Growing interest in lignocellulosic bioethanol production is driving advancements in biomass logistics and transportation. Establishing preprocessing stations for biomass densification enables efficient, long-distance delivery to biorefineries, enhancing supply chain performance. Upgrading infrastructure and adopting decentralised conversion approaches facilitate local sourcing, improve biomass flow, and reduce pressure on energy systems. Artificial intelligence and machine learning analyse environmental data to develop sustainable practices, optimise transportation routes, and reduce greenhouse gas emissions. Locating processing facilities near biomass sources reduces transport distances, while AI-driven modelling improves logistics planning, route efficiency, and inventory management. A hybrid logistics model that integrates decentralised and centralised strategies, including regional depots for pretreatment, balances economies of scale with reduced transportation costs.