Supply chain projects involving generative artificial intelligence (GenAI) are gaining steam, and many early movers are already putting the technology to work serving clients. Logistics service providers are among those pushing forward with tools that are helping to improve the customer experience, applying GenAI to freight shipping tasks—such as quoting, taking orders, and booking appointments—and to sales-development activities.
Streamlining work and creating more efficient processes are at the heart of those advances.
“[GenAI] allows us, as humans, to be more efficient—to work faster,” explains Eric Walters, vice president of analytics and performance management at contract logistics specialist DHL Supply Chain, which introduced a suite of GenAI tools late last year. “For example, you could ask an associate to read through a document and summarize it for you, [but] AI does it faster. Data management is another example. Similar to how a human could comb through data and fill in the gaps—GenAI can do this for us too.”
Traditional AI and GenAI top today’s list of supply chain investment priorities, according to a 2024 survey by research and advisory firm Gartner, which polled more than 400 supply chain leaders responsible for their organization’s digital supply chain strategies. Twenty percent cited traditional AI, including machine learning, as a top priority, and 17% said GenAI projects are getting the most attention these days.
AUTOMATING THE FREIGHT CYCLE
Logistics industry projects are in line with what’s happening with GenAI investments in the broader world, according to the technology research and advisory firm Information Services Group (ISG). In a study released in November, ISG found that that most projects are focused on text-based applications because of their relatively simple interfaces, rapid return on investment, and usefulness.
“Companies have been especially aggressive in implementing chatbots powered by large language models (LLMs), which can provide personalized assistance, customer support, and automated communication on a massive scale,” ISG said in its report on the study.
Large companies with lots of data and a staff of software developers are tackling those projects in house, building LLMs—a type of AI algorithm that can process and understand language or text—that “learn” from all that data and then apply what they’ve learned to solving problems. Freight broker and third-party logistics service provider (3PL) C.H. Robinson is a case in point. The 3PL has launched several homegrown GenAI tools over the past year that can analyze unstructured data, such as emailed text, to speed and streamline the freight shipment cycle.
“We still have customers who want to do things manually—for example, via email,” explains Megan Orth, director of digital connectivity for C.H. Robinson. “GenAI allows us to meet the customer where they are. They get the same [level of customer service] they would get if they were digitally enabled.
“This is different from what other companies [have done]. Some started with chatbots, for example. We took a different approach, [focusing on ways to reduce] the manual tasks and touches in our system.”
C.H. Robinson began with quoting, building an LLM to identify quote-request emails and using GenAI to read the email and respond. The technology eliminates the time-consuming steps of having an employee open and read the email, swivel to another screen, type in the quote request, and then swivel back to send an email response with the price.
“We focused on that swivel—going from one system to another and using the GenAI to read, grab, and go,” Orth explains. “Then we started applying it to the remainder of the shipment cycle.”
C.H. Robinson is now applying GenAI to more complex tasks such as accepting loads, setting appointments for pickup and delivery, and checking on loads in transit. The technology has allowed the 3PL to whittle down the time it takes to complete those tasks from hours to seconds. Before GenAI, it could take an employee as much as four hours to manage and complete a load tender, for example; that task has been reduced to 90 seconds.
The extra time allows employees to focus on more value-added work, like managing exceptions.
“You still have a human in the loop. We still have to monitor and look for exceptions,” Orth says, explaining that C.H. Robinson has designed its workflows to identify issues the GenAI can’t adequately address. “GenAI is not completely hands off the wheel. You still have to build your workflow so that if something doesn’t go right, that’s what our managers work on. [What’s changed is that those managers] are now going to be doing more strategic work.”
Orth credits C.H. Robinson’s software developers for much of the success of the GenAI program.
“We’re fortunate that we have a lot of talented developers who rolled up their sleeves and started learning this,” Orth says, adding that the company also works closely with Microsoft on its GenAI projects.
IMPROVING CUSTOMER SERVICE
DHL Supply Chain is taking a somewhat different approach in its venture into GenAI. The 3PL is deploying a suite of AI applications that are enhancing the company’s data management and analytics capabilities—which, in turn, allows it to provide more value, improve the customer experience, and cut the time it takes to deliver logistics solutions to clients. DHL partnered with Boston Consulting Group to develop the solutions.
The first application is a data cleansing tool that DHL’s in-house design engineers—who develop logistics solutions for shippers—use to clean, sort, and analyze data submitted by potential customers. The tool helps those designers build better transportation routes, as one example.
“This GenAI tool does all that data management for the engineers and allows them to fast forward to the design phase—so [they can] respond to the customer quicker and, at times, [with a] more thorough proposal for their evaluation,” Walters explains.
A second GenAI application supports DHL’s sales team with proposal development. The AI analyzes and manages preliminary RFQ (request for quote) data and fills in the gaps by gathering additional data online, speeding the research and development process and allowing sales to devote more time to specific customer challenges and produce customized solutions.
As Walters explains: “This GenAI tool that business development uses can read through an entire RFQ [and then] go out on the internet and find things like the annual shareholder report for that company …. That helps us identify the key items that are important to that customer and put forward a well-thought-out [proposal] on how we can improve [their] strategy.”
Walters says both tools are part of the company’s broader mission to apply robotics and automation on a large scale.
“Our vision is to deploy strong robotic solutions and [offer] best-in-class data management and data availability,” he explains. “GenAI is the marrying of those two. It’s a robotic solution that’s available to the masses at DHL … Being able to bring GenAI to the fingertips of thousands of associates and increase their efficiency—that allows us to do more to provide value to our customers.”
UNLEASHING OPPORTUNITY
Orth and Walters agree that GenAI is here to stay in supply chain, largely on account of its ability to streamline operations without pressuring customers to change their ways.
“We saw the ‘unlock’ with the unstructured data, which is a big opportunity within the supply chain,” Orth says. “People like to [stick with] their [own] processes; they don’t like to change their ways. [With GenAI], we’re able to unlock those opportunities.”
As some see it, AI is a technology that has finally found its footing in logistics and supply chain, and will only grow from here.
“What’s interesting to me is that AI is not new. It’s really been around for decades,” Walters says, pointing to the Roomba vacuum cleaner and virtual assistants like Siri and Alexa as examples of the technology in action. “AI is just getting the [media attention] now, and we’re seeing it more in the professional work environment.
“I think there is a broad desire to adopt AI and a strong appetite for it.”
