How Delivery Organizations Can Gain A CX Advantage With AI
Satish Natarajan is CEO and Co-Founder of DispatchTrack, a global leader in last mile delivery technology and customer experience.
OpenAI’s Sam Altman recently shared a piece of AI-generated writing on X, stating that it was “the first time i [sic] have been really struck by something written by AI.” There was considerable debate about whether the text in question really was moving—but you could argue that that debate missed an important point: The boundaries of AI technology have been pushed so far that we take its ability to produce boring, run-of-the-mill, correct responses as a given.
Blink and you could miss it, but the fact that systems like GPT-4 and Gemini can produce predictable, mundane responses to queries is huge for logistics providers, retailers, distributors and anyone else who deals with logistics. It means that the technology can finally be leveraged in a low-risk, customer-facing way to enhance the delivery experience.
What do AI deployments in delivery logistics look like?
It’s easy to get bogged down in the heady aspects of this technology, but the practical implementation of an AI-powered customer service agent at this point would be fairly straightforward:
• As part of the normal cadence of customer delivery notifications, you send a text message with an AI-powered agent enabled.
• On the thread, the customer sends a new text message asking for their order ETA.
• Here, the AI acts as a first line of defense. In a natural, conversational way, the agent retrieves the ETA (and any other relevant delivery information) and texts it to the client.
• If the client needs to make corrections or adjustments to an order—like rescheduling or removing items—the agent could handle the request on the backend, updating the customer’s data accordingly.
• In cases where the agent can’t handle the client request, it could seamlessly escalate to a human who can help, providing the customer service rep with the conversation history and other context that they need.
Ten years ago, this would have looked like a magic trick, but we’ve reached the point where it seems almost mundane compared to what the latest large language models (LLMs) are capable of. That’s what makes it the perfect time to start integrating this technology into the last mile of the supply chain.
Why is AI a game-changer for customer delivery experience?
By adopting this technology now, you can gain a competitive advantage in a handful of ways.
1. Offer 24/7 support to customers via AI agents.
Unless you have a call center staffed around the clock, you can’t guarantee a live customer support rep or salesperson will be ready to handle a customer’s late-night query. There might not be many cases of customers needing to update their order details at three in the morning, but when the situation arises, it can be hugely frustrating.
When you integrate an AI-powered agent into the process, that’s no longer a concern. Customers get their queries resolved and make adjustments to their orders 24/7. AI agents are always on—so your team doesn’t have to be.
2. Provide instant responses to inquiries.
We can take the logic of the always-on AI agent a step further: no more waiting for a human customer service rep to get back to customers. Instead of crossing their fingers for a quick reply, delivery customers can get instant answers to questions about delivery ETAs and more.
This helps customers feel connected and in-the-loop. It improves confidence—they can get the information they need, when they need it—which in turn decreases the odds of missed and failed deliveries. A few years from now, I expect people to think of instant answers to their inquiries the same way they think of real-time delivery tracking: a standard part of the modern delivery experience.
3. Level up your customer support team.
Leveraging an AI-powered agent to speed up responses gives you some obvious quick wins: Your customers get the information they want precisely when they want it. In the long run, however, the biggest impacts may come from the way this technology empowers your customer support staff and other teams.
By cutting down the time your team spends responding to the same customer questions over and over again, you can free them up to spend their time and attention where it really matters. This is a classic example of AI augmenting human capabilities. With more time to devote to high-impact activities, the humans on your team can provide more personalized service and smarter, faster issue resolution.
AI can help improve the experience on the customer support team’s end as well. It can summarize key information from any previous conversations with the customer. It can help draft responses quickly. It can even potentially analyze photos to contextualize damage claims. Deployed in a smart, human-centric way, this kind of AI augmentation can improve performance—and potentially help businesses accomplish more with a smaller team.
4. Deliver on time with smarter routing and scheduling.
However sophisticated your AI deployment may be, you still have to get the logistics fundamentals right: You have to deliver on time.
LLMs get most of the headlines around AI these days, but more tried-and-true applications of machine learning and AI can also work in the background to help you ensure a solid foundation for logistics operations. In route optimization, you can leverage AI to turn operational data into significant improvements in ETA accuracy—meaning you can consistently get the right goods to the right customer at the right time.
AI is here to stay; it’s time for delivery businesses to take advantage of it.
Developments in AI have been so quick in the past two years that you could easily miss important milestones—especially in an industry like logistics that’s traditionally cautious about adopting new technology.
But AI has breezed past the point where it can be safely deployed in a customer-facing way. McKinsey found that more than 70% of businesses are already using AI in at least one function—and that number is sure to grow. I expect customer experience to be the next frontier for a large number of logistics organizations—and the ones who adopt AI early will gain a distinct competitive advantage.
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