Key challenges with modal shifts and potential solutions3.2 The main challenges facing modal shifts are as follows: –Infrastructure limitations: many regions do not have the necessary rail or port capacity to handle large volumes of goods currently moved by road. Rail networks are often concentrated in certain areas and expanding them is restricted by geographical and urban development constraints. –Geographical factors further complicate the issue, especially for landlocked countries that lack access to ports, limiting their ability to shift from road to sea transport. –Modal flexibility is a barrier, as modern supply chains rely on adaptable solutions for first-mile and last-mile deliveries. Trucks remain essential for this flexibility, especially in e-commerce, where deliveries need to be highly responsive. Whilst modal flexibility is crucial for goods including direct-to-consumer deliveries which depend on road transport, a share of bulk items such as raw materials or heavy equipment could be moved to lower-emission modes such as rail or shipping. –Specialized goods, particularly high-value or time-sensitive items (e.g. temperature- controlled pharmaceuticals) require secure and fast modes such as air transport. Nevertheless, less time-critical imports and exports could potentially shift from air to sea for scalability and cost effectiveness. AI has the potential to allow much more efficient planning and scheduling, which will allow modal shifts and flexibility. This power of AI is why we must make sure there are powerful incentives to cut emissions – so that optimization includes emissions. Failure could lead more use of AI to higher emissions modes of transport. David Victor, Professor of Innovation and Public Policy, Global Transformation Chair in Innovation, University of California, San Diego Large retailers have made significant public commitments to achieve net-zero carbon emissions between 2030 and 2040, reflecting a broader industry trend towards sustainability driven by increasing consumer demand and investor push. Such companies are setting standards for environmental stewardship and operational efficiency, aiming to reduce their own carbon footprints and influence the entire retail and logistics ecosystem. Modal shifts, such as moving from air to ocean freight, have become viable levers for reducing carbon emissions due to advancements in storage and handling technology, improved reefer (climate controlled shipping container) capabilities and increased reliability through predictive berth planning. Despite structural barriers, there is room for improvement – and AI could play a critical role in overcoming challenges around modal flexibility. AI-powered solutions can manage the vast data and complexity associated with optimizing global transportation networks, making it possible to integrate lower-emission modes without compromising business efficiency. This could allow companies to make dynamic adjustments, identifying opportunities to shift from road or air to rail or sea, maximizing carbon savings without increasing costs or delivery times and consistently making the most rational emissions- reducing decisions. We extensively consider all three modalities for our customers while developing the solutions. Modal shifts are a huge lever for both cost reduction and decarbonization. Carsten Lützenkirchen, Senior Vice President, Commercial Operations Customer Solutions & Innovation, DHL Intelligent Transport, Greener Future: AI as a Catalyst to Decarbonize Global Logistics 18

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