Most of the AI we’re seeing in the wild right now isn’t actually AI—it’s just RPA... From my perspective, true AI is still not being widely deployed. But when it is, and when it’s done well, it’s exciting. It has the potential to truly empower people to focus on revenue-generating tasks.
Supply chain and logistics are ready for a shake-up. Some forward thinking solution providers are working AI into their systems to realize efficiencies; however, some experts argue that much of what's labeled as AI isn't truly intelligent—at least not yet.
According to Robert Bain, Director of Partnerships at GLCS, what most companies are deploying currently is better described as automation. In order to really get ahead with AI, we need much deeper frameworks to rebuild the foundations of the industry at large, he says.
True AI remains elusive: Bain starts off with a strong stance: "Most of the AI we're seeing in the wild right now isn't actually AI—it’s just RPA; it's task automation. That said, I expect the terminology will adjust over time. From my perspective, true AI is still not being widely deployed. But when it is, and when it's done well, it's exciting. It has the potential to truly empower people to focus on revenue-generating tasks."
The distinction matters, Bain says, especially when evaluating the impact of the technology. "True AI is capable of learning. Whether powered by small or large language models, it improves over time in ways that mirror human learning," he explains. "When integrated effectively, it allows teams to shift away from repetitive tasks and focus on revenue-generating activities—but such use cases are still relatively rare."
Aversion to failure: According to Bain, the slow adoption curve is due to industry dynamics. With tight margins and high operational risk, logistics companies tend to be cautious about new technology. "This industry has long resisted change, and for good reason," he says. "Carriers and 3PLs operate on thin margins. Most cannot afford to invest heavily in new tools without a clear return on investment. They're reluctant to become early adopters if the risk of failure is significant."
This industry has long resisted change, and for good reason. Carriers and 3PLs operate on thin margins. Most cannot afford to invest heavily in new tools without a clear return on investment. They’re reluctant to become early adopters if the risk of failure is significant.
Manual processes: Still, Bain sees promising applications in both front-end and back-end operations—especially in areas where workflows remain highly manual. "In some organizations, there are hundreds or even thousands of people whose primary responsibilities include scheduling, load tracking, and appointment setting. These processes are still largely manual and represent a major opportunity for improvement."
He also points to back-office functions, where automation is already driving efficiencies. "We're seeing success with tools that handle document collection and preparation," Bain says. "But these gains come with new challenges. There are instances where fraudsters have submitted fake bills of lading, driver's licenses, and receipts. Many automation tools are not equipped to detect this level of fraud, which can result in payouts for shipments that never occurred."
Cybersecurity risk: Bain cautions against the idea of a plug-and-play AI solution, noting that the industry's current infrastructure isn't ready to support it. "There's an appealing notion of a universal system that can be seamlessly integrated across operations," he says. "But the cybersecurity standards in this space are still inadequate. The environment is too open, and that poses a significant risk."
