In New Zealand, 40,000 – 50,000 hectares of forest is harvested each year with most areas replanted while some areas are converted to another land use. Ministry for the Environment conduct deforestation assessments every two years to monitor these changes and meet New Zealand’s international reporting obligations. In 2020 the Ministry turned to an AI based approach through Lynker Analytics to conduct an assessment of deforestation that had occurred during 2017 and 2018. Using an aerial survey, Lynker Analytics captured photography of almost 7,500 distinct areas of potential forest loss in all regions of the country. The imagery was then classified into land cover classes such as cutover, plantation seedlings, pasture, and mature native forest within each target using a Machine Learning (ML) approach. From this a multi-criteria analysis was used to assign each area of possible forest loss a dominant land cover and replant status. The model was used as the primary monitoring system to detect deforestation and re-planting and flag those targets to the Ministry. The automated monitoring system proved reliable in detecting deforestation, re-planting and other land cover changes exceeding one hectare. It also enabled more rapid assessment of replant status used by the Ministry for reporting.