Writing in Fortune, Dave Bozeman, president and chief executive of C.H. Robinson, argues that speed on its own does not produce better business outcomes and that the real return on artificial intelligence shows up when companies use it to strengthen human decision-making. He applies the claim most directly to supply chains, where he says the daily work turns on judgment under shifting conditions rather than on problems a faster system can settle by itself. The distinction matters, in his account, because much of the current enthusiasm treats faster answers as an end rather than a means.
Bozeman grounds the case in the scale of his own company, which he says handles 37 million shipments a year. That volume, in his account, exposes how much complexity sits inside modern commerce, since each shipment can carry its own timing, cost, and risk considerations. He writes that C.H. Robinson trained its AI systems on hundreds of trillions of proprietary data points, which he presents as a way to keep the technology’s recommendations tied to real operating context instead of generic output.
The obstacles that matter in logistics, according to Bozeman, are business problems before they are technical ones. He points to tariff changes, port closures, and capacity constraints as examples of disruptions that call for weighing trade-offs and relationships, not only computation. In his framing an AI system can surface options quickly, but a person still has to decide which option fits a given customer’s situation, and that judgment is where he locates the difference between a useful tool and a costly one.
Capturing value, Bozeman argues, requires redesigning workflows rather than layering new tools onto existing routines. He describes using AI for repetitive automation while reserving human effort for building partnerships and for working through problems that lack clean answers. The competitive edge, he writes, belongs to organizations that combine technology, context, and human expertise, rather than to those that simply hold the most advanced systems. A more sophisticated system, on its own, is not the point of his argument.
The piece frames AI’s ultimate contribution as amplified human potential rather than replacement. Bozeman positions his view against the assumption that automation’s main promise is cutting people out of the process, and he concludes that companies willing to keep human expertise at the center of their operations will get more from the technology than those chasing efficiency alone. For readers running any complex operation, his message is that the tool follows the judgment, not the other way around.
