5 ways truck brokers are using AI to boost efficiency

Artificial intelligence is no longer a buzzword in logistics. Stakeholders are applying AI in various parts of their operations, tapping into troves of data to automate processes and become more efficient.

Truck brokers, especially large ones, are particularly well-suited to adopting AI because they already have large swaths of available data, said Dustin Burke, global co-leader for Boston Consulting Group’s manufacturing and supply chain practice and global leader of the firm’s supply chain AI team.

Within the supply chain, brokers “are doing some of the most interesting work” related to AI, Burke said. “This is increasingly just core to who they are.”

Before brokers start deploying AI, they have to ensure their data is accurate, said Peter Weis, CIO and SVP of supply chain services at ITS Logistics. Cleaning data isn’t exactly “sexy work,” Weis said, but it’s crucial. Without that base, data could be stored in disparate systems, resulting in potentially inaccurate AI model results. 

Once the data foundation is established, brokers can apply AI to multiple parts of the shipment process. 

For example, C.H. Robinson announced in October it has deployed AI technology to introduce automation across the entire freight lifecycle, from pricing to tracking loads in transit. To start, the broker focused on tasks that required a lot of back and forth utilizing unstructured data, said Megan Orth, senior director of commercial connectivity at C.H. Robinson.

Generative AI “can process so much more data than any human could possibly do,” Orth said. 

Here are five examples of how truck brokers are using AI within their operations. 

1. Freight and load matching

Burke said freight matching is the “core application” for AI investment among brokers because it improves productivity. In the past, brokers would look