Fuel Costs Are Pushing Logistics Beyond Routing To Orchestration—Here's How AI Can Help

Satish Natarajan is CEO and Co-Founder of DispatchTrack, a global leader in last mile delivery technology and customer experience.

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​AI agents baked into everything from drones to billing software are already saving logistics businesses hundreds of hours of labor per day. This is good news for an industry that’s strapped for person-power and struggling with astronomical fuel costs, but it also misses a huge part of the story.

While AI has been showing off its power to reduce costs, it’s also been subtly reshaping entire logistics processes from the ground up. ​​

Logistics has long been defined by reactive processes. Orders come in, and when the items are available to schedule, they’re moved into a delivery management system and routed onto trucks. If there are delays or the customer has issues, then the team has to scramble to resolve the situation and get deliveries back on track. ​

At best, businesses manage by exception, and at worst, they’re flying blind. Often, decision makers don’t even have visibility into delivery costs or customer satisfaction. The result is that it’s nearly impossible to craft consistent delivery experiences across an entire network, let alone do so in a cost-effective way. ​

AI has already shown its ability to drive toward increased visibility and streamlined customer experience, but can it also move us from a reactive logistics model to a proactive and intelligent one that actually meets the challenges faced by distributors and retailers at this moment? ​

The short answer is: Yes, it can. With the advent of sophisticated agentic AI systems in the supply chain, we’re moving out of the era of simply routing deliveries and into the era of delivery orchestration.

Cost Pressures Mean That Routing Is No Longer Enough​

This April, average fuel costs across the U.S. topped $4 a gallon for the first time since 2022, which means that the biggest line item on every delivery organization’s budget has just ballooned significantly. This isn’t the kind of cost pressure that you can fight by shaving off a few miles here and there. ​

Modern route optimization tools that leverage machine learning can improve route efficiency and density (to the tune of 15% or more for best-in-class solutions), which can go a long way toward making costs more manageable. But where the real power lies is in placing those machine learning-powered capabilities in a larger, more integrated context. ​

That’s where delivery orchestration comes into play. While routing is essentially treating deliveries as a problem to be solved, delivery orchestration is a way of connecting your dispatchers, customers, drivers, contractors, third parties and everyone else in the logistics process, and putting them in a position to operate efficiently and effectively. ​

The numbers on the size of the delivery orchestration market (which is growing quickly) strongly suggest that this shift is already underway. But the confluence of increasing costs and improved AI performance is driving a real acceleration, and distributors and retailers who stick with the old way of doing things risk getting left behind.

The Power Of AI Agent Systems In Delivery Orchestration

​​What do these AI agents and processes actually look like? They can take multiple forms, but in delivery management, the most powerful paradigms that we’re seeing involve agentic systems for interfacing directly with customers.

Rather than simply answering questions about order details and ETAs, these systems can take action based on real-time conversations with customers.

​Here’s how this might play out:

The customer places an order, and an AI system reaches out to conversationally schedule a delivery time slot that works for both parties. If the AI notices that a delivery address is in an apartment building, it automatically reaches out to the customer with a site-readiness questionnaire.

Between the initial conversation and the delivery, the AI is always available via text or chat to deal with anything from adding delivery instructions to double-checking order details to even rescheduling a delivery. When the driver is headed to the delivery site, an AI-generated voice memo is read out on their mobile device to provide the customer’s notes and any other context (building and elevator access, gate codes, etc.).

Post-delivery, AI verifies that the photographic proof of delivery actually contains the correct items and engages the customer in a quick conversational survey.

​This is where orchestration really starts to become a reality. It represents less of an incremental shift aimed at trimming costs and more of a paradigm shift that reimagines the entire delivery management function as a connected, cohesive, value-adding process that’s nearly frictionless for end customers.

Of course, even as of last year a huge proportion of companies were seeing little to no return on their AI investments. It’s not a panacea or something to set and forget. It can extend a lean team and speed up workflows, but it can’t necessarily fix a broken process or turn unprofitable deliveries into profitable ones. It rewards investments in visibility and connectivity across your logistics network, but it can’t replace them. ​

Looking Forward: Orchestration Is The Next Competitive Battleground

​As delivery orchestration becomes a more common way of looking at the process of getting the order to the end customer, AI will become foundational to more and more processes—even as they undergo transformation. This might be anything from streamlining billing clients and settling with drivers to extracting more powerful insights from the supply chain than ever before.

​The era of point solutions that treat the first mile, the middle mile, the last mile and other processes as disparate activities is drawing to a close. Instead, AI is already helping distributors and retailers to take greater control of the entire logistics chain from the first mile to the last mile and beyond.

​When distributors stop merely routing and start orchestrating, new grounds will continue to open up for AI to streamline, improve and redefine logistics processes. Drawing actionable insights out of logistics data will get easier.

​These two approaches, AI and orchestration, must go hand in hand to yield results. But when the ability to provide low-friction experiences becomes a competitive differentiator, businesses with an existing AI-powered orchestration layer will be poised to outcompete their peers. ​

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