The Kenyan Govt has an ambitious program to improve road and rail connectivity across Kenya, as a key pillar to stimulate the economy. The Nairobi-Nakuru-Mau Summit Project involves the dualling of a 175 km portion of A8 Highway and the strengthening of a 58 km section of the A8-South Highway between Rironi and Naivasha. The A8 Highway is part of the Northern Corridor which is one of the busiest and most important transport corridors in East and Central Africa, providing a gateway through Kenya to neighboring landlocked economies. The project is currently being planned and designed, including the preparation of a comprehensive environmental and social impact assessment (ESIA). The ecological components of the ESIA includes surveys of flora, fauna and habitat, as well as a fauna connectivity study to identify locations along the highway where wildlife are likely to occur and where safe movement across the highway is critical to species persistence and human safety. This fauna connectivity study includes numerous firsts and will set a standard for future ESIA’s in developing countries and beyond, including: the formal engagement of transport-ecologists from Africa as a ‘brains trust’ to guide the project; deployment of internet-enabled remote camera traps which transmit photos to the cloud; the use of artificial intelligence (AI) procedures to sort photos and identify target fauna; the use of systematic surveys, existing data and expert opinion to develop habitat suitability models to predict the occurrence of wildlife and movement pathways; and most importantly, the use of rigorous statistical methods to identify fauna crossing locations to inform the planning and design of the road. Fifty cameras were deployed in February 2021 and 67,000 detections of wildlife were made by the end of April 2021. The AI techniques have been developed and refined, and the accuracy of images quantified, with true positive rates for key species, which range so far between 71% for African Buffalo and 86% for Giraffe. A major challenge in this project was the lack of systematically collected wildlife occurrence points and paramaterising the connectivity model, which was overcome through the use of a participatory mapping tool called Maptionnaire to engage with local experts. In this presentation, we describe the approach to collect data and develop habitat suitability models, which were used to inform the fauna connectivity study. The final results of the connectivity study will be presented, as well as lessons learnt for future projects. A significant outcome of this project is the ability to use statistical methods to quantify connectivity, even in landscapes where little formal data exists. This project has set a benchmark that impact assessments for linear infrastructure projects in the developing world must emulate if they are to be considered best-practice.