Everyone’s talking about autonomous supply chains and autonomous vehicles powered by AI—and the upshot seems to be that they’re never quite as close to being a reality as we would like. Part of this comes down to the AI problem, in which anything that AI can actually do effectively is no longer viewed as cutting edge technology (in the way that ChatGPT is “glorified autocomplete”).
But another part of the equation is that a lot of the chatter about AI in the supply chain in general—and AI for drivers in particular—misses the real-life ways that AI is already having an impact.
Case in point: Driver AI. AI isn’t replacing drivers in the last mile (at least not for big and bulky and scheduled deliveries), but it is making their lives easier and improving productivity.
In this article, we’ll dig into exactly how it’s doing that and what the future might hold in terms of AI for delivery drivers. If you’re interested in how the world of delivery and logistics will be leveraging new technology to improve efficiency and boost performance, this will be a crucial trend to keep an eye on.
Driver AI may be in its relative infancy at the moment, but it already represents a powerful technology that delivery businesses can leverage to reduce costs. It’s helping drivers to do their jobs more effectively and keep their focus on providing a great delivery experience to the customer and positively reflecting your brand.
How is AI doing that, exactly? Right now, the most prominent AI use case for drivers takes the form of automated voice briefings for each stop along a route. Here, AI leverages a combination of your team’s delivery data and location information from around the web to provide drivers with all the information they need to get the job done quickly and efficiently.
That might include:
These are the kinds of things that can either get overlooked or take the driver by surprise—resulting in slower delivery service with potential downstream impacts on the rest of the route.
By inserting this kind of intelligence seamlessly into the driver’s existing workflow, you can use AI to help smooth out the driver’s experience and delight your customers in the process.
When it comes to executing on delivery routes, a little extra assistance can go a long way. Too often, drivers feel like they’re on their own once they get out onto the road, and if problems crop up they have only their own resources to deal with them.
With effective driver AI deployments, delivery organizations are able to flip that paradigm on its head. Drivers are empowered with the information they need, when they need it.
This has a few direct, immediate benefits:
Most of the time, these impacts will add up to a few minutes per stop. That might not seem like a lot—but when you scale it up to your entire delivery operation, you’re talking about completing more deliveries per day at a lower cost, with an added bonus of ensuring more happy customers.
These impacts aren’t just hypothetical. At DispatchTrack, we’ve seen adopters of our Driver AI tool like Updike Distribution Logistics achieve immediate results:
Director of Logistics Bernis Berber had this to say about the impact of the DispatchTrack’s Driver AI feature: "The first time I tested it at a highrise location, Driver AI nailed every detail—parking, security check in, gate codes, even the elevator. It’s like having a local expert in the cab."
That captures the power of AI for delivery drivers in a nutshell.
The kind of seamlessly-integrated driver AI workflows that we’re discussing aren’t complicated to deploy. For what we described above, all you really need is a full-featured driver mobile app and a technology provider that’s committed to innovating in the field of AI.
On a deeper level, the best way to ensure an effective driver AI deployment is to make sure you’re using connected, intelligent technology that covers the entire last mile journey—including driver management—and beyond. A disjointed solution that lacks a connected mobile app, or a software platform that doesn’t give you real visibility into your logistics, is going to set you up for disjointed, low-visibility AI implementation.
As AI for drivers becomes more sophisticated, the best way to ensure you’re able to get the maximum benefit is to lay a strong technology foundation beforehand. All of the AI innovation in the world just amounts to bells and whistles if you can’t achieve connected logistics visibility.
One other key is to think about adoption and change management during the initial stages of AI deployment. Drivers will happily use anything that legitimately makes their lives easier, and they’ll avoid using anything that feels like a chore.
Driver AI that slots seamlessly into drivers’ existing workflows and requires little to no training is your best bet to generate quick wins and sustainable success. For more sophisticated driver AI integrations, this same litmus test will apply.
At DispatchTrack, we pride ourselves on being pioneers in the field of AI in logistics. Our route optimization has been powered by AI for many years, and we’ve recently expanded our portfolio to include DT Agent (an AI-powered chat agent that sits atop two-way messaging with customers) and Driver AI.
With Driver AI, our customers are gaining delivery efficiency and powering drivers to do their jobs more effectively. Drivers get AI-generated location intelligence for each stop, so they’re prepared for what’s up ahead. The best part is that it’s easy to implement and slots seamlessly into the existing workflows on the driver mobile app.
If the idea of leveraging AI for delivery drivers in a straightforward, low-risk, and proven way appeals, why not get in touch with one of our experts today and get a briefing?