What Does AI-Powered Shipping Look Like?

According to a recent Gartner article, high performing supply chain organizations leverage AI at more than twice the rate of lower performing businesses. There’s a handful of reasons this might be the case—higher-performing supply chains might be more technologically cutting edge overall, not just in this one area—but the basic fact points to one important idea: AI is already here, and it’s already making an impact in logistics.

Of course, there’s often a big gap between fact and fiction when it comes to AI in any context. While advances in generative AI are still making front page news with some regularity, that’s only one domain within the larger AI umbrella. While the frontiers have continued to move forward, more specialized use cases have been refined and rolled out in multiple different industries—including the supply chain. 

But what exactly do these more specialized AI deployments look like? More specifically, how is AI impacting shipping and delivery, and what does that mean for businesses that deal with logistics?  

How AI Is Impacting Logistics

It’s easy enough to miss it, but AI has been making its presence felt in logistics and shipping for many years at this point. 

Gartner points out that demand forecasting, order management and fulfillment, supply planning, logistics and distribution, and integrated business planning are some of the larger areas where supply chain businesses are investing in AI. That should give you some indication of the extent to which AI is making its presence felt, and also a sense of the breadth of different areas where it can be applied. 

How is AI actually being leveraged in these areas? There’s different answers for different businesses, but with demand forecasting, you might expect businesses to leverage large caches of historical ordering data, combined with information about price fluctuations and economic conditions, as well as many other factors, in order to more accurately forecast changes in demand over time. Many of these deployments will rely mostly on machine learning, which is a branch of AI that leverages complex algorithms to deal with large quantities of data. 

In supply planning, you might see similar technology at work—essentially, leveraging AI to predict the optimal stock levels and in some cases to purchase stock at favorable prices. 

When it comes to last mile logistics, AI and machine learning can be deployed in the route optimization process. That goes for the first and middle miles as well, but it has the potential to be more impactful on more complex routes like the ones you see in the last mile of the supply chain. Here, data from past deliveries and other sources can be leveraged into routes that are more efficient—and ETAs that are more accurate—than a human router could possibly produce by hand. 

The use of generative AI in things like chatbots is also becoming more and more common, albeit less prevalent than the use of AI in areas like the ones we discussed above. This would include the use of something like ChatGPT to power a customer-facing chatbot—an application that has potential promise, but there are still potential hurdles to implementing this sort of thing in a way that actually adds value for customers.   

<< Interested in reducing last mile delivery costs? Read our latest playbook for concrete ways to cut costs >> 

Benefits of AI-Powered Shipping 

Okay, so all of these technology applications are out there and available for supply chain businesses. Thanks to the increasingly widespread use of cloud computing, it’s actually easier than ever before to adopt newer technologies like this without a huge IT lift on your end. But why bother? What are the actual benefits to AI-powered shipping and logistics? 

Let’s take some of the applications on the last mile as a representative example:

• When you optimize routes using AI, you’re able to roll out more efficient routes than you’d be able to generate by hand—or even with legacy software solutions. This saves you money on fuel and driver pay, since your drivers are traveling fewer miles per stop. 
• At the same time, AI can speed up the routing process by analyzing data more quickly than human planners. Rather than spending hours poring over maps and spreadsheets, you can route thousands of stops in minutes. This saves a huge amount of planning time that can then be reinvested in more valuable tasks. 
• In addition to boosting the efficiency of your routes, AI also helps you improve their accuracy—specifically around delivery ETAs. AI-powered shipping is, quite simply, less likely to result in late deliveries than traditional methods. The result is that you can get more deliveries done on each route each day, and you’re much less likely to encounter not-at-homes and unplanned returns as a result. The entire last mile delivery process goes a lot more smoothly, and the result is that you reduce costs in a number of different areas, from redelivery attempts to miles driven. 

Obviously, the impacts will be different depending on what areas of shipping and logistics you’re looking at. But the above should provide a decent example of how this kind of technology benefits delivery organizations. It’s about more than just streamlining processes and saving work for human planners—rather, it can be a way to remove disruptions and exceptions by empowering smarter plans and better execution. 

For shippers, there will always be risks that come with trotting out cutting edge technology and being an early adopter of something that isn’t tried and tested. But many of the AI applications we’re discussing have long since aged out of that category—they’re now tried and true methods for increasing efficiency and decreasing costs. 

What Does the Future Hold for AI in the Supply Chain? 

Looking ahead to the future of supply chain management and shipping, we can be pretty confident that AI and machine learning aren’t going anywhere. While the world speculates wildly about what large language models can evolve into, practical AI applications will continue to be developed and rolled out in ways that may not make splashy headlines, but will certainly make real impacts for the people who work in this field. 

For instance, we mentioned AI-powered chatbots above. While it’s not yet clear how receptive customers will be to this kind of technology deployment, it’s possible that we’ll see more software solutions offering AI-generated “suggested responses” in customer interactions to speed up the process of resolving issues. Likewise, generative AI might prove to have a place in customer communications more broadly. 

On the other end of the spectrum, things like route optimization that are already leveraging AI and machine learning will theoretically only get smarter and more sophisticated from here. Those who are already leveraging this technology will be poised to take the greatest advantage of new advances. 

Zooming out to the supply chain as a whole, AI has the potential to make logistics operations overall more efficient and cost-effective through a mix of predictive analytics and other similar use cases. It’s difficult to predict exactly what the world of AI-powered shipping will look like a few years from now, but we can be fairly confident that there will be considerable evolution—if not revolution—in how technology is leveraged to help delivery organizations reduce costs and delight their customers.