AI needs data centres, servers, cooling, electricity, spare parts, specialist transport, warehouse space, assembly, international supply chains and people who coordinate all of it.
DHL Supply Chain is adding warehouse capacity in North America for this market: data-centre components, server racks, sensitive equipment and international supply chains.
Digital expansion creates physical logistics demand. As companies use more AI, the supporting infrastructure grows, increasing the need for reliable logistics processes.
The interfaces are particularly complex: international supply chains, sensitive cargo, tight time windows, construction-site coordination, specialist handling, documents, permits and technical dependencies.
These processes involve multiple systems and increase the clarification burden. AI can also help teams manage that growing work.
AI know-how for logistics professionals in 2 minutes
What is a context window?
A context window describes how much information an AI model can consider in one operation.
Earlier models handled relatively short texts. Modern models can take in longer documents, several emails, spreadsheets and extracts from systems.
More context still requires careful selection. A model given too much disorganised information may assign importance to the wrong details.
For logistics, relevant information needs to be assembled clearly. Good AI work starts with data quality, process knowledge and clear questions before the prompt is written.