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 at demand and available capability and match the two but with “little technology behind [the process],” Burke said.
By adding a more tech-focused approach by introducing algorithms, AI has taken load matching a step further by applying forecasting. Brokers can match freight not only based on historical and current data, but also through predictions on how loads and capacity on a particular lane may change in the future.
2. Quoting
Prior to the October announcement, C.H. Robinson had begun using AI to automate the quoting process — an area where the logistics industry has fallen behind, Orth said. In most other sectors, a customer can check prices or get instant quotes online.
“Those customer expectations are now pushing their way into our industry,” Orth said.
C.H. Robinson is using large language models to classify emails to identify quote requests. Then, the company uses generative AI to read the emails and quickly respond to customers with quotes, resulting in replies to 2,000 emailed quote requests every day. The responses included a note saying the quotes are AI generated.
3. Carrier recommendations
As C.H. Robinson receives orders from shippers, it uses genAI to recommend loads to carriers.
“The carriers love that,” Orth said, because instead of having to search for loads, they receive AI-driven freight recommendations via text or email.
4. Chatbots
GenAI and advanced chatbots give shippers and carriers the ability to ask questions and get answers in real time. For example, what if a shipper wanted to ask how much it would cost to send a load tomorrow instead of Thursday from Dallas to Chicago?
“You can still have a customer ask a person at the brokerage about that, but you might not have to,” Burke said.
Brokers can use chat-related features internally as well, a tactic ITS is utilizing. Instead of manually developing reports, employees can ask questions about top customers or most profitable lanes, and the AI platform will generate an answer, Weis said.
Ryder has a similar feature. Employees can ask an AI platform to plan an optimal route or identify customers with the largest costs, and call center AI agents can summarize call logs to improve customer service.
5. Trailer management
ITS has grown its trailer network from a few hundred vehicles a year ago to about 3,000 today, and AI has helped it manage its growing fleet. More specifically, the company uses AI models to pull data from shipper orders to determine where trailers should be located.
“We can't pay for a bunch of empty trailers all spread out in the wrong locations,” Weis said. “AI is absolutely crucial.”
AI on the agenda
As generational shifts take place in the workplace, Burke anticipates shippers and carriers will move even more of their communication from phone to online, opening the doors to additional AI uses cases.
CHR plans to continue looking at high-touch aspects of the shipment lifecycle where AI can accelerate responses. The broker also seeks to use AI to decipher PDFs, documents and even handwritten notes, Orth said.
Weis said customer pricing is next on ITS’ agenda. Its AI platform already makes recommendations related to carrier costing but not shipper pricing. Tying AI into RFP responses could also be a future use case.
The solutions, ultimately, have to meet brokers’ goals of providing the best customer service to clients.
“We want to be the broker of choice, both for our customers and for our carriers, because you never know in this business who has the leverage,” Weis said. “You've got to be nice to everybody.”
