Every year DHL, the planet’s largest logistics firm, moves roughly 1.8bn parcels across 220 countries and territories. Each one follows a route planned almost to the minute, from the hub where it is sorted to the van that delivers it. Coordinating this has long relied on operations research, a branch of applied mathematics shaped in wartime and later used to run global supply chains. Now DHL is adding artificial intelligence (AI) to its operations.
The technology can improve many aspects of delivery, but unlike the explicit models and paper trails that preceded it, AI’s judgments are probabilistic, its reasoning is hard to explain and its errors cannot always be traced. This poses a question that extends far beyond logistics: how can firms deploy AI systems responsibly when the technology itself resists easy oversight?
DHL’s emerging answer is shaped by Shreya Ruikar, who leads AI initiatives across the firm. In conversation with Economist Enterprise, she shuns grand rhetoric and describes responsibility as a practical framework that helps make AI usable at scale. It is built around lightweight governance that turns anxieties into decisions, safeguards that tighten as the cost of a mistake rises and feedback loops that expose AI’s flaws before they spread. Taken together, DHL’s approach offers lessons for any organisation wrestling with the gap between the technology’s promise and the messy reality of its use.