Paleo-datasets are important for understanding long-term ecological systems and their interactions with climate and human activity. Yet, these paleo-datasets are difficult to create as identification of fossil pollen and phytoliths is very labour-intensive and time-consuming. Errors may also accumulate due to manual errors. Use of AI/ML techniques can speed up the identification of pollen and phytolith taxa, and may also help identify pollen taxa at higher taxonomical resolutions than can be done manually. AI/ML tools may also be used to identify and quantify micro-charcoal of different sizes. This session brings together experiences from across the globe with the aim of expediting the creation of paleo-datasets that further our understanding of climate change and biodiversity, and inform landscape management.