Illegal logging is a serious criminal activity that contributes to climate change and causes loss in biodiversity and revenue. Governments have made multiple efforts to fight this international issue, but it remains relevant and ongoing. Recent technological advances, and in particular Artificial Intelligence (AI), can bolster law enforcement and significantly enhance their effectiveness. Image processing techniques have been developed and applied to satellite imagery to monitor forest change and deforestation. These techniques include NDVI change mapping and GeoAI approaches which leverage Machine Learning technology, such as Convolutional Neural Networks. This study reviews and compares multiple methods that can potentially be used to detect and map illegal logging and highlights the use of AI in this field. We provide the essential background and details to understand the approaches that have shown to be particularly successful, such as Fully Convolutional Neural Networks. We conclude by highlighting the remaining challenges and future opportunities to further AI’s impact in the fight against illegal logging.