Making sense of unstructured oceans of data is the greatest need supply chain managers have when it comes to artificial intelligence, says Chris Cutshaw, vice president of market solutions at C.H. Robinson.

One of the most interesting developments in supply chain, Cutshaw says, is that it has been “democratized” in the last five years. Many of the large-language models that are available can be accessed by more users than ever before, which makes it “easier to get speed to value.

“Tons of parties” are responsible for coordinating products and services and getting them to different markets, all the while using data from disparate sources. “It’s a really good first focus for AI to bring unstructured data together, and help keep products and goods moving and aligning to a core strategy.”

While there are many needs in the supply chain for artificial intelligence, Cutshaw believes taking unstructured data from disparate sources and making sense of it in real time is probably paramount. “That’s a challenge today. We're trying to connect different parties through different means, but if I don't need to focus on that integration and can run it through an AI model to give me that same output, that's the immediate focus for supply chain leaders today.” 

Supply chains are inundated with data – “noise,” to use Cutshaw’s term – and it’s vital to find a signal in the middle of that din. “We're trying to find [one] that's going to have meaningful impact to customer deliveries, to customer experience, to total land cost, to cost savings. AI starts to make sense of all that, and allows us to focus on the things that matter.”

Cutshaw believes the future of supply chains is in autonomous agent-to-agent communication. “Humans are going to set the strategy, but a lot of the day-to-day execution and decisions are going to be transitioned to AI.”