How Has AI Impacted Logistics in 2025 So Far?

After more than 120 years in business, C.H. Robinson is still evolving. They’ve managed to pull themselves out of a recent downturn and weather a difficult economic situation that’s hitting other shippers hard—and they credit a huge portion of that recent success to AI.

Even a couple of years ago, there would have been a small camp of unsurprised AI enthusiasts compared to a much larger crowd of relative skeptics. But in the intervening time AI (generative and agentic AI in particular) has evolved from a party trick to a tool that can be leveraged in powerful ways to streamline logistics. 

Maybe that’s why it’s not hard to find examples of supply chain players utilizing AI in new and interesting ways, from Walmart leveraging it to streamline decision-making to Amazon’s latest attempts to utilize AI for improved robotics. Organizations of all shapes and sizes are experimenting with the best ways to leverage capabilities that would have been pure speculation as recently as last year. 

All of this makes for an intriguing technology landscape, but at the same time it can be hard to keep up. If you’re thinking about how to apply this technology to your own logistics operations, you need a bird’s eye view of the actual impact that these technologies are having right now. 

How AI Is Changing the Face of Logistics 

Every logistics business has a different level of risk tolerance, but never before have businesses had to negotiate and renegotiate that risk tolerance so rapidly. There’s a wide spectrum of AI in logistics deployments, ranging from tried-and-tested to cutting edge and untested, but new use cases can move from one end of the spectrum to the other fairly rapidly. 

On the flipside, promising AI use cases on the “untested” end of the spectrum can drop off the spectrum entirely if the technology doesn’t hold up. As a result, it’s not a simple narrative around the real impact of AI in logistics this year—rather, it’s a patchwork of individual businesses figuring out what works and what doesn’t. 

Here’s what we’ve been seeing so far that’s made a real difference for logistics operators:

1. The Future of Driver Empowerment

AI in driver management workflows conjures up images of autonomous vehicles for most people—and that’s something that is having a small impact on parcel deliveries already and projects to potentially become more commonplace in long haul trucking. 

But when it comes to last mile deliveries of big and bulky items (whether that’s kegs of beer or pallets of roofing shingles or washing machines), the real impact of AI has been on making life easier for human delivery drivers. 

For instance, we’re seeing delivery organizations leverage AI to automatically provide stop-level location intelligence to drivers as they go to jobs along their routes. One user described it as being “like having a local expert in the cab.”

This kind of innovation has the potential to boost driver productivity without radically changing the way they do their jobs—and it’s already making that happen. How? By offering useful information about building access, local parking and traffic, and customer requests so that drivers can keep their deliveries on track. 

2. Agentic AI for Customer Experience

As customer expectations in last mile delivery have gotten more stringent, the volume of labor around answering customer questions, dealing with requests, scheduling orders, and keeping customers in the loop has only gotten greater. 

Automation has helped with this to be sure, but this is one of the biggest areas where AI is currently improving life for the customer support teams that would otherwise have to field huge volumes of calls and messages. 

By using agentic AI to handle the front line of messages from customers, logistics businesses are freeing up huge amounts of time for their teams and speeding up response times to customers. As agents are getting more sophisticated, you’re seeing more and more examples of agents collecting surveys and helping reschedule customer orders—all of which boosts productivity and improves performance across the board. 

3. Human-Centered AI

If there’s a theme to the two impacts we’ve looked at closely, it’s this: current AI deployments are most effective when they’re being leveraged to augment the work that humans are already doing. This might not be the case forever, but for the time being it’s human-centered AI deployments that are having the biggest impact in the world of logistics at the moment. 

As we start to see more AI usage in areas like dispatching and reporting, it will be valuable to keep this trend in mind. It can valuable to home in on a single problem and solve it with the shiniest new technology, but there’s also real value to taking a broader view of your entire logistics network—including the technology, assets, and human beings who make it up—and thinking holistically about how they can work together more effectively. 

Above all, that’s one of the top lessons that logistics operators have been learning this year. 

What AI Agents Can and Can’t Do 

One of the other things that businesses across the spectrum have been learning this year is what AI agents can and can’t do. A report from a few months ago showed that AI agents fail at an alarmingly high rate, and that many things that are billed as agentic AI aren’t really AI at all. 

At the same time, groups like BCG are calling it a “strategic imperative.” So how are logistics leaders supposed to navigate the ambiguity here? 

As DispatchTrack’s CEO, Satish Natarajan, noted in a recent article in Forbes, “This is an area where logistics leaders need to leverage their own domain knowledge to make sure their AI vendors can speak their language.” This is on top of properly scoping your AI agents, setting clear boundaries for what they should try to handle, and bringing humans into the loop in the right places. 

This may seem like it’s easier said than done, and it almost certainly is. At the same time, this is somewhere where a human-centric approach—and an approach rooted in your own deep domain knowledge in logistics—can put you in a strong position to cut down the AI failure rate and get a huge amount of value out of new technology as it emerges. 

Looking Ahead: A Data Revolution on the Horizon

For the rest of the year and into 2026, we expect one of the major themes in the world of AI in logistics to revolve around data. Specifically, how do you leverage AI to get more out of the operational data that you’re already collecting. Soon, it could be practically commonplace to be able to query a database in a conversational manner and get an accurate AI generated response. 

This is going to push the envelope even further when it comes to streamlining your logistics operations and helping to boost productivity and reduce costs. And the people who are poised to see the most benefits are those who are already finding ways to leverage AI in logistics. 

And, as ever, one of the keys to success will be partnering with the right AI technology provider.