Separating Fact from Fiction: Real AI in Last Mile Delivery

Artificial intelligence (AI) is the hot topic in almost every industry, and last mile delivery is no exception. As is often true of new technologies, the prospect of vast improvements in processes and lower costs is mesmerizing. However, as we’ve learned, the devil is in the implementation, and a sharp divide has emerged in last mile software between platforms using AI that’s little more than hype as a marketing tool and those delivering real AI and real benefits.

What Is Real AI?

Not all AI is created equal. Just because a developer says its product is “AI-powered,” doesn’t mean that AI is being used to its full potential, or even that it’s doing useful work inside the platform. Like the word “organic” in food, “AI” can mean anything from “the engineers used ChatGPT to do some research” to having a significant amount of AI and machine learning (ML) processes baked in. Hype AI is just adding “AI” to the marketing materials even if the software makes little use of actual AI to improve results.

Real AI for the last mile uses sophisticated algorithms to perform its basic functions, from sorting stops into routes, optimizing fleet capacity, and predicting highly accurate ETAs to behind-the-scenes—but critical—functions such as planning optimal sales territories, analyzing driver behavior, and identifying patterns in performed routes to highlight opportunities for improvement. In doing this, the AI combs through vast amounts of data from every past route performed.

How to Tell Reality from Hype

As any route specialist will tell you, the complexity of managing the last mile can be overwhelming. AI is ideally suited to cutting through that complexity to produce simple, actionable plans, suggestions, and insights.

To do that, the software needs data—lots of data. Collecting, storing, and analyzing data points from every part of the process (i.e. capacity and equipment of every vehicle in your fleet, service time records of each driver, customer preferences, actual arrival times vs ETAs, updated traffic information etc.) is essential.

So the first question you need to ask is how many (and which) factors are used in computing routes and ETAs. Software that simply computes the shortest distance between stops is not going to optimize your fleet or keep your customers satisfied. Some of the important factors include:

• Capacities and equipment for each vehicle in your fleet
• Customer preferences for delivery windows
• Driver service times by job type for each driver and crew
• Evolving traffic conditions
• Shuttle routing to remote DCs or hubs
• Need to reload

Are routing results fixed or can you make manual adjustments without degrading efficiency? Sophisticated AI can take manual adjustment inputs and reconfigure a day’s worth of routes in seconds, not hours. Especially for B2B deliveries (from a food or beverage wholesaler or a building supplies vendor), defining a base route that satisfies customer order patterns and preferred delivery days/times that can then be updated when someone orders extra cases of canned tomatoes or wooden studs—instantly and efficiently—is essential.

Beyond routing, ask what other functions AI supports in the platform? The complexity of the last mile extends far beyond routing, embracing everything from processing orders to creating routes, assigning loads to vehicles to optimize fleet capacity, loading, performing the routes, maintaining communication with customers, delivery/installation services, obtaining proof of delivery and analyzing results. While standard software can do some of these things, real AI does them faster and extends capabilities, such as looking for patterns in results that can be exploited to achieve better optimization.

AI Chatbots vs Intelligent Two-Way Communication

AI chatbots are a novel development in last mile delivery, but are they an improvement or the latest shiny object?

While they may make us feel good, chatbots aren’t necessarily preferred by most consumers. A 2023 research study found that 86% of those surveyed preferred human agents to chatbots, and users reduced purchases by more than 79% when communicating with chatbots on e-commerce sites. Users said they believed that chatbots can’t provide high quality communications, leading to less loyalty to the platforms and increased complaints (source).

The reasons human agents connected via two-way chat are perceived as more capable is obvious: They can assess a customer’s situation (not just their request) and quickly provide a solution if there’s a problem. They may need to reach out to the driver, or connect the driver with the customer in real time, or call in the operations team for a quick fix. They can make a phone call to the consumer and speak with them if necessary.

Of course, there’s still a place for chatbots in the last mile. It’s just a matter of being intentional about how you use them, and of making sure that you’re deploying them in a way that augments real human interactions, rather than trying to replace them. 

Clients have found the robust suite of customer communications tools in DispatchTrack to be highly effective in increasing both first attempt delivery rates and customer satisfaction. DispatchTrack’s platform provides the technological muscle for varied communication types and channels:

• Self-scheduling online using capacity aware delivery windows
• Automated pre-delivery and day of delivery reminders
• Route start notifications
• ETA updates  
• Live delivery tracking
• One stop away notification
• Arrival notification
• Proof of delivery
• Satisfaction survey invitation

At any point in the process, the customer can engage directly with a human. Together, this structure allows customers to set their own delivery windows (while AI ensures your fleet capacity remains optimized), resulting in far fewer not-at-homes. Continuous communication about that delivery gives the customer control over the process while also minimizing where-is-my-order calls. Customers are empowered, delivery rates go up, communication is simple, customer satisfaction increases and—importantly—costs are minimized. 

That is intelligent communication. It may not be as sexy as an AI chatbot, but it can be more effective in delivering the “high touch” experience that customers desire. 

Learn how Morris Furniture Company improved their NPS by leveraging DispatchTrack for exactly the kind of experience we've been talking about: 

Delivering the Benefits of AI Now

AI is not just something that promises a better future: The AI and ML capabilities baked into DispatchTrack are already revolutionizing the last mile. By creating algorithms that dig into the hard complexities of delivery and finding workable solutions, DispatchTrack has been building AI reality for years. When you see a promise about what AI can do for you, look beneath the surface and make sure what’s being offered is real AI, not just hype.