and other chronic conditions, many of which require intensive healthcare intervention. Early identification is a critical component of preventative mental health care. This project introduces an AI-based neurodivergence identification technology to meet these needs early. In the UK, initial identification of neurodivergent traits commonly occurs within the education system. However, neurodivergence can be complex and difficult to recognise, particularly in younger children and in cases where traits are masked. Educators face considerable challenges in fulfilling their role as the first line of identification, due to limited resources and a lack of practical screening tools. Our AI digital health tool is delivered via a child-friendly and fun iPad game. The AI algorithms use motor pattern analysis to detect early indicators of neurodivergent development. They have been developed and tested in 2000 children using gold-standard diagnostic trial procedures to give a non-invasive, scalable, clinically validated identification technology, but this technology has not yet been tested in real-life situations. By enabling structured early screening in nurseries and schools, the tool will support earlier access to tailored educational interventions and timely referral to healthcare services for the best lifelong outcomes for a healthy, flourishing life. This project will test the feasibility of our technology in UK educational settings, focusing on children aged 2 to 6\. Those flagged by as potentially neurodivergent will undergo follow-up using standardised behavioural questionnaires, and those showing signs of clinical-level need will be referred for NHS evaluation. In doing so, the project helps to build a more integrated care pathway across education and health. The work aligns with the NHS Long Term Plan and the National Autism Strategy by supporting earlier, needs-based identification, reducing pressure on diagnostic services, and improving long-term outcomes through preventive care. The project will evaluate the feasibility of the tool in real-world use, gather evidence to inform future clinical and commissioning decisions, and refine the system for wider deployment across the health-education interface.